To see the other types of publications on this topic, follow the link: Condition Monitoring.
Dissertations / Theses on the topic 'Condition Monitoring'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 dissertations / theses for your research on the topic 'Condition Monitoring.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse dissertations / theses on a wide variety of disciplines and organise your bibliography correctly.
1
Samouhos, Stephen V. (Stephen Vincent) 1982. "Building condition monitoring." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/61611.
Full textAbstract:
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2010.Cataloged from PDF version of thesis.
Includes bibliographical references (p. 201-206).
The building sector of the United States currently consumes over 40% of the United States primary energy supply. Estimates suggest that between 5 and 30% of any building's annual energy consumption is unknowingly wasted due to pathologically malfunctioning lighting and comfort conditioning systems. This thesis is focused on developing analytical methods embodied within useful software tools to quickly identify and evaluate those building system faults that cause large building energy inefficiencies. The technical contributions of this work include expert rules that adapt to HVAC equipment scale and operation, a general framework for applying probabilistic inference to HVAC fault detection and evaluation, and methods for sorting fault signals according to userdefined interests such as annual cost of energy inefficiencies. These contributions are particularly unique in their treatment of model and measurement uncertainty within the fault inference, and the careful consideration of user interests in fault evaluation. As a first step to developing this general framework for fault detection, I targeted first order faults such as simultaneous heating and cooling and imbalanced air flows within several large air-handling units in three buildings on the MIT campus. Experiments included the purposeful implementation of mechanical and software control programming faults on otherwise fault-free equipment. Between the five pieces of equipment, the software system successfully identified all previously known and experimentally implemented faults, as well as additional faults that had not been previously identified or imposed during the experiment. User testing and experiments show that embracing uncertainty within HVAC fault detection and evaluation is not only paramount to judicious fault inference but it is also central to gaining the trust and buy-in of system users who ultimately can apply fault detection information to actually fix and improve building operations.
by Stephen Samouhos.
Ph.D.
2
Danielson, Hugo, and Schmuck Benjamin von. "Robot Condition Monitoring : A first step in Condition Monitoring for robotic applications." Thesis, Luleå tekniska universitet, Institutionen för teknikvetenskap och matematik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-66011.
Full textAbstract:
The industrial world is in constant demand for faster, cheaper and higher quality manufacturing. Robot utilisation and automation has evolved to become a necessary asset to master in order to stay competitive in the global market. With the growing dependency on robots, unexpected downtime and brakedowns can cause devastating loss of revenue. Consequently, this has lead to an increased importance for an accurate condition based way of performing robotic maintenance. As of writing, robots are predominantly maintained through time dependent maintenance. Part replacement is based on statistical models where maintenance is performed without taking the actual robot condition into consideration. As a result an overall level of uncertainty is ensued, where lacking the ability to properly diagnose the robot, also leads to superfluous repairs. Because of the costly impact this has on production, a condition based maintenance approach to robots would yield increased reliability at a lower cost of maintenance. This research focuses on trying to monitor vibrations in a robot, so as to infer about wear and to provide a first step in vibration based Robot Condition Monitoring. This research has been of multidisciplinary nature where robotics, tribology, mechanical component, signal analysis and diagnosis theory have overlapped in several areas throughout the project. The research has provided a vibration baseline and trends of the theoretical bearing defect frequencies for a hypocycloid gearbox installed on an ABB IRB6600 robot. The gearbox was not worn to a level that a severe gearbox degradation was irrefutably detectable and analysable. Accelerometers normally used on wind turbines were used for the project, and are believed to be sufficiently successful in capturing bearing related signals to accredit it for continued use at the preliminary stages of Robot Condition Monitoring development. A worn RV410F hypocycloid gearbox, was dismantled and analysed. Bearings found inside indicate high degrees of moisture corrosion and extensive surface wear. These findings had decisive roles in what future work recommendations where presented. Areas with great potential are condition monitoring through the use of Acoustic Emission and lubrication analysis. Further recommendations include investigating signal analysis techniques such as cepstrum pre-whitening and discrete wavelet transforms.
3
Blakeley, Bruce. "Audio plant condition monitoring." Thesis, Swansea University, 2001. https://cronfa.swan.ac.uk/Record/cronfa42239.
Full textAbstract:
Accelerometers are widely used in plant condition monitoring (PCM) to diagnose faults in rotating machinery. This can be expensive, and is typically only used to monitor the condition of critical machines. The objective of this project is to develop a system, using microphones, that could screen less critical machines for faults. Microphones are non-contact sensors that can be placed away from the machines, to avoid damage. If the data gathered by the microphone is reduced to a single parameter, that increases with wear, then analysis would be greatly simplified. This system could be used to provide basic PCM screening for equipment not considered important enough for routine vibration monitoring. To achieve this objective, a test-rig was designed and constructed, consisting of a motor, gearbox and load. Various faults were introduced into the test-rig, and a microphone used to record the sound. These results were then compared to accelerometer readings. Time synchronous averaging (TSA) was employed to increase the signal to noise ratio. It was proven that Kurtosis and crestfactor of a microphone signal both increase, if used with a high pass filter, when an impacting fault such as a broken gearbox tooth was introduced into the test-rig. It proved harder to reduce the sound of other non-impacting faults, such as misalignment, into a single parameter. The technique was tested in an industrial environment with a 100 dB background noise level. It was shown that the technique was capable of detecting faults even with a signal to noise ratio of -15 dB. A one dimensional FEA model was created, with six degrees of freedom, modelling the test-rig's vibrational behaviour. This was used to investigate the affect of a broken tooth, and to explain the increase in noise as the tooth passing frequency coincided with a resonance.
4
Shen, Chia-Hsuan. "Acoustic Based Condition Monitoring." University of Akron / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=akron1341797408.
Full text
5
Stander, Cornelius Johannes. "Condition monitoring of gearboxes operating under fluctuating load conditions." Thesis, University of Pretoria, 2005. http://hdl.handle.net/2263/25604.
Full textAbstract:
Conventional gearbox vibration monitoring techniques are based on the assumption that changes in the measured structural response are caused by deterioration in the condition of the gears in the gearbox. However, this assumption is not valid under fluctuating load conditions, since the fluctuating load will amplitude modulate the measured vibration signal and cause the rotational speed of the system to change. In general monitoring of machines subject to fluctuating load conditions is dealt with by considering the constant load conditions on gearboxes or during free rotational tests. The need to monitor the condition of large gearboxes in mineral mining equipment has attracted greater interest in order to improve asset management. An inherent need for signal processing techniques, with the ability to indicate degradation in gear condition, under fluctuating load conditions exist. Such techniques should enable the online monitoring of gearboxes that operate under fluctuating load conditions. A continued flow of up to date information should consequently be available for asset and production management. With this research, a load demodulation normalisation procedure was developed to remove the modulation caused by fluctuating load conditions, which obscures the detection of an incipient gear fault conditions. A rotation domain averaging technique is implemented which combines the ability of computer order tracking and time domain averaging to suppress the spectral smearing effect caused by the fluctuation in speed, as well as to suppress the amplitude of the vibration which is not synchronous with the rotation of the gear shaft. It is demonstrated that the instantaneous angular speed of a gearbox shaft can be utilised to monitor the condition of the gear on the shaft. The instantaneous angular speed response measurement is less susceptible to phase distortion introduced by the transmission path when compared to conventional gearbox casing vibration measurements. A phase domain averaging approach was developed to overcome the phase distortion effect of the transmission path under fluctuating load conditions. The load demodulation normalisation and rotation domain averaging signal processing procedures were applied to both the conventional gearbox casing vibration and instantaneous angular speed measurements prior to the calculation of a smoothed pseudo Wigner-Ville distribution of the data. Statistical parameters such as the energy ratio were calculated from the distribution. These parameters could be monotonically trended under different load conditions to indicate the degradation of gear conditions.Thesis (PhD (Mechanical Engineering))--University of Pretoria, 2005.
Mechanical and Aeronautical Engineering
unrestricted
6
Sæther, Jørgen Hagemo. "Choke condition and performance monitoring." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for marin teknikk, 2010. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-11623.
Full textAbstract:
Sand production is a common complex problem in the oil and gas industry, and choke valves is typically suffering for this in form of erosive damage. The degree of erosive damage is decided by many different factors where the flow rate velocity and the sand rate are the most important ones. Much effort has been spent on ways of reducing the choke erosion to be able to maintain the oil and gas production at an optimal level with attention to increased profit, safety and availability. Use of Computational Fluid Dynamics (CFD) has been essential in this work by simulating flow through the choke valve for optimizing the choke design, choosing the optimal erosion resistant material, coming up with improved erosion-related models, and optimal operational procedures of the choke. Producing with Acceptable Sand Rate (ASR), which means allowing a certain degree of sand erosion in chokes, have proven to be a successful way of maintaining the oil and gas production at an optimal level. To satisfy ASR-production, demands are made on an optimal use of condition and performance monitoring equipment and tools. The use of the condition and performance monitoring tool INSIGHT (from ABB) has in general proven to be successful for satisfying the ASR-production on different Statoil fields, including Statfjord which is in this thesis the area of focus regarding the use of INSIGHT. Important condition monitoring data such as sand rate, flow rate and pressure necessary to say something about the choke erosion status in INSIGHT must be as good as possible, because the quality of the results are limited by quality of the input data. In this thesis, INSIGHT has been presented, discussed and tested to be able to come up with possible limitations and improvements with special attention to condition monitoring (input) data used in INSIGHT.
7
Moussa, Wael. "Thermography-Assisted Bearing Condition Monitoring." Thesis, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/31379.
Full textAbstract:
Abstract
Despite the large amount of research work in condition based maintenance and condition monitoring methods, there is still a need for more reliable and accurate methods.
The clear evidence of that need is the continued dependence on time based maintenance, especially for critical applications such as turbomachinery and airplane engines. The lack of accurate condition monitoring systems could lead to not only the unexpected failures as well as the resulting hazards and repair costs, but also a huge waste of material and time because of unnecessary replacement due to false alarms and unnecessary repair and maintenance.
Temperature change is a phenomenon that accompanies every dynamic activity in the universe. However, it has not been adequately exploited for mechanical system condition monitoring. The reason is the slow response of current temperature monitoring systems compared to other condition monitoring methods such as vibration analysis. Many references inferred that the change in temperature is not sensible until approaching the end of the monitored component life and even the whole system life (Kurfess, et al., 2006; Randall, 2011; Patrick, et al., March 7-14, 2009).
On the other hand, the most commonly used condition monitoring method, i.e., vibration analysis, is not free from pitfalls. Although vibration analysis has shown success in detecting some bearing faults, for other faults like lubrication problems and gradual wear it is much less effective. Also, it does not give a reliable indication of fault severity for many types of bearing faults.
The advancement of thermography as a temperature monitoring tool encourages the reconsideration of temperature monitoring for mechanical system fault detection. In addition to the improved accuracy and responsiveness, it has the advantage of non-contact monitoring which eliminates the need for complex sensor mounting and wiring especially for rotating components.
Therefore, in current studies the thermography-based monitoring method is often used either as a distinct method or as a complementary tool to vibration analysis in an integrated condition monitoring system. The main objectives of this study are hence to:
1. Define heat sources in the rolling element bearings and overview two of the most famous bearing temperature calculation methods.
2. Setup a bearing test rig that is equipped with both vibration and temperature monitoring systems.
3. Develop a temperature calculation analytical model for rolling element bearing that include both friction calculation and heat transfer models. The friction calculated by the model will be compared to that calculated using the pre-defined empirical methods. The heat transfer model is used for bearing temperature calculation that will be compared to the experimental measurement using different temperature monitoring devices.
4. Propose a new in-band signal enhancement technique, based on the synchronous averaging technique, Autonomous Time Synchronous Averaging (ATSA) that does not need an angular position measuring device. The proposed method, in addition to the Spectral Kurtosis based band selection, will be used to enhance the bearing envelope analysis.
5. Propose a new method for classification of the bearing faults based on the fault severity and the strength of impulsiveness in vibration signals. It will be used for planning different types of tests using both temperature and vibration methods.
6. Develop and experimentally test a new technique to stimulate the bearing temperature transient condition. The technique is supported by the results of finite element modeling and is used for bearing temperature condition monitoring when the bearing is already running at thermal equilibrium condition.
8
Horch, Alexander. "Condition Monitoring of Control Loops." Doctoral thesis, Stockholm : Tekniska högsk, 2000. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3050.
Full text
9
Sandberg, Erik. "Condition monitoring in steel industry." Thesis, University of Manchester, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.489505.
Full textAbstract:
This thesis presents investigations about the applicability of different multivariate statistical methods (OLS, PCA, PCR, PLS) for condition monitoring of steel industry processes (electric arc furnaces and blast furnaces). The work has been focused on three main areas; condition monitoring of blast furnaces (BF), charge material mix optimisation for electric arc furnaces (EAF) and batch-monitoring of EAFs.
10
Macintyre, John. "Condition monitoring and neural networks." Thesis, University of Sunderland, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.297129.
Full text
11
Brown, S. A. "Condition monitoring using stable isotopes." Thesis, Imperial College London, 1987. http://hdl.handle.net/10044/1/38246.
Full text
12
Huang, Zheng. "Integrated railway remote condition monitoring." Thesis, University of Birmingham, 2017. http://etheses.bham.ac.uk//id/eprint/7904/.
Full textAbstract:
The profound value of wayside monitoring in helping safeguard the RAMS of railway operations is undeniable. However, despite significant investments by the rail industry, the efficiency and reliability of wayside monitoring have not reached the desired level. Structural deterioration of the rail infrastructure and rolling stock faults still remain a significant problem which needs to be addressed as traffic density, train speeds and axle loads increase in rail networks around the world. The main objectives of this study were to develop and evaluate an advanced wayside monitoring system based on acoustic emission and vibration analysis that can detect various types of axle bearing defects in rolling stock and structural deterioration in cast manganese crossings. The potential architecture for different levels of system correlation has been proposed which can be further integrated with customised monitoring system. A novel signal processing technique based on spectral coherence has been developed. This particular method is based on the identification of suitable templates containing features of interest. It also features in identifying the severity of the defect. In addition, a suitable approach for data fusion from various sensors has been investigated. Successful tests have been carried out under simulated conditions and in the UK network.
13
Zhao, Xiaoyu. "Condition Monitoring of Hydraulic Systems." Thesis, KTH, Maskinkonstruktion (Inst.), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-183005.
Full textAbstract:
The purpose of this project is to investigate and propose a system for condition monitoring and analysis of the hydraulic system of a forestry machine based on available on-board oil quality sensor data. The sample machine used was Scorpion King from Ponsse. This machine is equipped with an Icount PDR particle sensor from Parker. A two weeks long field test was conducted by Skogforsk. The data measured by the particle counter was collected, and breaks longer than five minutes were recorded as well as the reason for each break. The main results from the thesis are the relations between three factors: number of particles in the oil, machine operations, and machine breaks. The thesis also aims at proposing how the operator could use the Icount PDR data to manage the maintenance of the machine.Syftet för detta projekt är att utreda och föreslå ett system för tillståndsövervakning och analys av en skogsmaskins hydraulsystem baserat på tillgängliga data från ombordmonterade partikelsensorer. Den maskin som studerats är Ponsse Scorpion King, som är utrustad med partikelsensorn Icount PDR från Parker. Data samlades in under en två veckor lång fälttest. Maskinoperationerna och mätdata från partikelräknaren samlades in, och orsakerna till avbrott längre än fem minuter loggades manuellt. Resultatet av detta examensarbete presenterar relationerna mellan tre faktorer: partikelantal hos hydrauloljan, maskinens verksamhet och de avbrott som inträffade. Denna avhandling avser också föreslå hur informationen från Icount PDR skall presenteras för operatören och hur förebyggande maskinunderhåll skall kunna planeras.
14
Zandberg, Hermanus Andries Jakobus. "Wireless transformer condition monitoring system." Thesis, Cape Peninsula University of Technology, 2013. http://hdl.handle.net/20.500.11838/1186.
Full textAbstract:
The Department of Electrical Engineering in fulfilment of the
requirements for the Magister Technologiae in Electrical
Engineering at the
Cape Peninsula University of Technology
November 2013Pole mounted transformers (PMT) in rural areas present an opportunity for local utilities to do current monitoring on these systems. These transformers are exposed to abnormal amounts of stress due to the vast power demand in these areas. The aim of this study is to develop a more cost-effective condition monitoring system. Transformer current monitoring can be a dangerous practice if not done by suitably trained utility electricians. Hence this study is partly aimed at the elimination of hazardous working environments associated with manual electrical measurements. An investigation to determine a safe and cost-effective way to obtain the electrical measurements required from PMTs is undertaken. Although current measurements can be done with a current clamp-on meter, these measurements still take place at the phases of the transformer and are unsafe. The possibility of implementing wireless data gathering on current clamp-on meters is therefore investigated. This is made possible by a wireless sensor node (WSN) which gathers information and transmits it wirelessly to a WSN base station. This wireless solution is battery powered, necessitating battery replacements, therefore leading to the investigation of magnetic fields, magnetic materials and magnetic induction. A current clamp able to generate a high voltage (HV) output with minimal magnetic field strength is developed. The magnetic fields produced by the transformer’s phase cables are used to generate an alternating voltage. With the help of a microcontroller and an energy harvesting circuit, this voltage is converted and used to charge supercapacitors. The magnetic fields are also used to determine the current flow in the transformer phase cables when the device is not in energy harvesting mode. The device will then undergo comprehensive laboratory testing to determine its accuracy and durability, and is then used to do ‘real life’ current measurements, the results of which are compared against an off-the-shelf current monitoring device.
15
Mozok, E. M. "Monitoring condition of thermal object." Thesis, Сумський державний університет, 2014. http://essuir.sumdu.edu.ua/handle/123456789/34870.
Full textAbstract:
Thermal power plants are producing more than a third of consumed electricity and become main enterprise which generate electricity, both in Ukraine and other countries. To achieve optimal control of the combustion process it is necessary to provide individual adjustment of the following parameters: distribution of the combustion zone according to the project plan; control of air distribution and air/fuel ratio in combustion zone.
When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/34870
16
Liang, Ming-Te. "Condition monitoring of piled foundations." Thesis, University of Aberdeen, 1986. http://digitool.abdn.ac.uk/R?func=search-advanced-go&find_code1=WSN&request1=AAIU005228.
Full textAbstract:
In this thesis a brief history of dynamic pile analysis methods and the associated background theory are presented. In addition an unpublished rigorous mathematic proof of the Case method and new general theoretical model for dynamic pile analysis, developed as the Aberdeen method, are given. The dynamic and static response of model concrete piles in dry sand to impact and static loads have also been investigated experimentally and the results are reported in this thesis. Pile response has been found to be crucially dependent on the damping in the system. The method of modal analysis has been found to be the best approach to determine the damping factor of both the onshore and the offshore piles and is discussed in detail. A theoretical relationship between the initial and the reflected stress waves and the dynamic point resistance is used to calculate the force-penetration relationship and nonlinear parameters for the special case of pile points on dry sand. The shock relation, equations of motion and compatibility of the dynamic measurement at pile top are given by the Aberdeen method. This method gives a mathematical description of the behaviour of impact response which has not been achieved in either the Case or the TNO method. At present, the Case and TNO methods are used to investigate the integrity of piled foundations by means of the impact concept. This thesis introduces a third method, the J-integral method in the study of piled foundation. In addition, the thesis also gives a theoretical explanation to the TNO method which have not been provided elsewhere.
17
Moore, David John. "Condition monitoring of diesel engines." Thesis, University of Manchester, 2013. https://www.research.manchester.ac.uk/portal/en/theses/condition-monitoring-of-diesel-engines(629ec6ef-d54b-449a-90c1-32ac0eee8bcf).html.
Full textAbstract:
Reliability of emergency Diesel generator systems, or indeed any Diesel engines in a wide range of fields is critical. Traditional maintenance procedures for these engines follow time based or statistical based methods. Due to the wide variety of uses of Diesel engines it is not possible for these forms of maintenance to be as effective as condition based monitoring. Condition based monitoring holds many advantages over traditional maintenance methods. It allows for the earlier detection and diagnosis of a fault and allows for planned maintenance work avoiding costly and unexpected downtime. It also reduces the overall maintenance costs as parts need only be replaced when they are worn or faulty, not based on a time schedule. The ability to unobtrusively monitor the engines also has many advantages in- cluding reduced sensor cost and negating the need to tamper permanently with the engine. Acoustic monitoring has been identified as the most prominent and effective way in which to achieve this goal. As such, extensive experimentation was carried out on both large and small Diesel engines over a wide range of speeds, loads and faults and the data was then analysed. The data was first investigated statistically and then processed using Independent Component Analysis after the statistical re- sults were found to be poor. A program was written for the automatic comparison of the collected data and the results presented in this thesis show that ICA and acoustic emissions have the ability to aid in engine fault detection and diagnosis. The results have shown to be reliable, consistent and able to distinguish when the engine is healthy or faulty.
18
Stephen, Joseph Temitope. "Condition monitoring of bolted joints." Thesis, University of Sheffield, 2015. http://etheses.whiterose.ac.uk/10425/.
Full textAbstract:
Rail joints have been in existence for a long time of which their design has remained primarily unchanged over this period. Rail joints are a typical example of bolted joints. Like other bolted joints, their integrity depends on the quantitative representation of the contact pressure distribution at the interface during design. In service, rail joints are subjected to complex operating stresses, and they demand high maintenance cost because they are safety critical and have the lowest service life of the components on the rail tracks. In this study, non-intrusive ultrasonic techniques have been employed to investigate the parameter relevant to their design, operation and condition monitoring. The effect of variation in plate thickness and diameter of the bearing surface of the bolt head on the contact pressure distribution at bolted interfaces under varying axial loads was investigated. While it was observed that the contact pressure at the interface increases as the applied load increases, the distance from the edge of the bolt hole at which the distribution becomes stable is independent of the applied load on the bolted joint. However, the contact pressure distribution was observed to vary with the plate thickness. Although the variation in the peak value of average contact pressure distribution in bolted joints does not depend on the plate thickness, the distance from the edge of bolt hole at which the value of the distribution becomes stable increases as the plate thickness is increased. It was revealed that the peak value of the contact pressure distribution decreases as bearing diameter of the bolt head increases, and that the distance at which the normalised average contact pressure distributions become fairly constant also increases as the bearing diameter of the bolt head increases. In the majority of the cases, the distance falls between 3 and 4 of the bolt radius from the edge of the bolt hole. It was also observed that the edge of the bolt head has a pronounced effect on the position of the peak value of the contact pressure distribution at the interface. Furthermore, a model based on a Weibull distribution has been proposed to fit the experimental data, and a good correlation was observed. Non-intrusive experimental techniques were simultaneously used to investigate the relaxation of contact pressure and loosening of bolted joints subjected to cyclic shear loading. Three critical areas: the contact interface of bolted component, the bolt length and the rotation of the bolt head, were monitored during loosening of the joints. The results show that loosening of bolted joints can be grouped into four stages. The early stage of the loosening of bolted joints is characterised by cyclic strain ratcheting- loosening of the bolted joint during vibration without rotation of the bolt head. The higher the rate of relaxation at this early stage the lower is the resistance of the bolted joint to vibration induced loosening of bolted joints. Furthermore, the rate of loosening at the bolted joint interface is not the same but increases away from the bolt hole. While the rate of loosening of bolted joints largely depends on the amplitude and the number of cycles of the applied dynamic shear load, it is independent of the frequency of the applied load. In addition, increasing the bolt torque was found to increase the loosening resistance of the bolted joint. When joints are subjected to a constant shear load in addition to the dynamic shear load, the loosening rate increase, and this rate depend on the magnitude of this constant shear load. A normal incidence pulse-echo ultrasonic technique was used to monitor de-bonding at the interface of adhesive bonded insulated lap joints and insulated block joints, subjected to a shear load induced failure. The results revealed that the insulated joint exhibited elastic behaviour before a sudden failure (rupture) of the joint. The de-bonding of adhesive/insulating layer on the web sides of IBJs was found to occur earlier than at any other parts of the joint when the applied load was only a fraction of the peak of the shear load. However, the de-bonding at the top and foot of the rail occurred almost at the peak of the shear load. This same technique was used to monitor the degradation, and eventual failure of IBJs subjected to cyclic shear loading. The results showed that the degradation of the adhesive insulating layer has commenced, and was in progress when the joint was virtually intact and displayed elastic behaviours. The failure at the adhesive interface is indicated by a sudden change in the value of the measured reflection coefficient. After this, the failure of the joint is preceded by plastic behaviour of the joint. In addition, the change in the length of the bolts can also be monitored directly, as a complete failure at the interface of the bolted joints can be highlighted before the failure occurred. The results of this study have shown that, with further development, ultrasound can be used to monitor the condition of IBJs while in service.
19
Cablea, Georgia. "„Three-phase signals analysis for condition monitoring of electromechanical systems : application to wind turbine condition monitoring”." Thesis, Université Grenoble Alpes (ComUE), 2016. http://www.theses.fr/2016GREAT073/document.
Full textAbstract:
Cette thèse propose une méthode d'analyse des signaux triphasés pour la surveillance d'état des systèmes électromécaniques. La méthode proposée repose sur l'utilisation de la transformée en composantes symétriques instantanées et d'outils simples de traitement du signal pour détecter les défauts électriques et mécaniques dans de tels systèmes. Les avantages de cette approche triphasée par rapport à une approche monophasée pour la surveillance d'état sont étudiés en détail. Tout d'abord, pour les défauts électriques, l'utilisation de la transformée triphasée permet de séparer les composantes symétriques et asymétriques, et facilite ainsi la détection d'un déséquilibre électrique. Ensuite, pour les défauts mécaniques, l'approche par transformée en composantes symétriques permet de travailler dans des espaces avec un meilleur rapport signal à bruit. En effet, en appliquant le même traitement à la fois en monophasé et en triphasé sur les composantes symétriques, on observe que certains défauts mécaniques ne sont détectables qu’en utilisant la séquence positive des composantes symétriques. La méthodologie complète et les algorithmes pour calculer les indicateurs de défaut pour les défauts électriques et mécaniques sont donnés et les résultats sont validés sur signaux synthétiques et expérimentaux. En termes d'application, l'accent est mis sur la surveillance d'état des composants de turbines éoliennes. Toutefois, le procédé proposé peut être appliqué à des systèmes électromécaniques en général et peut facilement être étendu à des systèmes polyphasésThis thesis proposes a three-phase electrical signals analysis method for condition monitoring of electromechanical systems. The proposed method relies on the use of instantaneous symmetrical components (ISCs) transform and simple signal processing tools to detect both electrical and mechanical faults in such systems. The advantages of using this three-phase approach for condition monitoring instead of single-phase ones are thoroughly detailed. Firstly, for electrical faults the use of the three-phase transform separates the balanced and unbalanced components thus making electrical unbalance detection easier. Secondly, for mechanical faults the ISCs approach has better signal-to-noise ratio (SNR). Indeed, by applying the same processing to both single-phase and ISCs, some mechanical faults are only detectable using the positive-sequence ISC. The complete methodology and algorithms to compute fault indicators for both electrical and mechanical faults are given and the results are validated using synthetic and experimental signals. In terms of application, the focus was on condition monitoring of wind turbine components. However, the proposed method can be applied on electromechanical systems in general and can easily be extended to poly-phase systems
20
Ridwan, Firman. "STEP-NC enabled machine condition monitoring." Thesis, University of Auckland, 2011. http://hdl.handle.net/2292/10395.
Full textAbstract:
It is widely recognised that feed-rate optimisation is an effective way of improving and obtaining better machining performances. The rigid data format of ISO 6983 (G-code) makes feed-rate optimisation difficult because the controller normally executes the code with pre-set feed-rates. In order to select and use the best parameters to automatically deal with the "worst case scenario", this research project incorporates process monitoring and control based on the STEP-NC (STandard for Exchange of Product data for Numerical Control) data model. The STEP-NC data model provides standard data requirements for machining processes associated with CNC machining. In order for STEP-NC to support machining optimisation, a data model for optimisation has been developed, which is then incorporated with the rest of the STEP-NC data model. With an optimisation schema developed to work alongside the STEP-NC data model, optimisation can be carried out in a more timely fashion to give an optimum feed-rate for a particular duration of machining process. It then becomes possible that the desired feed-rate is attained by considering and verifying the optimised feed-rate under actual machining conditions. Any modifications to the machining parameters on the shop-floor can be recorded, evaluated, and transferred back to the planning phase for preservation of knowledge and experience. A new framework is designed to provide the functional requirements in the development of an effective STEP-NC enabled machine control monitoring system. The functional requirements include (i) an offline optimisation module, (ii) a data model in support of process optimisation, (iii) real-time process monitoring and control, and (iv) a universal CNC language. With the aim of enabling and improving machining optimisation, this research proposes new system architecture for generic feed-rate optimisation, process control and knowledge-based evaluation. The system is divided into three sub-systems: an optimisation system based on STEP-NC called optiSTEP-NC, an adaptive executor of an NC program with feed-rate optimisation called AECopt and a Knowledge-based Evaluation (KBE) system. The first and second functional requirements are incorporated in the design of the optiSTEP-NC system. The third and fourth functional requirements are included in developing the AECopt controller system. The first functional requirement can also be accommodated using the KBE system which records and evaluates the optimum parameters through real machining data. This way, machining optimisation before, during and after machining operations can be carried out. Integration of all these stages under a single platform opens an avenue for developing an intelligent machining environment. The system was tested using a CNC milling machine. It has been proved that the proposed system allows pre-machining optimisation ensuring that optimal parameters are used during the machining process; allows real-time monitoring, optimisation and control of a machine tool; and improves subsequent machining operations. A twenty-nine percent reduction in machining time was achieved in the case study conducted. Furthermore, the optimisation algorithm also helped reduce chatter. This led to a much healthier machining process. The system architecture overcomes the problems faced by the conventional G-code based optimisation.
21
Aas-Hansen, Mads. "Monitoring of hull condition of ships." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for marin teknikk, 2010. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-11665.
Full textAbstract:
In this thesis five bulk ships from Kristian Gerhard Jebsen Skipsrederi AS has been monitored over time in order to discover the increase in resistance due to fouling on the hull and propeller. Each ship has reported weather and ship data twice a month. These reports have been used to discover the resistance due to fouling by correcting all other added resistances from each measurement in the given time period. When all other resistance types are corrected for, each measurement is as if the ship travelled in calm weather. Then these results can be compared. The resistance types that are corrected for in this thesis are: Added resistance in waves Added resistance in wind Added resistance due to steering Speed loss due to shallow water When each measurement has been corrected for these resistance types, they are corrected to a reference speed and draft to be able to compare the results properly. In addition, the extent of the added resistance due to yaw angle because of lift forces from the rudder has been investigated and found to be neglectable. It has been found that the increase in resistance due to fouling is relatively linear the first two-three years. After three years the increase in resistance gets exponential.
22
Chen, Ping. "Bearing condition monitoring and fault diagnosis." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/mq64993.pdf.
Full text
23
Wisznia, Roman. "Condition Monitoring of Offshore Wind Turbines." Thesis, KTH, Kraft- och värmeteknologi, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-118455.
Full textAbstract:
The growing interest around offshore wind power, providing at the same time better wind conditions and fewer visual or environmental impacts, has lead many energy suppliers to consider the installation of offshore wind farms. However, the marine environment makes the installation and maintenance of wind turbines much more complicated, raising the capital and operation costs to an undesirable level and preventing the fast progression of this technology worldwide. Availability of offshore wind turbines varies between 65 and 90% depending on location, whereas onshore turbines range between 95 and 98% in most cases. In 2009, the ETI launched a research project aiming to improve economical efficiency of offshore wind farms by increasing their availability and decreasing their maintenance costs (partly through replacing corrective maintenance by preventive maintenance). This project named “Inflow” involves the development of a condition monitoring system, a system designed to monitor the state of different wind turbine components, and to analyze this data in order to determine the wind turbines overall condition at any given time, as well as its potential system ailments This paper describes two different approaches to perform the condition monitoring of offshore wind farms, the first one involves thresholds-based analysis, while the other involves pattern recognition.
24
Mahmoud, Osama Esmail. "An intelligent engine condition monitoring system." Thesis, University of Newcastle Upon Tyne, 2009. http://hdl.handle.net/10443/1665.
Full textAbstract:
The main focus of the work reported here is in the design of an intelligent condition monitoring system for diesel engines. Mechanical systems in general and diesel engines in particular can develop faults if operated for any length of time. Condition monitoring is a method by which the performance of a diesel engine can be maintained at a high level, ensuring both continuous availability and design-level efficiency. A key element in a condition monitoring program is to acquire sensor information from the engine, and use this information to assess the condition of the engine, with an emphasis on monitoring causes of engine failure or reduced efficiency. A Ford 70PS 4-stroke diesel engine has been instrumented with a range of sensors and interfaced to a PC in order to facilitate computer controlled data acquisition and data storage. Data was analyzed to evaluate the optimum use of sensors to identify faults and to develop an intelligent algorithm for the engine condition monitoring and fault detection, and in particular faults affecting the combustion process in the engine. In order to investigate the fault-symptom relationships, two synthetic faults were introduced to the engine. Fuel and inlet air shortage were selected as the faults for their direct relationship to the combustion process quality. As a subtask the manually operated hydraulic brake was adapted to allow automatic control to improve its performance. Two modes of controlling were designed for the developed automatic control of the hydraulic brake system. A robust mathematical diesel engine model has been developed which can be used to predict the engine parameters related to the combustion process in the diesel engine, was constructed from the basic relationships of the diesel engine using the minimum number of empirical equations. The system equations of a single cylinder engine were initially developed, from which the multi-cylinder diesel engine model was validated against experimental test data. The model was then tuned to improve the predicted engine parameters for better matching with the available engine type. The final four-cylinder diesel engine model was verified and the results show an accurate match with the experimental results. Neural networks and fuzzification were used to develop and validate the intelligent condition monitoring and fault diagnosis algorithm, in order to satisfy the requirements of on-line operation, i. e. reliability, easily trained, minimum hardware and software requirements. The development process used a number of different neural network architecture and training techniques. To increase the number of the parameters used for the engine condition evaluation, the Multi-Net technique was used to satisfy accurate and fast decision making. Two neural networks are designed to operate in parallel to accommodate the different sampling rate of the key parameters without interference and with reduced data processing time. The two neural networks were trained and validated using part of the measured data set that represents the engine operating range. Another set of data, not utilized within the training stage, has been applied for validation. The results of validation process indicate the successful prediction of the faults using the key measured parameters, as well as a fast data processing algorithm. One of the main outcomes of this study is the development of a new technique to measure cylinder pressure and fuel pressure through the measurement of the strain in the injector body. The main advantage of this technique is that, it does not require any intrusive modification to the engine which might affect the engine actual performance. The developed sensor was tested and used to measure the cylinder and fuel pressure to verify the fuel fault effect on the combustion process quality. Due to high sampling rate required, the developed condition monitoring and fault diagnosis algorithm does not utilize this signal to reduce the required computational resources for practical applications.
25
Jiang, Jian. "Acoustic Condition Monitoring In Industrial Environments." Thesis, University of Manchester, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.504737.
Full textAbstract:
Date of submission DDjr4f.1/VVVV· Condition monitoring (CM) based Maintenance is an effective way to ensure a machine's reliability during its useful life,' hence reducing the occurrence of unexpected accidents and bringing economic benefits. Awareness of condition monitoring has grown in recent years and so more attentions have been paid to the subject. Although traditional condition monitoring systems (using vibration, speed measurement, temperature monitoring, .etc) are still very effective in particular fields, they have some deficiencies, such as difficulty in implementation and the inability to provide remote and contactless measurement, which limit the condition monitoring systems' wide application. Acoustic measurements do not have these deficiencies as well as providing information richness. One major drawback limiting the use of acoustic measurements in industry, howev~r,. is that the signal can be seriously influenced by environmental factor§,~.:SUeli.l~s,lreverberation and background noise. Fortunately, developments in h'ardware)t~'chnology and signal processing have shown a potential for reducing these influences by using array technologies. However, large scale acoustic arrays are too expensive to be applied in many situations, and so small scale arrays offer a cost-effective alternative. This thesis concentrates on developing a new condition monitoring system using a small scale acoustic array. This system first localises the acoustic source, which is the object of condition monitoring, in the industrial environment. Then, based upon this localisation, the system uses beam-forming to enhance the signal propagating from the source direction and attenuate signals from other directions. Since reverberation signals often propagate from directions other than the source, this procedure has the potential to reduce the effects of reverberation. Other pre-processing methods, such as band-pass filters and temporal averaging are then used to further enhance the signal to noise ratio. Finally, the processed signals are used to monitor the condition of desired machine and diagnose the potential faults. The thesis is divided into 4 parts. In part 1, the motivation of this project and the reasons why acoustic method and small scale array technologies are used are introduced. In part 2, the technologies relating to ,t~e establishment of this new condition monitoring system are investig,!ted;, .rhe;: cpp.~ents include 1) investigation of the array's configuration, 2) time delay estimation algorithms used in industrial environment and 3) other issues relating to acoustic condition monitoring using the new system. In part 3, the new system is established and used to monitor the condition and diagnose the potential faults of a 4-cylinder diesel engine in industrial environments. The experimental results show that this system is effective in this practical application and has potential to be developed further. In part 4, a summary of this thesis is given.
26
Crabtree, Christopher James. "Condition monitoring techniques for wind turbines." Thesis, Durham University, 2011. http://etheses.dur.ac.uk/652/.
Full textAbstract:
This thesis focuses on practical condition monitoring of wind turbines. With offshore wind playing an increasing part in UK electricity generation, prompt fault detection leading to preventative maintenance is gaining in importance. This work describes the development of a condition monitoring test rig and the innovation and application of signal processing techniques for the detection of faults in non-stationary signals. Work is supported throughout by information from wind turbine operators and their experiences of variable speed, variable load wind turbines in the field. Experimental work is carried out on a condition monitoring test rig comprising a wound rotor induction generator, gearbox and DC driving motor. The test rig operates at variable speed and allows the implementation of a number of fault-like conditions including rotor electrical asymmetry, shaft mass unbalance and gear tooth failure. Test rig instrumentation was significantly developed during this research and both electrical and mechanical condition signals are monitored. A signal processing algorithm was developed based on experience with analysis techniques and their relationship with the characteristics of a wind turbine. The algorithm is based on Fourier analysis and allows the analysis of fault-related speed-dependent frequencies within non-stationary signals such as those encountered on a wind turbine. The detection of different faults is discussed and conclusions drawn on the applicability of frequency tracking algorithms. The newly developed algorithm is compared with a published method to establish its advantages and limitations.
27
Wilkinson, Michael Richard. "Condition Monitoring for Offshore Wind Turbines." Thesis, University of Newcastle Upon Tyne, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.492117.
Full text
28
Price, E. D. "High frequency techniques for condition monitoring." Thesis, Swansea University, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.638574.
Full textAbstract:
Acoustic emission and vibration data representative of wear modes experienced in naval air and surface combatants has been collected and analysed. Results obtained from data generated by four-ball testing indicate the suitability of both high frequency vibration monitoring and acoustic emission techniques for detection of scuffing wear and pitting fatigue wear. By monitoring changes in the frequency content of acoustic emission waveforms it is also possible to detect early development of subsurface cracking caused by rolling contact fatigue.
29
Reece, Steven Andrew. "Neural networks in business condition monitoring." Thesis, Southampton Solent University, 1997. http://ssudl.solent.ac.uk/1265/.
Full textAbstract:
The research uses neural nets as a tool in the investigation of busienss failure prediction and business performance monitoring. The novelty lies in the introduction of models including qualitative factors as well as financial ratios. In addition, an analysis of data gathered from a new survey is offered. To achieve its objectives the research begins by exploring the AI options and then reviews current neural net technology with a view to identifying appropriate technology for the implementation of a classifier for the two areas of failure prediction and performance monitoring. After consideration of the strengths and weaknesses of the options, a multi-layer perceptron, back propagation net is adopted as being unsuitable for this application. In order to verify the validity of the bespoke neural net software it was necessary to employ a two stage strategy. The first step was to confirm that the net, as implemented, retained the expected property of being able to solve problems that were not linearly separable. This was achieved by demonstrating its ability to solve the straightforward XOR problem. To be confident of the net performance it was deemed necessary to replicate the experiments of previous research which used only purely financial inputs to the net. The results confirmed the validity of the new network implementation. Using the intital results as a control, experiments were undertaken to ascertain the effect of reducing the training sample size and to identify minimum sample sizes commensurate with maintaining the effectiveness. The work then further contributes to this research by using traditional stastical methods to provide an empirically derived equation for calculating the minimum number of training patterns required for corporate failure prediction in the context of the experimental sets of variables. The resulting failure prediction model was then used to test for symptoms of bankruptcy in firms currently trading. The thesis then leads on to describing a technique developed in this study for pre-processing qualitative questionnaires, prior to input into a neural model as well as providing a method for predicting values not supplied in incomplete survey responses. A contribution is also made to the area of company performance analysis by using neural techniques and discriminant analysis to show that relationships do exist between certain company variables and business performance, as well as highlighting which of these variables are the most important if an appropriate corporate condition monitoring strategy is to be developed. Lastly, the corporate performance neural network model is enhanced by facilitating the categorisation of a firm into one of several performance bands.
30
Aitchison, David Robert. "Laser based cutting tool condition monitoring." Thesis, University of Hull, 1995. http://hydra.hull.ac.uk/resources/hull:3693.
Full text
31
Amini, Arash. "Online condition monitoring of railway wheelsets." Thesis, University of Birmingham, 2016. http://etheses.bham.ac.uk//id/eprint/6957/.
Full textAbstract:
The rail industry has focused on the improvement of maintenance through the effective use of online condition monitoring of rolling stock and rail infrastructure in order to reduce the occurrence of unexpected catastrophic failures and disruption that arises from them to an absolute minimum. The basic components comprising a railway wheelset are the wheels, axle and axle bearings. Detection of wheelset faults in a timely manner increases efficiency as it helps minimise maintenance costs and increase availability. The main aim of this project has been the development of a novel integrated online acoustic emission (AE) and vibration testing technique for the detection of wheel and axle bearing defects as early as possible and well before they result in catastrophic failure and subsequently derailment. The approach employed within this research study has been based on the combined use of accelerometers and high-frequency acoustic emission sensors mounted on the rail or axle box using magnetic hold-downs. Within the framework of this project several experiments have been carried out under laboratory conditions, as well as in the field at the Long Marston Test Track and in Cropredy on the Chiltern Railway line to London.
32
Martín, del Campo Barraza Sergio. "Towards autonomous condition monitoring sensor systems." Licentiate thesis, Luleå tekniska universitet, EISLAB, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-25706.
Full textAbstract:
Rolling element bearings are used to carry load and reduce friction between moving parts in rotating machines, which play a central role in society and industry, for example in the transportation and energy sectors. It is essential to monitor and maintain the condition of bearings such that machines can operate efficiently and any failures resulting in unplanned stoppages are avoided. Therefore, bearings with embedded sensing capabilities are becoming increasingly common, which makes it possible to consider bearings to be sensor systems that can monitor the condition of rotating machines. However, the task of automatically analyzing the signals is challenging because machines are different and evolve over time; moreover, the complexity of the signals, machines and possible failure modes is high and costly to accurately predict and model. Therefore, the use of unsupervised machine learning methods for the automated analysis of such signals and the detection of abnormal operational conditions is an interesting subject worth further exploration.Previous work has strongly depended on static features defined by human experts and thresholds that characterize abnormal operational conditions. Furthermore, machine learning methods typically depend on such static features to classify the faults and various operational conditions of the machine. This approach is challenging when reusing a method for different applications and environments, wherein similar features and thresholds can have different meanings. This problem is typically solved by reconfiguring or redesigning the condition monitoring system, thereby constraining the applicability and efficiency of the method.In this licentiate thesis, I investigate unsupervised methods for feature learning and anomaly detection. In particular, I focus on vibration signals, which contain information about both the bearing condition and the condition of the machine.The considered model represents the signal as a linear superposition of noise and atomic waveforms of arbitrary shape, amplitude and position. The atomic waveforms are adapted to each signal and machine using an unsupervised probabilistic optimization method and are considered features of the machine and physical processes exciting the signal. This model can automatically adapt the features to different environmental and operational conditions, thereby forming the basis for the development of a condition monitoring system that requires a minimum of manual configuration. Additionally, the model produces sparse codes that decrease the sensor data rate and, in principle, simplify the task of analyzing and communicating complex sensor information in resource-constrained embedded sensor systems.The thesis outlines an implementation of a sparse representation and dictionary learning method that is applied to vibration signals. I describe how signal analysis is performed using typical static pre-defined features and contrast this analysis with an analysis based on features that are automatically derived from the signal. In particular, the analysis focuses on the evolution of the vibration signal and the features when a fault develops within the ball bearing of a rotating machine. The evolution rate of learned features is defined and proposed as an interesting quantity for an autonomous condition monitoring process, and a first step towards an FPGA implementation of the method is presented.Godkänd; 2015; 20150413 (sermar)
33
Kotta, Anwesh. "Condition Monitoring : Using Computational intelligence methods." Master's thesis, Universitätsbibliothek Chemnitz, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-187100.
Full textAbstract:
Machine tool components are widely used in many industrial applications. In accordance with their usage, a reliable health monitoring system is necessary to detect defects in these components in order monitor machinery performance and avoid malfunction. Even though several techniques have been reported for fault detection and diagnosis, it is a challenging task to implement a condition monitoring system in real world applications due to their complexity in structure and noisy operating environment. The primary objective of this thesis is to develop novel intelligent algorithms for a reliable fault diagnosis of machine tool components. Another objective is to use Micro Electro Mechanical System (MEMS) sensor and interface it with Raspberry pi hardware for the real time condition monitoring.
Primarily knowledge based approach with morphological operators and Fuzzy Inference System is proposed, the e˙ectiveness of this approach lies in the selection of structuring elements(SEs). When this is evaluated with di˙erent classes of bearing fault signals, it is able to detect the fault frequencies e˙ectively. Secondarily, An analytical approach with multi class support machine is proposed, this method has uniqueness of learning on its own with out any prior knowledge, the e˙ectiveness of this method lies on selected features and used kernel for converging. Results have shown that RBF (Radial Bias Function) kernel, which is commonly known as gauss kernel has good performance in identifying faults with less computation time. An idea of prototyping these methods has triggered in using Micro Electro Mechanical System (MEMS) sensor for data acquisition and real time Condition Monitoring. LIS3DH accelerometer sensor is used for the data acquisition of spindle for capturing high frequency fault signals. The measured data is analyzed and compared with the industrial sensor k-shear accelerometer type 8792A.
34
Karlsson, Martin, and Fredrik Hörnqvist. "Robot Condition Monitoring and Production Simulation." Thesis, Luleå tekniska universitet, Institutionen för teknikvetenskap och matematik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-69024.
Full textAbstract:
The automated industry is in a growing phase and the human tasks is increasingly replaced by robots and other automation solutions. The increasing industry entails that the automations must be reliable and condition monitoring plays an important role in achieving that ambition. By utilizing condition monitoring of a machine it is possible to detect a wear before it turns into a critical damage that could result in complete failure. A useful tool when monitoring the condition of a machine is by sampling and analyzing vibrations. Vibrations are generated by the moving parts of the machinery and high amplitude vibrations can often be seen as an indication of the developed faults. The frequency of these vibrations can be calculated and then detected in the sampled data. Today there is no condition monitoring system that monitor industrial robots by analyzing vibrations. The problem with analyzing robots, is that they operate with a varying speed. Since the running conditions are changing rapidly all the time, this means that the vibration frequencies also changes constantly. This is due to the fact that the vibration frequencies are dependent and affected of the operation speed. This research is a sequel and continuation of a research from previous year. The purpose of the research is to investigate the possibility to monitor the condition of a gearbox in a industrial robot, by utilizing vibration analysis. The robot that has been tested under tuff conditions in order to reach a failure, is an ABB IRB 6600. To sample data in a stationary way even tough the speed is changing during the sample time, the method order tracking has been utilized. This makes it possible to sample data with numbers of measurement per rotation instead of sampling according to time. This is processed by SKF:s condition monitoring system multilog IMx and the signal is then presented as a time waveform in the software @ptitude Observer. In Observer, it is also possible to show the signal in a spectrum by using Fast Fourier Transform. By utilizing MATLAB, the research has also resulted in a new analyzing method. This method is called Spectral Auto-Correlation. The methodology of this practice is to correlated the time waveform with itself in order to see which frequencies that are reappearing. The correlated result is then calculated with a Fast Fourier Transform to illustrate the signal in a spectrum for further analysis. During the analysis of the parts in the gearbox, critical defects were found on both the cycloidal disks. The fault frequency for the defects were calculated and analyzed from the data. This resulted in trends where the amplitude from the fault frequency had more than doubled over the time the robot has been operating in the project. This report also include a production simulation where a robot cell from SKF is simulated. The robot cell is simulated with and without a condition monitoring system. A comparison was then made to see what advantages there were with utilizing a condition monitoring system. The result of the simulation was an increased productivity with two to three percent.
35
Da, Silva domingues Elizabeth. "Improved condition monitoring of composite insulators." Thesis, University of Manchester, 2012. https://www.research.manchester.ac.uk/portal/en/theses/improved-condition-monitoring-of-composite-insulators(d42e15fb-d9c2-4e45-94b9-3321e9d9b9f0).html.
Full textAbstract:
Although the cost of investment in power lines insulators is 3-5% of the total cost of the installation, the impact of their performance on reliability, failure costs, maintenance routines, etc in power systems is tens of times higher. Composite insulators were introduced 50 years ago and have been used around the world with consistently good experience. Low weight, easy handling, good performance under high pollution, low maintenance costs, and resistance to vandalism are some of their advantages. Nevertheless, acid rain, salty dust deposition, corona discharges, ozone, UV radiation, and humidity among other factors, deteriorate the quality of the polymeric housing reducing their hydrophobicity. The synergistic action of ageing factors is extremely complex and the whole degradation process may change when any one variable is slightly modified. Many studies have been carried out to increase understanding of the physicochemical processes which control the electrical and mechanical stability of polymers during in-service ageing with the objective of predicting remaining life-times. Vital areas of knowledge about polymer insulators are still incomplete and lacking; three of them are: (1) early stages of degradation in service under different environmental conditions, (2) monitoring and diagnosis techniques suitable for distribution installations and (3) steps to establish an insulators management plan based on condition and risk of failure. In this research these three topics are covered. A full review of literature about management of electrical distribution assets is included, followed by a specific plan developed for monitoring, diagnosis and ranking of insulators mainly supported by visual inspections. Diagnosis of medium voltages EPDM insulators recovered from service aged under different conditions is done using both traditional techniques and, uniquely, dielectric impedance. The relationship between surface roughness and static contact angle is also used to characterize insulators' surfaces. Early stages of degradation are studied focusing the experimental work to evaluate the electrohydrodynamic processes which occur on new samples under different conditions, giving special attention to leakage current pulse analysis, electric field enhancement, and resistance/capacitive behaviour including phase of leakage current. Results from each specific topic offer additional understanding of polymer insulators degradation providing insight to monitoring, diagnosis and management. Additionally, results open new topics in which new investigations are proposed.
36
Dandino, Charles M. "Condition Monitoring Sensor for Reinforced Elastomeric Materials." University of Cincinnati / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1352485050.
Full text
37
Ciliberti, Alessio. "Condition assessment of bridges using monitoring data." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019.
Find full textAbstract:
In the last years, significant interest has been vested in the possibility of using Structural health monitoring (SHM) as a standardized tool in bridge engineering. Structural Health Monitoring is an emerging field in engineering that gathers together several techniques such as structural dynamics, materials, signal processing, or microelectronics. Sensors, data, and simulation tools come together under the umbrella of SHM to offer - at every moment during the life of a structure - a diagnosis of its health and prognosis of its remaining life.
This thesis has been developed within the group of Structural dynamics and monitoring at ETH Zurich, under the supervision of Prof.Dr. Eleni Chatzi. The aim of this thesis has been to try to assess the condition of a bridge, used as case study, in order to detect changes in modal parameters and correlate them with possible types of damage, especially the ones caused by environmental (temperature) and operational (traffic) variability of modal parameters. Furthermore, a performance indicator of the health of a structure, such as fatigue, has been studied in this work in order to relate possible damage accumulation to the environmental and operational condition. For the purposes of these studies, a major bridge infrastructure in Switzerland has been analysed. Additional knowledge and information were essential though, before the intended calculations could be performed.
This study contributes to the development of an analysis process for SHM-based condition assessment for an existing structure, thereby defining further methodologies and strategies for maintenance and repair of bridges. In addition, it provides relevant information for design purposes about the influence of seasonal behaviour of action effects and traffic loads on the stiffness and different fatigue damage throughout a reference period for the long span bridge under investigation, pointing the way to implementing such methods for bridge infrastructure.
38
Eftekharnejad, Babak. "Condition monitoring of gearboxes using acoustic emission." Thesis, Cranfield University, 2010. http://dspace.lib.cranfield.ac.uk/handle/1826/6780.
Full textAbstract:
Acoustic emission (AE) is one of many technologies for health monitoring and diagnosis of rotating machines such as gearboxes. Although significant research has been undertaken in understanding the potential of AE in monitoring gearboxes this has been solely applied to spur gears and slow speed roller bearings. This research presents an experimental investigation that assesses the effectiveness of both AE and vibration technologies in identifying various types of defects on in a helical gearbox; the first known attempt.
Furthermore, the application of advanced signals processing techniques such as Spectral kurtosis (SK) and wavelet analysis were studied on AE and vibration signatures. It is shown that the application of advanced signal processing methods is particularly necessary for monitoring helical gears. The application of SK and wavelet analysis was found to be effective in denoising the acquired signals.
The first chapter of this thesis is an introduction to this research and briefly explains motivation and theoretical background supporting this research. The second chapter summaries the relevant literature to establish the current level of the knowledge in this field. The third chapter describes methodologies and experimental arrangement utilized for this investigation. Chapter 4 discusses helical gear diagnosis for both natural and seeded surface defect. Chapter 5 reports on an experimental investigation in which several technologies such as AE, vibration and motor current signature analysis, were applied to identify the presence of a naturally fatigued pinion shaft in an operating gearbox. Chapter 6 details an investigation which compared the applicability of AE and vibration technologies in monitoring a naturally degraded roller bearing.
It has been concluded that AE is a strong diagnostic tool for early diagnosis of bearings faults. However, the application of condition monitoring for helical gear diagnosis was fraught with some degree of complexity as compared to spur gears. This implies that condition monitoring of the gears using AET can be challenging. On the contrary, the applicability of AET for bearing diagnosis was promising and it offered an absolute advantage over the conventional vibrationdiagnosis. Furthermore, the application advanced signals processing methods such as Spectral Kurtosis and wavelet was found to be promising in denoise the recorded AE signals. It was also concluded that the use of different signal processing methods is often necessary to achieve meaningful diagnostic information from the signals.
39
Kidd, Moray William. "Automotive condition monitoring using standard vehicle architecture." Thesis, University of Manchester, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.556703.
Full text
40
Hede, Brian P. "Condition monitoring of tools in CNC turning." Thesis, Loughborough University, 2008. https://dspace.lboro.ac.uk/2134/14320.
Full textAbstract:
The metal cutting industry today is highly automated and, as a step towards Europe's ability to compete on the world market, an increased level of automation can be expected in the future. Therefore, much attention has been paid to the use of automated monitoring systems within the maintenance strategies designed to prevent breakdown. This research focuses on the condition monitoring of cutting tools in CNC turning, using airborne acoustic emission, (AAE). A structured approach for overcoming the problems associated with changing cutting parameters is presented with good results. A reverse and novel approach in estimating gradual tool wear in longitudinal roughing has been made by predicting cutting parameters directly from the acoustics emitted from the process. Using the RMS as a representation of the energy in the signal, where the spectral distributions are working as divisional operators, it has been possible to accurately extract a representation of feed rate, depth of cut and cutting speed from the signal. Using a simplified relationship to estimate tangential cutting force, a virtual force can be calculated and related to a certain amount of flank wear using non-linear regression. Furthermore, this research presents a monitoring solution where disturbances are eliminated by recognising the sound signatures where it, afterwards, is possible to evaluate the reliability of the wear decision. This is done by describing irregularities in the signal , where surface parameters used on a sound waveform, combined in a neural network, has been used to trigger outputs for several defined classes of disturbances. An investigation of the two wear types flank and crater wear, has been conducted and is has been concluded, that although crater wear has an effect on the AAE, it is difficult to recognise this. AAE has shown to an efficient tool to detect flank wear, where a direct relationship is shown between the changes in the cutting parameters, tool wear and AAE. This approach has resulted in a precise monitoring so lution, where flank wear can be estimated within an error of I0%.
41
Quinn, John. "Bayesian condition monitoring in neonatal intensive care." Thesis, University of Edinburgh, 2007. http://hdl.handle.net/1842/2144.
Full textAbstract:
The observed physiological dynamics of an infant receiving intensive care contain a great deal of information about factors which cannot be examined directly, including the state of health of the infant and the operation of the monitoring equipment. This type of data tends to contain both common, recognisable patterns (e.g. as caused by certain clinical operations or artifacts) and some which are rare and harder to interpret. The problem of identifying the presence of these patterns using prior knowledge is clinically significant, and one which is naturally described in terms of statistical machine learning. In this thesis I develop probabilistic dynamical models which are capable of making useful inferences from neonatal intensive care unit monitoring data. The Factorial Switching Kalman Filter (FSKF) in particular is adopted as a suitable framework for monitoring the condition of an infant. The main contributions are as follows: (1) the application of the FSKF for inferring common factors in physiological monitoring data, which includes finding parameterisations of linear dynamical models to represent common physiological and artifactual conditions, and adapting parameter estimation and inference techniques for the purpose; (2) the formulation of a model for novel physiological dynamics, used to infer the times in which something is happening which is not described by any of the known patterns. EM updates are derived for the latter model in order to estimate parameters. Experimental results are given which show the developed methods to be effective on genuine monitoring data.
42
Lavery, Grant. "A prototype transformer insulation condition monitoring system." Thesis, University of Canterbury. Electrical and Electronic Engineering, 1999. http://hdl.handle.net/10092/6037.
Full textAbstract:
A prototype data acquisition and processing system is developed for evaluating the insulation condition of a power transformer winding in real-time. The Transformer Insulation Condition Monitoring System (TICMS) evaluates the insulation condition by calculating the winding transadmittance function. The winding transadmittance function is used to fingerprint the insulation system and provides a means of monitoring its condition. The use of a transfer function for evaluating the insulation condition of a power transformer winding was proposed by Malewski and Poulin in 1988 [6, Chapter 1]. The work described in this thesis extends their work in a number of important areas and makes the following contributions to the state-of-the-art. Firstly, the TICMS is able to calculate the transadmittance function to 3MHz, which is sufficient to detect breakdown between individual turns in an Extra High Voltage (EHV) transformer. This is a key distinguishing feature of this work and is important as faults between individual turns can quickly snowball into a catastrophic failure. Previous attempts have been successful at determining the transadmittance function to around 1.5MHz, which only allows breakdown between discs to be detected in an EHV transformer. Second, the TICMS is able to determine the transadmittance function on-line and in real-time for a fully energised transformer. This is another key distinguishing feature of this work as it allows action to be taken to remove a faulty transformer from service prior to catastrophic failure. Previous attempts have calculated the transadmittance function in an offline situation over a period of minutes using pre-recorded data.
Recent advances in analog-to-digital converter (ADC) technology and the availability of high speed Digital Signal Processors (DSPs) have made it possible to extend the work of Malewski and Poulin as described above. This thesis describes the key design features of the TICMS which provide it with the ability to determine the transadmittance function over a 3MHz bandwidth in real-time. These features include the application of an excitation with tailored spectral characteristics, a novel transducer arrangement that allows the effective dynamic range of the digitizer to be extended and at the same time online measurements to be performed, a first-in-first-out (FIFO) memory arrangement that allows the high speed data acquisition section to easily interlace to the data processing section, and a powerful 32-bit floating point Digital Signal Processor (DSP) that enables the trans admittance function to be determined in real-time. The graphical user interlace to the laboratory prototype is also
presented.
Also described are the signal processing techniques, both applied and developed, that are used by the TICMS to determine the trans admittance function in real-time. These include the deconvolution of the voltage and current channel transducer output signals, a radix-2 decimation-in-time (DIT) fast Fourier transform (FFT) algorithm that transforms the voltage and current channel inputs into the frequency domain simultaneously, the calculation of the transadmittance function magnitude and phase from the recorded transients, and a zooming algorithm that is used to accurately determine pole height.
The transadmittance function of a 7.5kVA 11kV/230V distribution transformer is determined and compared with that obtained by performing a time consuming sweep frequency test. Artificial faults are inserted into a 2nd 7.5kVA 11kV/230V distribution transformer to establish relationships between the location and size of a fault and the corresponding changes in the transadmittance function. Sets of tests are conducted to evaluate the effect of fault size, fault location, the introduction of simulated partial discharges, and single turn faults. The ability of the system to detect single turn faults is a key feature as this allows faults to be detected before they can snowball into catastrophic failures.
The effect of temperature on the location and height of poles in the transadmittance function of a 7.5kVA 11kV/220V distribution transformer is established through the use of the TICMS. On-line testing of an energised transformer is performed to evaluate the effect of supply voltage magnitude, load current magnitude, and the point in the 50Hz AC cycle when the insulation test is initiated. This information allows the system to compare successive transadmittance functions and generate an alarm signal if insulation condition degradation is found to have taken place. This information will allow the system to eventually become a 'black box' that permanently sits beside a transformer continuously evaluating insulation condition.
43
Lacey, S. J. "Condition monitoring of the centreless grinding process." Thesis, Nottingham Trent University, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.355322.
Full text
44
Billington, Andrew John. "A generalised control and condition monitoring facility." Thesis, University of Sunderland, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.386056.
Full text
45
Tyler, Tristan. "Ground condition monitoring using friction generated acoustics." Thesis, Nottingham Trent University, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.429238.
Full text
46
Limchimchol, Thitikorn. "Web-based intelligent grinding condition monitoring system." Thesis, University of Nottingham, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.442268.
Full text
47
Wang, Ping. "Online condition monitoring of HV cable circuits." Thesis, University of Southampton, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.419194.
Full text
48
Hajiabady, Siavash. "Integrated condition monitoring of industrial wind turbines." Thesis, University of Birmingham, 2018. http://etheses.bham.ac.uk//id/eprint/8121/.
Full textAbstract:
The continuous growth in wind turbine power ratings and numbers has led to increased demands in inspection and maintenance due to the more significant financial and operational consequences of unexpected wind turbine failure. The fact that wind farms are commonly located at remote sites with potentially poor accessibility means it is necessary to reduce the need for corrective maintenance through evolution to preventive and prognostic maintenance activities. Prognostic repair schedules can be employed in order to optimise maintenance and contribute to the minimisation of the overall operational costs of wind farms. The present study presents the development and qualitative evaluation of remote condition monitoring methodologies for the evaluation of the wind turbine power electronics and gearboxes. The failures of power converter and gearbox components result in significant wind turbine downtime and associated repair costs. Effective condition monitoring can enable the timely diagnosis of faults in order to prevent unexpected failures and loss of electricity production, contributing towards a noteworthy increase the reliability, availability, maintainability and safety (RAMS) of wind farms. Within this study two customised test rigs have been employed to simulate various of faults and assess the capability of RCM in diagnosing this fault effectively. In addition, field measurements have been carried out and correlated to the findings of the test rig experiments. In this study, it has been possible to identify these variables qualitatively, but the quantitative investigation is still pending and will be most likely the subject of several future studies in this field. The present thesis provides a compact summary of the analysis of the key findings of the experimental work performed within the context of the OPTIMUS FP7 European collaborative project.
49
Spellman, Christopher Andrew. "Condition monitoring of high voltage surge arresters." Thesis, Cardiff University, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.410358.
Full textAbstract:
Industry requires that the quality of electricity supply be within certain tolerances, due to sensitive machinery or processes. If the supply is lost, then consumer industries will lose revenue as will the supplier and transmission company, and for this reason continuity and security of supply is paramount. The supplier and transmission company must ensure reliability even as the demand for supply grows, placing greater stress on the existing supply and transmission network. Since the transmission system cannot be easily expanded, due to government legislation, financial constraints and environmental considerations, the only option is to increase the load capacity of the existing network. Thus, protection of the network is of utmost importance. Surge arresters protect against transient faults caused by lightning and switching surges. Premature failure of arresters can compromise the system protection and early fault detection in these devices, by condition monitoring, plays a critical role in ensuring the reliability, continuity and security of the electricity supply. An extensive literature review is given that details arrester construction, characteristics, and causes of arrester failure. Laboratory experiments were used to characterise several arresters in the low-conduction and breakdown regimes where the resistive current dominated the leakage current. An existing arrester condition monitoring system utilising a field probe and current transformer, with third harmonic analysis of the leakage current was evaluated. The method of determining the resistive current, using the third harmonic analysis, was found to be imperfect, and an alternative technique was required. An improved point-on-wave technique was formulated and implemented. It accurately discriminated the resistive and capacitive components of leakage current that flowed through the arrester. As for all techniques, both applied voltage and leakage current flowing through the arrester were required for accurate arrester assessment. Characteristics of new arresters were measured, and then monitored during accelerated ageing tests, which were performed with high levels of leakage current. The point-onwave technique identified the changing characteristics and proved its ability to accurately determine arrester degradation. From the point-on-wave calibrations, an empirical expression was found that gave the resistive current peak values at varying levels of voltage and temperature. Substation implementation of any on-line monitoring technique requires noncontact voltage and current transducers to be used. A non-contact voltage measurement method was assessed, and three capacitive probes were constructed for on-site measurements. These probes gave excellent laboratory results. The voltage measurement method, with the three capacitive voltage probes, was calibrated in a substation, and the initial results were encouraging, indicating that accurate voltage measurement could be achieved.
50
Williams, Stephen Michael. "The condition monitoring of damaged steel structures." Thesis, University of Bristol, 1997. http://hdl.handle.net/1983/1e269816-fae1-4ffc-9b7b-75ba997377b6.
Full text