Dissertations / Theses: 'Automatic fault analysis'

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Nilsson, Markus. "A tool for automatic formal analysis of fault tolerance." Thesis, Linköping University, Department of Computer and Information Science, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-4435.

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The use of computer-based systems is rapidly increasing and such systems can now be found in a wide range of applications, including safety-critical applications such as cars and aircrafts. To make the development of such systems more efficient, there is a need for tools for automatic safety analysis, such as analysis of fault tolerance.

In this thesis, a tool for automatic formal analysis of fault tolerance was developed. The tool is built on top of the existing development environment for the synchronous language Esterel, and provides an output that can be visualised in the Item toolkit for fault tree analysis (FTA). The development of the tool demonstrates how fault tolerance analysis based on formal verification can be automated. The generated output from the fault tolerance analysis can be represented as a fault tree that is familiar to engineers from the traditional FTA analysis. The work also demonstrates that interesting attributes of the relationship between a critical fault combination and the input signals can be generated automatically.

Two case studies were used to test and demonstrate the functionality of the developed tool. A fault tolerance analysis was performed on a hydraulic leakage detection system, which is a real industrial system, but also on a synthetic system, which was modeled for this purpose.

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Deosthale, Eeshan Vijay. "Model-Based Fault Diagnosis of Automatic Transmissions." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1542631227815892.

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Abdul-Raheem, Khalid Fatihi. "Automatic bearing fault diagnostics using wavelet analysis and an artificial neural network." Thesis, Glasgow Caledonian University, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.493933.

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Machinery failure diagnosis is an important component of the Condition Based Maintenance (CBM) activities for most engineering systems. Rolling element bearings are the most common cause of rotating machinery failure. The existence of the amplitude modulation and noises in the faulty bearing vibration signal present challenges to effective fault detection method. The wavelet transform has been widely used in signal de-noising due to its extraordinary time-frequency representation capability. A new technique for an automated detection and diagnosis of rolling bearing conditions is presented in this thesis. The time-domain vibration signals of rolling bearings with different fault condition are pre-processed using Impulse and Laplace wavelet transforms for rolling bearing fault detection and feature extraction, respectively. The wavelet denoising and the wavelet envelope power spectrums are used for bearing fault detection and diagnosis. Furthermore, the extracted features for the wavelet transform coefficients in time and frequency domain are applied as input vectors to Artificial Neural Networks (ANN) for rolling bearing fault classification. The Impulse and Laplace Wavelets shape and the ANN classifier parameters are optimized using a genetic algorithm (GA). To reduce the computation cost, decrease the size, and enhance the reliability of the ANN, only the predominant wavelet transform scales are selected for feature extraction. The results for both real and simulated bearing vibration data show the effectiveness of the proposed technique for bearing condition identification and classification with very high success rate using minimum input features.

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Valle-Cervantes, Sergio. "Plant-wide monitoring of processes under closed-loop control." Access restricted to users with UT Austin EID Full text (PDF) from UMI/Dissertation Abstracts International, 2001. http://wwwlib.umi.com/cr/utexas/fullcit?p3035991.

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Labuschagne, P. J. "Automatic clustering with application to time dependent fault detection in chemical processes." Pretoria : [s.n.], 2009. http://upetd.up.ac.za/thesis/available/etd-07062009-142237.

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Ji, Liang. "Improving fault location through interpole analysis of circuit breaker and automatic reclose scheme operation." Thesis, University of Strathclyde, 2012. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=19009.

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This research concentrates on the development and evaluation of novel single ended impedance based fault location methods, which are easy and economical to implement in practice. The conventional single ended impedance based fault location methods normally suffer from negative effects associated with variability and inaccuracies in fault resistance, distance to fault and from the impact of variable remote end short circuit level. A novel concept of a single ended impedance based fault location method using analysis of 'interpole' states, which arise during the operation of the circuit breaker as the individual poles open sequentially, has been developed. The proposed fault location technique has been shown to have a very high theoretical accuracy by eliminating the aforementioned negative effects associated with conventional single ended impedance based methods. The thesis describes how the developed technique operates through comparing simulated voltage and currents during the interpole states with the actual measured voltage and currents, and searches for a match that may be indicative of fault location. When a match is found within a pre-specified tolerance error from analysis of the initial 'during fault' state, the ranges of corresponding possible fault locations, fault resistances and remote end short circuit levels used in the simulation are noted. The ranges of all possible values are subsequently reduced through analysis of the consecutive interpole stages as each pole of the circuit breaker opens sequentially to finally interrupt the flow of current in all three phases. The final, most accurate, fault location is obtained following on from analysis of the final state. Another single ended impedance based fault location method has been developed that extends the analysis to the operation of single/three phase auto-reclose schemes. Similarly with previous method, the second method also uses the analysis of different system states, which are arisen during the auto-reclose operation, and improves on the accuracy of the method that only analyses the single operation of the circuit breaker. The methods are demonstrated using EMTP/ATP simulation models for a variety of different cases and it is shown how high accuracy has been achieved, with improved performance when compared with conventional single ended impedance based method (Takagi method and network impedance method). Additionally, it is a potentially economic solution, as only local end data is required. The thesis concludes with an overview of ongoing and future work that has the intention of moving the work forward towards implementation within commercially available relay hardware.

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Yang, Hongyu. "Automatic Fault Diagnosis of Rolling Element Bearings Using Wavelet Based Pursuit Features." Thesis, Queensland University of Technology, 2005. https://eprints.qut.edu.au/16062/1/Hongyu_Yang_Thesis.pdf.

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Today's industry uses increasingly complex machines, some with extremely demanding performance criteria. Failed machines can lead to economic loss and safety problems due to unexpected production stoppages. Fault diagnosis in the condition monitoring of these machines is crucial for increasing machinery availability and reliability. Fault diagnosis of machinery is often a difficult and daunting task. To be truly effective, the process needs to be automated to reduce the reliance on manual data interpretation. It is the aim of this research to automate this process using data from machinery vibrations. This thesis focuses on the design, development, and application of an automatic diagnosis procedure for rolling element bearing faults. Rolling element bearings are representative elements in most industrial rotating machinery. Besides, these elements can also be tested economically in the laboratory using relatively simple test rigs. Novel modern signal processing methods were applied to vibration signals collected from rolling element tests to destruction. These included three advanced timefrequency signal processing techniques, best basis Discrete Wavelet Packet Analysis (DWPA), Matching Pursuit (MP), and Basis Pursuit (BP). This research presents the first application of the Basis Pursuit to successfully diagnosing rolling element faults. Meanwhile, Best basis DWPA and Matching Pursuit were also benchmarked with the Basis Pursuit, and further extended using some novel ideas particularly on the extraction of defect related features. The DWPA was researched in two aspects: i) selecting a suitable wavelet, and ii) choosing a best basis. To choose the most appropriate wavelet function and decomposition tree of best basis in bearing fault diagnostics, several different wavelets and decomposition trees for best basis determination were applied and comparisons made. The Matching Pursuit and Basis Pursuit techniques were effected by choosing a powerful wavelet packet dictionary. These algorithms were also studied in their ability to extract precise features as well as their speed in achieving a result. The advantage and disadvantage of these techniques for feature extraction of bearing faults were further evaluated. An additional contribution of this thesis is the automation of fault diagnosis by using Artificial Neural Networks (ANNs). Most of work presented in the current literature has been concerned with the use of a standard pre-processing technique - the spectrum. This research employed additional pre-processing techniques such as the spectrogram and DWPA based Kurtosis, as well as the MP and BP features that were subsequently incorporated into ANN classifiers. Discrete Wavelet Packets and Spectra, were derived to extract features by calculating RMS (root mean square), Crest Factor, Variance, Skewness, Kurtosis, and Matched Filter. Certain spikes in Matching Pursuit analysis and Basis Pursuit analysis were also used as features. These various alternative methods of pre-processing for feature extraction were tested, and evaluated with the criteria of the classification performance of Neural Networks. Numerous experimental tests were conducted to simulate the real world environment. The data were obtained from a variety of bearings with a series of fault severities. The mechanism of bearing fault development was analysed and further modelled to evaluate the performance of this research methodology. The results of the researched methodology are presented, discussed, and evaluated in the results and discussion chapter of this thesis. The Basis Pursuit technique proved to be effective in diagnostic tasks. The applied Neural Network classifiers were designed as multi layer Feed Forward Neural Networks. Using these Neural Networks, automatic diagnosis methods based on spectrum analysis, DWPA, Matching Pursuit, and Basis Pursuit proved to be effective in diagnosing different conditions such as normal bearings, bearings with inner race and outer race faults, and rolling element faults, with high accuracy. Future research topics are proposed in the final chapter of the thesis to provide perspectives and suggestions for advancing research into fault diagnosis and condition monitoring.

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Yang, Hongyu. "Automatic Fault Diagnosis of Rolling Element Bearings Using Wavelet Based Pursuit Features." Queensland University of Technology, 2005. http://eprints.qut.edu.au/16062/.

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Today's industry uses increasingly complex machines, some with extremely demanding performance criteria. Failed machines can lead to economic loss and safety problems due to unexpected production stoppages. Fault diagnosis in the condition monitoring of these machines is crucial for increasing machinery availability and reliability. Fault diagnosis of machinery is often a difficult and daunting task. To be truly effective, the process needs to be automated to reduce the reliance on manual data interpretation. It is the aim of this research to automate this process using data from machinery vibrations. This thesis focuses on the design, development, and application of an automatic diagnosis procedure for rolling element bearing faults. Rolling element bearings are representative elements in most industrial rotating machinery. Besides, these elements can also be tested economically in the laboratory using relatively simple test rigs. Novel modern signal processing methods were applied to vibration signals collected from rolling element tests to destruction. These included three advanced timefrequency signal processing techniques, best basis Discrete Wavelet Packet Analysis (DWPA), Matching Pursuit (MP), and Basis Pursuit (BP). This research presents the first application of the Basis Pursuit to successfully diagnosing rolling element faults. Meanwhile, Best basis DWPA and Matching Pursuit were also benchmarked with the Basis Pursuit, and further extended using some novel ideas particularly on the extraction of defect related features. The DWPA was researched in two aspects: i) selecting a suitable wavelet, and ii) choosing a best basis. To choose the most appropriate wavelet function and decomposition tree of best basis in bearing fault diagnostics, several different wavelets and decomposition trees for best basis determination were applied and comparisons made. The Matching Pursuit and Basis Pursuit techniques were effected by choosing a powerful wavelet packet dictionary. These algorithms were also studied in their ability to extract precise features as well as their speed in achieving a result. The advantage and disadvantage of these techniques for feature extraction of bearing faults were further evaluated. An additional contribution of this thesis is the automation of fault diagnosis by using Artificial Neural Networks (ANNs). Most of work presented in the current literature has been concerned with the use of a standard pre-processing technique - the spectrum. This research employed additional pre-processing techniques such as the spectrogram and DWPA based Kurtosis, as well as the MP and BP features that were subsequently incorporated into ANN classifiers. Discrete Wavelet Packets and Spectra, were derived to extract features by calculating RMS (root mean square), Crest Factor, Variance, Skewness, Kurtosis, and Matched Filter. Certain spikes in Matching Pursuit analysis and Basis Pursuit analysis were also used as features. These various alternative methods of pre-processing for feature extraction were tested, and evaluated with the criteria of the classification performance of Neural Networks. Numerous experimental tests were conducted to simulate the real world environment. The data were obtained from a variety of bearings with a series of fault severities. The mechanism of bearing fault development was analysed and further modelled to evaluate the performance of this research methodology. The results of the researched methodology are presented, discussed, and evaluated in the results and discussion chapter of this thesis. The Basis Pursuit technique proved to be effective in diagnostic tasks. The applied Neural Network classifiers were designed as multi layer Feed Forward Neural Networks. Using these Neural Networks, automatic diagnosis methods based on spectrum analysis, DWPA, Matching Pursuit, and Basis Pursuit proved to be effective in diagnosing different conditions such as normal bearings, bearings with inner race and outer race faults, and rolling element faults, with high accuracy. Future research topics are proposed in the final chapter of the thesis to provide perspectives and suggestions for advancing research into fault diagnosis and condition monitoring.

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Lennartsson, Richard. "Automatic diagnostic system for I-shift transmission using vibration analysis." Thesis, Linköping University, Automatic Control, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-57732.

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This master’s thesis work was performed at Volvo Powertrain in Köping, Sweden, which manufactures gearboxes and integrated transmission systems for heavy vehicles. The thesis is a continuation of a previous master’s thesis performed at the Köping factory in 2009. After manufacturing and assembly, each gearbox is manually validated to ensure the gearbox quality and functionality. When validating the gearbox gears, the operator shifts the gearbox in a predefined manner and listens for irregularities. If an error sound is heard the operator must then locate the source of error. With numerous of cog wheels rotating at the same time this task requires extensive knowledge and experience of the operator. The main objective is to develop an automatic diagnostic system for detection of cog errors and assist the operator in the process of locating the faulty component.

The work consists of two parts. In the first part the automatic diagnostic system is developed and a database of gearbox recordings is stored. The amounts of logged non-faulty gearboxes are significantly much larger (50) than the logged faulty gearboxes (1). Therefore, when determining thresholds needed for the diagnosis, the data obtained from the non-faulty gearboxes are used. Two statistical methods are presented to extract the thresholds. The first method uses an extremevalue distribution and the other method a Gaussian distribution. When validated, both methods did successfully detect on cog faults. In the second part an investigation is made of how shaft imbalance can be detected and implemented in the developed system.

Volvo Powertrain continually follows-up all faults found at the validation station to ensure the quality of their work and eliminate the sources of error. During system testing one logged gearbox was found faulty. The automatic diagnostic system did successfully detect and locate the faulty component which later also was confirmed when the gearbox was dismounted. With only one detected error it is difficult to conclude the system performance and further testing is required. However, during the testing no false detections were made.

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Zornoza, Moreno Enrique. "Model-based approach for automatic generation of IEC-61025 standard compliant fault trees." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-40912.

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Reliability and safety of complex software-intensive systems are proved to be a crucial matter since most of these systems fulfil tasks, where a failure could lead to catastrophic consequences. For example, in space systems such as satellites, a failure could result in the loss of the satellite. Therefore, a certain level of reliability and safety must be assured for such systems to trust the services they provide. Standards set this level and put requirements for the analysis and assurance of these properties using documented evidence. In particular, European Cooperation for Space Standardization (ECSS) standards for space systems require Fault Tree Analysis(FTA) for identifying the causes of system failure and consequently safety hazards, as well as fault trees as evidence for the assurance of reliability and safety. In this thesis, we present a tool supported model-based approach to generate fault tree automatically from an existing system modelling and analysis toolset. CHESS is a system and dependability modelling toolset and integrates Concerto-FLA to enable the support of failure logic analysis. We proposed a model-based transformation from Concerto-FLA to fault tree model and implemented it as an Eclipse plugin in CHESS toolset. A case study is performed in the aerospace domain; more specifically we modelled Attitude Control System (ACS) and automatically generated IEC-61025-compliant fault trees.
AMASS project

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Yalda, Riad, and Miroslav Urosevic. "Automatic post-fault analysis based on disturbance data stored in substation devices : Approach towards the preventive maintenance." Thesis, KTH, Hälsoinformatik och logistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-252823.

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This report studies the possibilities of minimizing unplanned maintenance work and improving the availability of power supply by enabling preventive maintenance in power systems, without having to make additional investments in the existing systems. This was done using information from COMTRADE files (disturbance recording files) that are created in the event of a fault in the power system. The IEC 61850 standard facilitates the process of retrieving and analyzing the disturbance files by standardizing their format and the way they are stored. By creating a software solution that automatically reads and analyses the COMTRADE files, deteriorating performance of the power system equipment can be detected and preventive maintenance suggested. The result of the project is a software solution that reads and analyses COMTRADE files in an automated way. The software identifies fault events (fault start, trip signal sent, circuit breaker open, auto-reclose command, circuit breaker closed) from the recorded signals using wavelet transform as the main method. It then calculates the times of relay and circuit breaker operations. The calculated times are compared to threshold values and warnings are generated if they exceed the thresholds.
Denna rapport studerar möjligheten att minimera oönskade underhållsarbeten och öka tillgången på strömförsörjning genom att möjliggöra förebyggande underhåll i kraftsystemet, utan att behöva göra ytterligare investeringar för sina befintliga system. Detta gjordes med hjälp av information från COMTRADE-filer (filer för inspelning av störningar) som skapades vid ett fel i elnätet. IEC 61850-standarden underlättar processen för att hämta och analysera störningsfilerna genom att standardisera sitt format och hur de lagras. Genom att skapa en programvarulösning som automatiskt läser och analyserar COMTRADE-filerna, kan försämrad prestanda hos strömsystemets utrustning detekteras och förebyggande underhåll föreslås. Resultatet av projektet är en mjukvarulösning som läser och analyserar COMTRADE-filer på ett automatiserat sätt. Programvaran identifierar felhändelser (fel start, sänd bryt-signal, brytare öppen, automatisk återstängnings kommando, strömbrytare stängd) från de inspelade signalerna med wavelettransformen som huvudmetod. Därefter beräknas driftstiderna för relä och brytare. De beräknade tiderna jämförs med tröskelvärden och varningar genereras om de överskrider tröskelvärdena.

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Meless, Dejen. "Test Cycle Optimization using Regression Analysis." Thesis, Linköping University, Automatic Control, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-54809.

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Industrial robots make up an important part in today’s industry and are assigned to a range of different tasks. Needless to say, businesses need to rely on their machine park to function as planned, avoiding stops in production due to machine failures. This is where fault detection methods play a very important part. In this thesis a specific fault detection method based on signal analysis will be considered. When testing a robot for fault(s), a specific test cycle (trajectory) is executed in order to be able to compare test data from different test occasions. Furthermore, different test cycles yield different measurements to analyse, which may affect the performance of the analysis. The question posed is: Can we find an optimal test cycle so that the fault is best revealed in the test data? The goal of this thesis is to, using regression analysis, investigate how the presently executed test cycle in a specific diagnosis method relates to the faults that are monitored (in this case a so called friction fault) and decide if a different one should be recommended. The data also includes representations of two disturbances.

The results from the regression show that the variation in the test quantities utilised in the diagnosis method are not explained by neither the friction fault or the test cycle. It showed that the disturbances had too large effect on the test quantities. This made it impossible to recommend a different (optimal) test cycle based on the analysis.

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Barrera, Núñez Víctor Augusto. "Automatic diagnosis of voltage disturbances in power distribution networks." Doctoral thesis, Universitat de Girona, 2012. http://hdl.handle.net/10803/80944.

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This thesis proposes a framework for identifying the root-cause of a voltage disturbance, as well as, its source location (upstream/downstream) from the monitoring place. The framework works with three-phase voltage and current waveforms collected in radial distribution networks without distributed generation. Real-world and synthetic waveforms are used to test it. The framework involves features that are conceived based on electrical principles, and assuming some hypothesis on the analyzed phenomena. Features considered are based on waveforms and timestamp information. Multivariate analysis of variance and rule induction algorithms are applied to assess the amount of meaningful information explained by each feature, according to the root-cause of the disturbance and its source location. The obtained classification rates show that the proposed framework could be used for automatic diagnosis of voltage disturbances collected in radial distribution networks. Furthermore, the diagnostic results can be subsequently used for supporting power network operation, maintenance and planning.
En esta tesis se propone una metodología para la identificación de la localización relativa (aguas arriba/abajo) y la causa de una perturbación eléctrica. La metodología utiliza las ondas trifásicas de tensión y de corriente registradas en redes de distribución radial sin presencia de generación distribuida. La metodología es validada utilizando perturbaciones eléctricas reales y simuladas. La metodología involucra atributos que han sido concebidos basándose en principios eléctricos e hipótesis de acuerdo a cada uno de los fenómenos eléctricos analizados. Se propusieron atributos tanto basados en la forma de onda como en la fecha de ocurrencia de la perturbación. La cantidad de información contenida y/o explicada por cada atributo es valorada mediante la aplicación del análisis multivariante de la varianza y algoritmos de extracción automática de reglas de decisión. Los resultados de clasificación muestran que la metodología propuesta puede ser utilizada para el diagnóstico automático de perturbaciones eléctricas registradas en redes de distribución radial. Los resultados de diagnóstico pueden ser utilizados para apoyar las tareas de operación, mantenimiento y planeamiento de las redes de distribución.

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Waly, Hashem. "Automated Fault Identification - Kernel Trace Analysis." Thesis, Université Laval, 2011. http://www.theses.ulaval.ca/2011/28246/28246.pdf.

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Hu, Peifeng. "Automated fault localization a statistical predicate analysis approach /." Click to view the E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B38838035.

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Hu, Peifeng, and 胡佩鋒. "Automated fault localization: a statistical predicate analysis approach." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B38838035.

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Andersson, Johan. "Automated Fault Tree Generation from Requirement Structures." Thesis, Linköpings universitet, Fordonssystem, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-122471.

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The increasing complexity of today’s vehicles gives drivers help with everything from adaptive cruisecontrol to warning lights for low fuel level. But the increasing functionality also increases the risk offailures in the system. To prevent system failures, different safety analytic methods can be used, e.g.,fault trees and/or FMEA-tables. These methods are generally performed manually, and due to thegrowing system size the time spent on safety analysis is growing with increased risk of human errors. If the safety analysis can be automated, lots of time can be saved. This thesis investigates the possibility to generate fault trees from safety requirements as wellas which additional information, if any, that is needed for the generation. Safety requirements are requirements on the systems functionality that has to be fulfilled for the safety of the system to be guaranteed. This means that the safety of the truck, the driver, and the surroundings, depend on thefulfillment of those requirements. The requirements describing the system are structured in a graphusing contract theory. Contract theory defines the dependencies between requirements and connectsthem in a contract structure. To be able to automatically generate the fault tree for a system, information about the systems failure propagation is needed. For this a Bayesian network is used. The network is built from the contract structure and stores the propagation information in all the nodes of the network. This will result in a failure propagation network, which the fault tree generation will be generated from. The failure propagation network is used to see which combinations of faults in the system can violate thesafety goal, i.e., causing one or several hazards. The result of this will be the base of the fault tree. The automatic generation was tested on two different Scania systems, the fuel level displayand the dual circuit steering. Validation was done by comparing the automatically generated trees withmanually generated trees for the two systems showing that the proposed method works as intended. The case studies show that the automated fault tree generation works if the failure propagationinformation exists and can save a lot of time and also minimize the errors made by manuallygenerating the fault trees. The generated fault trees can also be used to validate written requirementsto by analyzing the fault trees created from them.

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Rutaganda, Remmy. "Automated Model-Based Reliability Prediction and Fault Tree Analysis." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-67240.

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This work was undertaken as a final year project in Computer Engineering, within the Department of Computer and Information Science at Linköping University. At the Department of Computer and Information Science, work oriented at testing and analyzing applications is developed to provide solution approaches to problems that arise in system product development. One of the current applications being developed is the ‘Systemics Analyst’. The purpose of the application is to facilitate for system developers with an analysis tool permitting insights on system reliability, system critical components, how to improve the system and the consequences as well as risks of a system failure. The purpose of the present thesis was to enhance the ‘Systemics Analyst application’ by incorporating an ‘automated model-based reliability prediction’ and ‘fault tree analysis’ modules. This enables reliability prediction and fault tree analysis diagrams to be generated automatically from the data files and relieves the system developer from manual creation of the diagrams. The enhanced Systemics Analyst application managed to present the results in respective models using the new incorporated functionality. To accomplish the above tasks, ‘Systemics Analyst application’ was integrated with a library that handles automated model-based reliability prediction and fault tree analysis, which is described in this thesis. The reader will be guided through the steps that are performed to accomplish the tasks with illustrating figures, methods and code examples in order to provide a closer vision of the work performed.

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Singh, Shailendra. "Automated fault injection and analysis for wired/wireless networks." Diss., Online access via UMI:, 2009.

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Kincl, Zdeněk. "Metody pro testování analogových obvodů." Doctoral thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2013. http://www.nusl.cz/ntk/nusl-233583.

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Práce se zabývá metodami pro testování lineárních analogových obvodů v kmitočtové oblasti. Cílem je navrhnout efektivní metody pro automatické generování testovacího plánu. Snížením počtu měření a výpočetní náročnosti lze výrazně snížit náklady za testování. Práce se zabývá multifrekveční parametrickou poruchovou analýzou, která byla plně implementována do programu Matlab. Vhodnou volbou testovacích kmitočtů lze potlačit chyby měření a chyby způsobené výrobními tolerancemi obvodových prvků. Navržené metody pro optimální volbu kmitočtů byly statisticky ověřeny metodou MonteCarlo. Pro zvýšení přesnosti a snížení výpočetní náročnosti poruchové analýzy byly vyvinuty postupy založené na metodě nejmenších čtverců a přibližné symbolické analýze.

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Hossack, John A. "A multi-agent system for automated post-fault disturbance analysis." Thesis, University of Strathclyde, 2005. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=21606.

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Within today's privatised electricity industry, post-fault disturbance analysis is becoming an increasingly challenging prospect for protection engineers. Not only must they be proficient at operating a diverse range of data gathering tools but they must also be able to spend the time necessary to interpret the large volumes of data generated by modern network monitoring devices. Although a degree of automated assistance is provided by existing intelligent decision support tools, it remains for the protection engineer to manually collate and interpret the output of each system in order to compile a comprehensive understanding of each disturbance. As detailed in this thesis, the requirement for manual intervention has been eliminated through the development of the Protection Engineering Diagnostic Agents (PEDA) decision support architecture capable of automating all aspects of post-fault disturbance analysis. An essential component within this architecture is an alarm processor developed specifically to assist protection engineers with the early stages of post-fault disturbance analysis. The novel reasoning methodology employed emulates a protection engineer's approach to alarm analysis, providing automatic identification of transmission system disturbances and events. PEDA achieves fully automated post-fault disturbance analysis through the novel use of Multi-Agent Systems (MAS) to integrate the alarm processor with other automated systems for fault record retrieval, fault record interpretation and protection validation. As will be described in the thesis, achieving systems integration using MAS provides for levels of architecture flexibility and extensibility not previously realised within existing integrated decision support architectures. The PEDA architecture was developed following a comprehensive eleven stage methodology created as part of the reported research to assist with the specification of MAS for decision support within the power industry. Each stage of the PEDA specification process is detailed together with its implementation. Finally, the implemented architecture has been shown to offer automated retrieval, interpretation, collation and archiving of disturbance information within five minutes of a disturbance occurring. The beneficiaries of this near real-time provision of disturbance information need not be limited to protection engineers.

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Hogan, Paul Anthony. "A knowledge-based system for automated fault analysis of hydraulic systems." Thesis, University of Bath, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.332776.

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Ordonio, Robert Romero. "An automated tool to facilitate code translation for software fault tree analysis." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1993. http://handle.dtic.mil/100.2/ADA273205.

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Li, Tianpei. "Fault Diagnosis for Functional Safety in Electrified and Automated Vehicles." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1587583790925718.

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Winter, Mathias William. "Software fault tree analysis of an automated control system device written in Ada." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1995. http://handle.dtic.mil/100.2/ADA303377.

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Patil, Mayur. "Test Scenario Development Process and Software-in-the-Loop Testing for Automated Driving Systems." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1574794282029419.

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Weerasinghe, Manori. "Fault detection and diagnosis for complex multivariable processes using neural networks." Thesis, Liverpool John Moores University, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.298141.

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König, Johan. "Analyzing Substation Automation System Reliability using Probabilistic Relational Models and Enterprise Architecture." Doctoral thesis, KTH, Industriella informations- och styrsystem, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-145006.

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Modern society is unquestionably heavily reliant on supply of electricity. Hence, the power system is one of the important infrastructures for future growth. However, the power system of today was designed for a stable radial flow of electricity from large power plants to the customers and not for the type of changes it is presently being exposed to, like large scale integration of electric vehicles, wind power plants, residential photovoltaic systems etc. One aspect of power system control particular exposed to these changes is the design of power system control and protection functionality. Problems occur when the flow of electricity changes from a unidirectional radial flow to a bidirectional. Such an implication requires redesign of control and protection functionality as well as introduction of new information and communication technology (ICT). To make matters worse, the closer the interaction between the power system and the ICT systems the more complex the matter becomes from a reliability perspective. This problem is inherently cyber-physical, including everything from system software to power cables and transformers, rather than the traditional reliability concern of only focusing on power system components. The contribution of this thesis is a framework for reliability analysis, utilizing system modeling concepts that supports the industrial engineering issues that follow with the imple-mentation of modern substation automation systems. The framework is based on a Bayesian probabilistic analysis engine represented by Probabilistic Relational Models (PRMs) in com-bination with an Enterprise Architecture (EA) modeling formalism. The gradual development of the framework is demonstrated through a number of application scenarios based on substation automation system configurations. This thesis is a composite thesis consisting of seven papers. Paper 1 presents the framework combining EA, PRMs and Fault Tree Analysis (FTA). Paper 2 adds primary substation equipment as part of the framework. Paper 3 presents a mapping between modeling entities from the EA framework ArchiMate and substation automation system configuration objects from the IEC 61850 standard. Paper 4 introduces object definitions and relations in coherence with EA modeling formalism suitable for the purpose of the analysis framework. Paper 5 describes an extension of the analysis framework by adding logical operators to the probabilistic analysis engine. Paper 6 presents enhanced failure rates for software components by studying failure logs and an application of the framework to a utility substation automation system. Finally, Paper 7 describes the ability to utilize domain standards for coherent modeling of functions and their interrelations and an application of the framework utilizing software-tool support.

QC 20140505

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Russell, Kevin Joseph. "Model-Centric Interdependent Critical Infrastructure System Recovery Analysis and Metrics." Diss., Virginia Tech, 2016. http://hdl.handle.net/10919/71671.

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This dissertation defines and evaluates new operations management modeling concepts for use with interdependent critical infrastructure system reconfiguration and recovery analysis. The work combines concepts from Graph Trace Analysis (GTA), Object Oriented Analysis and Design (OOAandD), the Unified Modeling Language (UML) and Physical Network Modeling; and applies them to naval ship reduced manned Hull, Mechanical, Electrical and Damage Control (HMEandDC) system design and operation management. OOAandD problem decomposition is used to derive a natural solution structure that simplifies integration and uses mission priority and mission time constraint relationships to reduce the number of system states that must be evaluated to produce a practical solution. New concepts presented include the use of dependency components and automated system model traces to structure mission priority based recovery analysis and mission readiness measures that can be used for automating operations management analysis. New concepts for developing power and fluid system GTA loop flow analysis convergence measures and acceleration factors are also presented.
Ph. D.

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Hameed, Muhammad Muzaffar, and Muhammad Zeeshan ul Haq. "DefectoFix : An interactive defect fix logging tool." Thesis, Blekinge Tekniska Högskola, Avdelningen för programvarusystem, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-5268.

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Despite the large efforts made during the development phase to produce fault free system, most of the software implementations still require the testing of entire system. The main problem in the software testing is the automation that could verify the system without manual intervention. Recent work in software testing is related to the automated fault injection by using fault models from repository. This requires a lot of efforts, which adds to the complexity of the system. To solve this issue, this thesis suggests DefectoFix framework. DefectoFix is an interactive defect fix logging tools that contains five components namely Version Control Sysem (VCS), source code files, differencing algorithm, Defect Fix Model (DFM) creation and additional information (project name, class name, file name, revision number, diff model). The proposed differencing algorithm extracts detailed information by detecting differences in source code files. This algorithm performs comparison at sub-tree levels of source code files. The extracted differences with additional information are stored as DFM in repository. DFM(s) can later be used for the automated fault injection process. The validation of DefectoFix framework is performed by a tool developed using Ruby programming language. Our case study confirms that the proposed framework generates a correct DFM and is useful in automated fault injection and software validation activities.

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Yoshida, Everton Shigueaki. "Algoritmos para análise automática de faltas em sistemas elétricos de potência." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/3/3143/tde-29122014-175150/.

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Este trabalho apresenta o desenvolvimento de algoritmos para a análise automática de eventos de sobrecorrente em sistemas elétricos de potência. Os algoritmos propostos neste trabalho são baseados em registros de tensões e correntes, efetuados por dispositivos eletrônicos inteligentes (oscilógrafos digitais e/ou relés de proteção) instalados nas redes elétricas, e são capazes de avaliar o estado operativo dessas redes com base nessas informações. Os algoritmos integram um sistema automático de análise de eventos de sobrecorrente, que é capaz de estimar o instante de ocorrência do evento, identificar as fases envolvidas e classificar o tipo de falta por meio de fasores calculados a partir dos seus registros. Além disso, este trabalho apresenta uma comparação entre duas técnicas distintas para o cálculo do fasor (a primeira utiliza a Transformada Discreta de Fourier, com janela de um ciclo, e a segunda é baseada em algoritmos genéticos) e três técnicas distintas para a estimação do instante de ocorrência do evento (a primeira utiliza a transformada de Fourier associada a um filtro digital que implementa uma função densidade de probabilidade, a segunda substitui a transformada de Fourier pelos algoritmos genéticos e a terceira é baseada somente na Transformada de Park). Para a avaliação dos algoritmos desenvolvidos, foram elaboradas simulações de duas redes de distribuição no software ATP Alternative Electromagnetic Transients Program, além de dados reais de sistemas de distribuição de concessionárias brasileiras.
This work presents the development of algorithms for the automatic analysis of overcurrent events in electrical power systems. The algorithms proposed in this paper are based on data of voltages and currents recorded by intelligent electronic devices (digital oscillographs and / or protection relays) installed in electrical networks, which can evaluate the operating state of these networks based on this information. The algorithms incorporate an automatic system for overcurrent analysis, which is able to estimate the time of occurrence of the event, identify the steps involved and classify the fault type using the phasors of voltages and currents calculated from their records. Furthermore, this work presents a comparison between two distinct techniques for phasor calculation (the first one uses the Discrete Fourier Transform, with a cycle window, and the second one is based on genetic algorithms) and three distinct techniques to estimate the time of the occurrence of the event (the first is based on Fourier Transform and a digital filter that implements a probability density function, the second one replaces Fourier transform by Genetic Algorithm and the third one is based on Park transform). For the evaluation of the developed algorithms, cases from two distribution network model have been generated in the ATP software - Alternative Electromagnetic Transients Program, additionally, actual data from distribution Brazilian utilities systems were also analyzed by the developed algorithm.

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Plönnigs, Jörn. "Control Network Performance Engineering." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2007. http://nbn-resolving.de/urn:nbn:de:swb:14-1189518885137-19770.

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Beim Entwurf großer Netzwerke der Automation ermöglichen Methoden der Leistungsbewertung den Test und die Dimensionierung eines Netzwerkes bereits vor der Inbetriebnahme und erlauben damit einen effizienten, qualitätsorientierten Entwurf. Es ist jedoch sehr wissensintensiv und aufwendig, entsprechende Analyse- oder Simulations-Modelle aufzustellen und die Ergebnisse auszuwerten, weshalb die Methoden in der Praxis der Automation selten verwendet werden. Viel vertrauter sind dem Entwerfer hingegen die speziellen Software-Tools, mit denen in der Automation Netzwerke entworfen werden. Auf Basis der Datenbanken dieser Tools werden in dieser Arbeit verschieden Verfahren zur automatischen Systemmodellierung, Verkehrsmodellierung, Leistungsbewertung und Fehlerdiagnose zu einem Control Network Performance Engineering kombiniert, welches die Qualitätsbewertung und -beratung nahtlos und ohne Mehraufwand in den Netzwerkentwurf integriert. (Die Dissertation wurde veröffentlicht im Jörg Vogt Verlag, Voglerstr. 20, 01277 Dresden, Internet: http://www.vogtverlag.de/, email: info@vogtverlag.de, ISBN 978-3-938860-10-6)
During the design of large automation networks, performance analysis methods can be used for testing and dimensioning the network before implementation and are essential for an efficient and reliable design process. However, setting up the necessary analytical or simulative models is time-consuming, requires in-depth knowledge, and is therefore often not applicable in practice. The network designers are much more used to the design tools used to develop automation networks. Based on these tools' databases various methods for automated system and traffic modeling, performance analysis and diagnoses are combined in the control network performance engineering that seamlessly integrates quality analysis and consulting into network design without requiring additional effort. (This manuscript is also available - in the form of a book - from Jörg Vogt Verlag, Voglerstr. 20, 01277 Dresden, Germany world-wide web address: http://www.vogtverlag.de/, electronic-mail address: info@vogtverlag.de, ISBN 978-3-938860-10-6 )

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Ganapathy, Priya. "Development and Evaluation of a Flexible Framework for the Design of Autonomous Classifier Systems." Wright State University / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=wright1261335392.

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Trajin, Baptiste. "Analyse et traitement de grandeurs électriques pour la détection et le diagnostic de défauts mécaniques dans les entraînements asynchrones. Application à la surveillance des roulements à billes." Phd thesis, Institut National Polytechnique de Toulouse - INPT, 2009. http://tel.archives-ouvertes.fr/tel-00554240.

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Les entraînements électriques à base de machine asynchrone sont largement utilisés dans les applications industrielles en raison de leur faible coût, de leurs performances et de leur robustesse. Cependant, des modes de fonctionnement dégradés peuvent apparaître durant la vie de la machine. L'une des raisons principales de ces défaillances reste les défauts de roulements à billes. Afin d'améliorer la sûreté de fonctionnement des entraînements, des schémas de surveillance peuvent être mis en place afin d'assurer une maintenance préventive. Ce travail de thèse traite de la détection et du diagnostic des défauts mécaniques et plus particulièrement des défauts de roulements dans une machine asynchrone. Généralement, une surveillance vibratoire peut être mise en place. Cette méthode de surveillance est cependant souvent chère du fait de la chaîne de mesure. Une approche, basée sur l'analyse et le traitement des courants statoriques, est alors proposée, afin de suppléer à l'analyse vibratoire. L'étude est basée sur l'existence et la caractérisation des effets des oscillations du couple de charge sur les courants d'alimentation. Un schéma de détection est alors introduit pour détecter différents types de défauts de roulements. De plus, des variables mécaniques, telles que la vitesse ou le couple, sont également reconstruites afin de fournir une indication sur la présence de défauts de roulements. Par ailleurs, un diagnostic des modulations des courants statoriques est proposé, en régime permanent et en régime transitoire, quel que soit le rapport entre les fréquences porteuse et modulante. Les méthodes étudiées sont la transformée de Hilbert, la transformée de Concordia, l'amplitude et la fréquence instantanées ainsi que la distribution de Wigner-Ville.

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Musaruddin, Mustarum. "Automatic fault analysis in power systems via application service provider." Thesis, 2011. http://hdl.handle.net/2440/70281.

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This dissertation presents a new approach to automated fault analysis in electrical power systems. New contributions to the fault and disturbance investigation topic are automated fault analysis service (AFAS) via application service provider (ASP) and remote relay testing service (RRTS). The implementation of AFAS complies with the new international standard of communication network and system in substations (IEC-61850). The signal processing approaches in an automated fault analysis service are based on the wavelet transform and empirical mode decomposition methods. Several case studies have been carried out to test the performance of the signal segmentation technique. The data for analyses are from simulated fault data and from real disturbance records obtained from the intelligent electronic devices (IEDs) in substations. The implementation of AFAS and RRTS was developed using C# with .NET technologies, MATLAB and open source software. Signal segmentation, signal modelling, fault type classification, fault location service, a web-based COMTRADE viewer and remote relay test service have been developed in this dissertation. Such services are designed to enhance manual investigations performed by engineers. The services have been tested extensively using disturbance records from power utilities and a power system simulation model.
Thesis (Ph.D.) -- University of Adelaide, School of Electrical and Electronic Engineering, 2011

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Hsieh, Chih-Sheng, and 謝志勝. "Improving Feedback Time of Steelmaking Process by Big Data Analytics and Machine Learning Techniques for Automatic Instrument Fault Analysis." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/70750487989019391690.

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碩士
國立高雄應用科技大學
電機工程系博碩士班
105
The chemical analysis of steel is the key point of the steel-making process in the steel industry. International famous steelmaking plants have begun to automate to take the place of traditional artificial manual analysis. Traditional automate cannot be able to undertake these heavy tasks in the competitive international industry with the popularity of automatic analysis technique and the rising of the technological capability. It’s most important to develop the intelligent system by broken the traditional thinking of chemical analysis automate system. This study applies Machine Learning and Data Mining under the concept of automation more intelligent in Industry 4.0 to analysis the cause of equipment failure. This study still find out the best factor of train information by using support vector machines(SVM)，and using support vector regression(SVR) to find out the relationship between automation equipment and analysis feedback time. Then we can make sure the most important equipment which inference the analysis feedback time and improve it by using Multiple Regression Analysis. This study reveals that this way determines relevant factors correctly, and promotes the timeliness of automation during steel-making process effectively; in addition, it reduces required labor costs and time in data analysis. Especially, the study indicates not to aim at the equipment that breakdown easily, and differs from the traditional way.

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Yap, Choon-Shian, and 葉俊賢. "LOAD ANALYSIS AND FAULT RESTORATION IN DISTRIBUTION AUTOMATION USING NCKU DISTRIBUTION NETWORK." Thesis, 1994. http://ndltd.ncl.edu.tw/handle/44951082013744595476.

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碩士
國立成功大學
電機工程研究所
82
This thesis proposes a distribution automation case study for National Cheng Kung University (NCKU). Supporting from possible re-installation plan in NCKU, an effective and reasonable method to restore the non-faulted out-of-service area is proposed. The proposed method in this thesis is combined with a fully automated distribution system. In the control center, distribution engineers can recieve the information of the distribution system. When a fault has been detected, distribution engineers can isolate the faulted zone, restore the non-faulted out-of-service area through the control of switches and tie-switches in the automated distribution system. Using load flow calculation method to analyze and modify various loading case of the possible outage area, therefore the solution can determine the priority of the tie-switch for each outage case and establish a restoration data base. At the instant of fault,a suitable solution is directly searched from this data base to restore the out-of-service area. This thesis also suggests a load estimation calculation method to revise the data base. It can make the system operation with more safe and efficient. Distribution system in NCKU, feeders are connected radially.In this research, the parameters of this distribution system were determined to set up in data base. Through the Z-loop load flow method and the characteristic realization of this system, a suitable restoration data base which is under any condition of all possible outage areas has been established.

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Yan, Jiaxiang. "Modeling, monitoring and optimization of discrete event systems using Petri nets." 2014. http://hdl.handle.net/1805/3874.

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Indiana University-Purdue University Indianapolis (IUPUI)
Yan, Jiaxiang. M.S.E.C.E., Purdue University, May 2013. Modeling, Monitoring and Optimization of Discrete Event Systems Using Petri Nets. Major Professor: Lingxi Li. In last decades, the research of discrete event systems (DESs) has attracts more and more attention because of the fast development of intelligent control strategies. Such control measures combine the conventional control strategies with discrete decision-making processes which simulate human decision-making processes. Due to the scale and complexity of common DESs, the dedicated models, monitoring methods and optimal control strategies for them are necessary. Among various DES models, Petri nets are famous for the advantage in dealing with asynchronous processes. They have been widely applied in intelligent transportation systems (ITS) and communication technology in recent years. With encoding of the Petri net state, we can also enable fault detection and identification capability in DESs and mitigate potential human errors. This thesis studies various problems in the context of DESs that can be modeled by Petri nets. In particular, we focus on systematic modeling, asynchronous monitoring and optimal control strategies design of Petri nets. This thesis starts by looking at the systematic modeling of ITS. A microscopic model of signalized intersection and its two-layer timed Petri net representation is proposed in this thesis, where the first layer is the representation of the intersection and the second layer is the representation of the traffic light system. Deterministic and stochastic transitions are both involved in such Petri net representation. The detailed operation process of such Petri net representation is stated. The improvement of such Petri net representation is also provided with comparison to previous models. Then we study the asynchronous monitoring of sensor networks. An event sequence reconstruction algorithm for a given sensor network based on asynchronous observations of its state changes is proposed in this thesis. We assume that the sensor network is modeled as a Petri net and the asynchronous observations are in the form of state (token) changes at different places in the Petri net. More specifically, the observed sequences of state changes are provided by local sensors and are asynchronous, i.e., they only contain partial information about the ordering of the state changes that occur. We propose an approach that is able to partition the given net into several subnets and reconstruct the event sequence for each subnet. Then we develop an algorithm that is able to reconstruct the event sequences for the entire net that are consistent with: 1) the asynchronous observations of state changes; 2) the event sequences of each subnet; and 3) the structure of the given Petri net. We discuss the algorithmic complexity. The final problem studied in this thesis is the optimal design method of Petri net controllers with fault-tolerant ability. In particular, we consider multiple faults detection and identification in Petri nets that have state machine structures (i.e., every transition in the net has only one input place and one output place). We develop the approximation algorithms to design the fault-tolerant Petri net controller which achieves the minimal number of connections with the original controller. A design example for an automated guided vehicle (AGV) system is also provided to illustrate our approaches.

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Dissertations / Theses on the topic 'Automatic fault analysis'

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