Academic literature on the topic 'Advanced machine controls'
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Journal articles on the topic "Advanced machine controls":
1
Koren, Yoram. "Control of Machine Tools." Journal of Manufacturing Science and Engineering 119, no. 4B (November 1, 1997): 749–55. http://dx.doi.org/10.1115/1.2836820.
Abstract:
This paper reviews the progress in machine tool control during the last three decades. Three types of controls are discussed: (i) Servocontrol loops that control the individual axes of the machine, (ii) interpolators that coordinate the motion of several axes, and (iii) adaptive control that adjusts the cutting variables in real time to maximize system performance. We cover a selection of the most advanced techniques utilized in each of these types, and draw conclusions based on experimental results.
2
Chen, Mingzhang, Xinfei Ning, Zijian Zhou, Yuwen Shu, Yun Tang, Yang Cao, Xuebing Shang, and Xinghui Han. "LMS/RLS/OCTAVE Vibration Controls of Cold Orbital Forging Machines for Improving Quality of Forged Vehicle Parts." World Electric Vehicle Journal 13, no. 5 (April 27, 2022): 76. http://dx.doi.org/10.3390/wevj13050076.
Abstract:
Cold orbital forging (COF) as an advanced incremental metal-forming technology has been widely used in processing vehicle parts. During the COF process, the vibration on the COF machine injures the service life of the machine and the quality of the forged part. The study of the vibration control of the COF machine is therefore necessary. In this study, the dynamic model of the COF machine is established, and the vibration performances of some key positions are obtained using Matlab&Simulink software. Subsequently, the vibration performances are effectively verified by conducting a vibration test experiment. Based on the dynamics model of the COF machine and Matlab&Simulink software, least-mean-squares (LMS), recursive least-squares (RLS) and OCTAVE vibration-control algorithms are applied to reduce the vibration. Comparing the vibration performances of the COF machine, these vibration-control algorithms are useful for reducing the vibration of the machine, which improves the service life of the machine and the quality of the forged part. Based on the vibration performances of the COF machine, the effects of LMS and RLS vibration controls are better than the OCTAVE, and they also obviously reduce the vibration of the COF machine. The vibration-control algorithms are first to be applied to reduce the vibration of the COF machines in this study, which will be beneficial to future research on the vibration controls of metal-forming machines and other mechanical systems.
3
Wright, Alan D., and Mark J. Balas. "Design of Controls to Attenuate Loads in the Controls Advanced Research Turbine." Journal of Solar Energy Engineering 126, no. 4 (November 1, 2004): 1083–91. http://dx.doi.org/10.1115/1.1792654.
Abstract:
The wind industry seeks to design wind turbines to maximize energy production and increase fatigue life. To achieve this goal, we must design wind turbines to extract maximum energy and reduce component and system loads. This paper applies modern state-space control design methods to a two-bladed teetering-hub upwind machine located at the National Wind Technology Center. The design objective is to regulate turbine speed in region 3 (above rated wind speed) and enhance damping in several low-damped flexible modes of the turbine. The controls approach is based on the Disturbance Accommodating Control method and provides accountability for wind-speed disturbances. First, controls are designed with the single control input rotor collective pitch to stabilize the first drive-train torsion as well as the tower first fore-aft bending modes. Generator torque is then incorporated as an additional control input. This reduces some of the demand placed on the rotor collective pitch control system and enhances first drive train torsion mode damping. Individual blade pitch control is then used to attenuate wind disturbances having spatial variation over the rotor and effectively reduces blade flap deflections caused by wind shear.
4
Kim, Joong Nam. "Man-Machine Interface Design for Korean Next Generation Reactor: A Human Factors Perspective." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 44, no. 22 (July 2000): 823–26. http://dx.doi.org/10.1177/154193120004402285.
Abstract:
The concept of advanced man-machine interface (MMI) technology is employed to the design of the main control room (MCR) for Korean Next Generation Reactor (KNGR), an advanced light water nuclear power plant (NPP) currently under development. In the KNGR MCR, computerized workstations and digital operating systems provide the operator with electronically generated graphics and information for system status displays and plant controls. The introduction of digital technology to the development of advanced power plant control station has brought new issues and concerns associated with the KNGR MMI design, especially in human factors perspective. This paper presents some of human factors efforts in the development of KNGR MMIs that includes large screen display, workstation CRT, computerized procedure, and soft controller.
5
Xavier, André Amorim Gonçalves, Flavio Maldonado Bentes, Marcelo de Jesus Rodrigues da Nóbrega, Fabiano Battemarco da Silva Martins, and Hildson Rodrigues de Queiroz. "CNC Machine Building Through Open Sources Projects and Programs." International Journal for Innovation Education and Research 8, no. 9 (September 1, 2020): 108–18. http://dx.doi.org/10.31686/ijier.vol8.iss9.2600.
Abstract:
This research presents a theoretical and practical approach on the construction of a low-cost CNC machine, using as a base model found on the internet. Having his knowledge of movement that in the past was movement only one axis at a time, and in current controls movement on three simultaneous axes. The use of an Arduino micro controller will be the key part of the machine's operation, since it behaves like a PLC, starting from basic to advanced programming. The use of the project will end in its academic use and the dissemination of the technology used
6
Maleki, Ehsan, Brice Pridgen, William Singhose, Urs Glauser, and Warren Seering. "Educational Use of a Small-Scale Cherrypicker." International Journal of Mechanical Engineering Education 40, no. 2 (April 2012): 104–20. http://dx.doi.org/10.7227/ijmee.40.2.2.
Abstract:
Cherrypickers are a useful class of machines that can lift people to great heights. Unfortunately, the operator bucket oscillates and the entire machine can tip over in catastrophic accidents. Understanding the dynamics and stability of these machines is crucial for efficient and safe operation. To this end, a small-scale cherrypicker was constructed for experimental dynamic analysis and educational use. The dynamic behavior of the cherrypicker, as well as the improved system response using vibration-control techniques are presented. The cherrypicker was used during fall 2010 as an experimental apparatus in an advanced graduate controls course taught simultaneously at the Georgia Institute of Technology and the Massachusetts Institute of Technology. Its educational use in this multi-institutional course is discussed.
7
O’Brien, Megan K., Olivia K. Botonis, Elissa Larkin, Julia Carpenter, Bonnie Martin-Harris, Rachel Maronati, KunHyuck Lee, et al. "Advanced Machine Learning Tools to Monitor Biomarkers of Dysphagia: A Wearable Sensor Proof-of-Concept Study." Digital Biomarkers 5, no. 2 (July 27, 2021): 167–75. http://dx.doi.org/10.1159/000517144.
Abstract:
<b><i>Introduction:</i></b> Difficulty swallowing (dysphagia) occurs frequently in patients with neurological disorders and can lead to aspiration, choking, and malnutrition. Dysphagia is typically diagnosed using costly, invasive imaging procedures or subjective, qualitative bedside examinations. Wearable sensors are a promising alternative to noninvasively and objectively measure physiological signals relevant to swallowing. An ongoing challenge with this approach is consolidating these complex signals into sensitive, clinically meaningful metrics of swallowing performance. To address this gap, we propose 2 novel, digital monitoring tools to evaluate swallows using wearable sensor data and machine learning. <b><i>Methods:</i></b> Biometric swallowing and respiration signals from wearable, mechano-acoustic sensors were compared between patients with poststroke dysphagia and nondysphagic controls while swallowing foods and liquids of different consistencies, in accordance with the Mann Assessment of Swallowing Ability (MASA). Two machine learning approaches were developed to (1) classify the severity of impairment for each swallow, with model confidence ratings for transparent clinical decision support, and (2) compute a similarity measure of each swallow to nondysphagic performance. Task-specific models were trained using swallow kinematics and respiratory features from 505 swallows (321 from patients and 184 from controls). <b><i>Results:</i></b> These models provide sensitive metrics to gauge impairment on a per-swallow basis. Both approaches demonstrate intrasubject swallow variability and patient-specific changes which were not captured by the MASA alone. Sensor measures encoding respiratory-swallow coordination were important features relating to dysphagia presence and severity. Puree swallows exhibited greater differences from controls than saliva swallows or liquid sips (<i>p</i> < 0.037). <b><i>Discussion:</i></b> Developing interpretable tools is critical to optimize the clinical utility of novel, sensor-based measurement techniques. The proof-of-concept models proposed here provide concrete, communicable evidence to track dysphagia recovery over time. With refined training schemes and real-world validation, these tools can be deployed to automatically measure and monitor swallowing in the clinic and community for patients across the impairment spectrum.
8
Purushotham, Dr M. "Advanced Key Foundations of Multiagent System." International Journal for Research in Applied Science and Engineering Technology 11, no. 3 (March 31, 2023): 1–6. http://dx.doi.org/10.22214/ijraset.2023.49153.
Abstract:
Abstract: Ethics is inherently a multiagent concern. However, analysis on AI ethics nowadays is dominated by work on individual agents: (1) however Associate in Nursing autonomous golem or automotive could hurt or (differentially) profit folks in theoretical things (the questionable tramcar problems) and (2) how a machine learning formula could turn out biased choices or recommendations. The social group framework is basically omitted. To develop new foundations for ethics in AI, we tend to adopt a sociotechnical stance during which agents (as technical entities) facilitate autonomous social entities or principals (people and organizations). This multiagent conception of a sociotechnical system (STS) captures however moral considerations arise within the mutual interactions of multiple stakeholders. These foundations would modify USA to understand ethical STSs that incorporate social and technical controls to respect stated moral postures of the agents within the STSs. The visualized foundations need new thinking, on 2 broad themes, on how to realize (1) Associate in STS that reflects its stakeholders’ values and (2) individual agents that perform effectively in such Associate in STS.
9
Hafiz, Mohd Zani, Halim Isa, and Muhammad Syafiq Syed Mohamed. "An Overview of Ergonomics Problems Related to CNC Machining Operations." Advanced Engineering Forum 10 (December 2013): 137–42. http://dx.doi.org/10.4028/www.scientific.net/aef.10.137.
Abstract:
In the new era of advanced manufacturing technology, machine tool design plays an important role in maximizing productivity and occupational health of industrial workers. However, the machine tool manufacturers face difficulty in designing an ergonomic machine tool that can be suited to Malaysian industrial workers because almost all machine tools were designed according to physical dimensions, capabilities and limitations of European or American populations. This mismatch between machine design and worker abilities may eventually lead to occupational injuries. Therefore, the purpose of this paper is to disseminate information on ergonomics problem, assessment methods, and control measures associated with CNC machining operation. Published articles related to CNC machining operation have been reviewed. Based on published researches, work-related musculoskeletal disorders such as low-back pain, neck and shoulder problem have been identified as common health problems associated with the machine operation. Engineering and administrative controls have been proposed to minimize the health problems.
10
Castro-Martin, Ana Pamela, Horacio Ahuett-Garza, Darío Guamán-Lozada, Maria F. Márquez-Alderete, Pedro D. Urbina Coronado, Pedro A. Orta Castañon, Thomas R. Kurfess, and Emilio González de Castilla. "Connectivity as a Design Feature for Industry 4.0 Production Equipment: Application for the Development of an In-Line Metrology System." Applied Sciences 11, no. 3 (February 1, 2021): 1312. http://dx.doi.org/10.3390/app11031312.
Abstract:
Industry 4.0 (I4.0) is built upon the capabilities of Internet of Things technologies that facilitate the recollection and processing of data. Originally conceived to improve the performance of manufacturing facilities, the field of application for I4.0 has expanded to reach most industrial sectors. To make the best use of the capabilities of I4.0, machine architectures and design paradigms have had to evolve. This is particularly important as the development of certain advanced manufacturing technologies has been passed from large companies to their subsidiaries and suppliers from around the world. This work discusses how design methodologies, such as those based on functional analysis, can incorporate new functions to enhance the architecture of machines. In particular, the article discusses how connectivity facilitates the development of smart manufacturing capabilities through the incorporation of I4.0 principles and resources that in turn improve the computing capacity available to machine controls and edge devices. These concepts are applied to the development of an in-line metrology station for automotive components. The impact on the design of the machine, particularly on the conception of the control, is analyzed. The resulting machine architecture allows for measurement of critical features of all parts as they are processed at the manufacturing floor, a critical operation in smart factories. Finally, this article discusses how the I4.0 infrastructure can be used to collect and process data to obtain useful information about the process.
Dissertations / Theses on the topic "Advanced machine controls":
1
Ma, Yu Ph D. Massachusetts Institute of Technology. "Machine learning in ocean applications : wave prediction for advanced controls of renewable energy and modeling nonlinear viscous hydrodynamics." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/127057.
Abstract:
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, May, 2020Cataloged from the official PDF of thesis.
Includes bibliographical references (pages 144-150).
Many conventional problems in ocean engineering remain challenging due to the stochastic nature of ocean waves, viscous effects of the flow, nonlinear resonance, etc., and the combination of these factors. Data-driven techniques is an prospective approach complementary to traditional methods to model physical problems since data from experiments, field tests or high-fidelity simulations are mostly informative about actual physical systems. Machine learning algorithms, especially kernel based methods have very good generalization capability as well as statistical inference. This thesis targets to establish a framework that how we can use data from real-time measurements or data gathered from experiments and field tests and simulations to provide an alternative approach for physical modeling or practical engineering solutions.
In this thesis, we mainly target two different types of problems-mapping highly nonlinear physical relations and predicting time series, to prove the feasibility of such a framework. More specifically, one problem is the short-term wave prediction based on realtime measurements and its application to the advanced controls of renewable energy. The other one is the modeling of nonlinear viscous hydrodynamic loads of ships and offshore platforms. The Support Vector Machines (SVM) is used in solving both the problems. In the thesis, the SVM regression model are developed for the realtime short-term forecast of wave elevations and wave excitation forces. Optimal controllers aiming to reduce the structural loads or optimize energy capture with the knowledge of the forecasted wave force are established for offshore floating wind turbines and wave energy converters.
A series of CFD simulations of a rectangular barge with bilge keels are conducted and validated, along with the experiment data of a fixed offshore cylindrical platform, to serve as the baseline data set to model the nonlinear viscous hydrodynamic loads. Using the wave elevations and ship roll kinematics as features, the SVM regression models are trained and tested to predict the nonlinear hydrodynamic loads. The influence of the stochastic effect and different feature selections and kernel selections are discussed in the thesis as well. Key words: Machine learning, SVM regression, short-term forecast, model predictive control, nonlinear viscous hydrodynamic loads
by Yu Ma.
Ph. D.
Ph.D. Massachusetts Institute of Technology, Department of Mechanical Engineering
2
Bouyahia, Omar. "Génération électrique tolérante aux défauts à base de structures multiphasées : comparaison, choix d'une technologie, transfert technologique." Electronic Thesis or Diss., Amiens, 2022. http://www.theses.fr/2022AMIE0040.
Abstract:
Le projet de cette thèse consiste en la définition d'une génératrice multiphasée tolérante aux défauts permettant d'accroitre la fiabilité d'une chaîne de production électrique. En effet, quelle que soit l'énergie primaire fossile (pétrole, gaz, charbon) ou renouvelable (hydraulique, éolien, biomasse, solaire) utilisée en amont, il faut pour la transformer en énergie électrique une chaîne de conversion basée sur une génératrice électrique et ce quel que soit le niveau de puissance (du kW au MW). Cet élément, basiquement de structure triphasée, est sujet à pannes lors de la perte d'une phase. Aussi, en multipliant le nombre de phases, la production peut perdurer pour peu qu'il reste trois phases actives. Néanmoins, même si la génération est toujours possible, il faut définir une commande intelligente s'adaptant au défaut et pilotant le convertisseur de puissance de manière à maintenir une production d'énergie électrique propre respectant les règles imposées par le réseau électrique nationalThe project of this thesis consists in the definition of a fault tolerant multiphase generator allowing to increase the reliability of a production line. In fact, whatever the fossil fuel (oil, gas, coal) or renewable (hydraulic, wind, biomass, solar) primary energy used upstream, it is necessary to transform it into electric energy a conversion chain based on an electric generator. whatever the power level (from kW to MW). This element, basically of three-phase structure, is subject to failures during the loss of a phase. Also, by multiplying the number of phases, the production can continue if there remain three active phases. Nevertheless, even if the generation is still possible, it is necessary to define an intelligent control that adapts to the fault and drives the power converter so as to maintain a clean power generation complying with the rules imposed by the national power grid
3
BERTO, MATTEO. "Advanced Modeling of Anisotropic Synchronous Machine Drives for Sensorless Control." Doctoral thesis, Università degli studi di Padova, 2022. http://hdl.handle.net/11577/3459855.
Abstract:
Synchronous machines are extensively used for home appliances and industrial applications thanks to their fast dynamic response, good overload capability and high energy density. A precise knowledge of the rotor position is required to control efficiently this kind of motors. In most of the applications resolvers or absolute encoders are installed on the rotor shaft. The employment of position sensors leads to significant drawbacks such as the increased size and cost of the system and a lower reliability of the drive, caused by additional hardware and cabling.
In sensorless drives motor position is estimated and employed in the machine control. Thus, no position sensor is required by the drive and all the drawbacks entailed by the sensor are eliminated. Moreover, the position estimation could be useful for redundancy in case of system failures. Therefore, position estimation techniques are object of great interest in the electric drives field.
Position estimation techniques can be divided into two main categories: methods that are suitable for medium or high speed and techniques suitable for low speed or standstill operations. In the former group the motor position is estimated through a reconstruction of the permanent magnet flux or back electromotive force (back-EMF). In case of synchronous reluctance machines it is possible to reconstruct the extended active flux or back-EMF. Stator voltages and currents measurements are needed for these reconstruction methods. Since these signals amplitude is proportional to the rotor speed, position estimation can be successfully performed only for medium and high speed machine operations.
In the low speed range, sensorless schemes exploit the rotor magnetic anisotropy. Thus, position can be estimated only for anisotropic motors, i.e. synchronous reluctance motors (SynRM), permanent magnet assisted synchronous reluctance motors (PMA-SynRM) and interior permanent magnet synchronous motors (IPMSM). The rotor anisotropy is recognized thanks to an high frequency voltage injection in the stator windings. Several injection techniques have been proposed, differing from the signal typology. In particular, high frequency sinusoidal or square-wave carriers are often applied. The position information is usually extracted from the current response through a heterodyning demodulation that entails the use of low pass filters in the position estimator, limiting its dynamic.
The aim of the research was proposing a new algorithm to estimate the rotor position from the HF current response, getting rid of the demodulation and its weaknesses. Thus, the ellipse fitting technique has been proposed. Robustness against signal processing delay effects and a reduced number of required filters are the main advantages of this novel approach. The inverse problem related to the ellipse fitting is solved implementing a recursive least squares algorithm. The proposed ellipse fitting technique is not affected by signal processing delay effects, and it requires the tuning of only one parameter, called forgetting factor, making the studied method suitable for industrial application thanks to its minimal setup effort.
Besides the ellipse fitting technique for rotor position estimation, two other topics have been studied:
- Computation of self-sensing capabilities of synchronous machines.
- Online incremental inductances identification for SynRM.Synchronous machines are extensively used for home appliances and industrial applications thanks to their fast dynamic response, good overload capability and high energy density. A precise knowledge of the rotor position is required to control efficiently this kind of motors. In most of the applications resolvers or absolute encoders are installed on the rotor shaft. The employment of position sensors leads to significant drawbacks such as the increased size and cost of the system and a lower reliability of the drive, caused by additional hardware and cabling. In sensorless drives motor position is estimated and employed in the machine control. Thus, no position sensor is required by the drive and all the drawbacks entailed by the sensor are eliminated. Moreover, the position estimation could be useful for redundancy in case of system failures. Therefore, position estimation techniques are object of great interest in the electric drives field. Position estimation techniques can be divided into two main categories: methods that are suitable for medium or high speed and techniques suitable for low speed or standstill operations. In the former group the motor position is estimated through a reconstruction of the permanent magnet flux or back electromotive force (back-EMF). In case of synchronous reluctance machines it is possible to reconstruct the extended active flux or back-EMF. Stator voltages and currents measurements are needed for these reconstruction methods. Since these signals amplitude is proportional to the rotor speed, position estimation can be successfully performed only for medium and high speed machine operations. In the low speed range, sensorless schemes exploit the rotor magnetic anisotropy. Thus, position can be estimated only for anisotropic motors, i.e. synchronous reluctance motors (SynRM), permanent magnet assisted synchronous reluctance motors (PMA-SynRM) and interior permanent magnet synchronous motors (IPMSM). The rotor anisotropy is recognized thanks to an high frequency voltage injection in the stator windings. Several injection techniques have been proposed, differing from the signal typology. In particular, high frequency sinusoidal or square-wave carriers are often applied. The position information is usually extracted from the current response through a heterodyning demodulation that entails the use of low pass filters in the position estimator, limiting its dynamic. The aim of the research was proposing a new algorithm to estimate the rotor position from the HF current response, getting rid of the demodulation and its weaknesses. Thus, the ellipse fitting technique has been proposed. Robustness against signal processing delay effects and a reduced number of required filters are the main advantages of this novel approach. The inverse problem related to the ellipse fitting is solved implementing a recursive least squares algorithm. The proposed ellipse fitting technique is not affected by signal processing delay effects, and it requires the tuning of only one parameter, called forgetting factor, making the studied method suitable for industrial application thanks to its minimal setup effort. Besides the ellipse fitting technique for rotor position estimation, two other topics have been studied: - Computation of self-sensing capabilities of synchronous machines. - Online incremental inductances identification for SynRM.
4
VARATHARAJAN, ANANTARAM. "Generalized Sensorless and Advanced Control of Synchronous Reluctance Machines." Doctoral thesis, Politecnico di Torino, 2021. http://hdl.handle.net/11583/2872347.
5
Hsieh, Kuang-Han. "Part geometry for advanced quality control and process monitoring /." free to MU campus, to others for purchase, 1997. http://wwwlib.umi.com/cr/mo/fullcit?p9842539.
6
Milthorpe, Thomas Edward. "Development of advanced control strategies for a dynamic triaxial soil testing machine." Thesis, University of Reading, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.590131.
Abstract:
As civil engineering projects become increasingly ambitious, the earthworks that form a significant part of these projects become increasingly critical. Geotechnical engineering is concerned with the measurement , modelling and simulation of soil under various conditions for the application within civil engineering. In triaxial testing, an actuator applies a force or displacement to a soil sample. Dynamic triaxial testing is concerned with applying forces conforming to a rapidly changing pattern. The simplest case is concerned with applying a force in a sinusoidal pattern. The accuracy of models produced during triaxial testing depends largely on the accuracy of the equipment used for testing. As such, the control of the applied force is of great importance. The response of the soil sample directly influences the closed loop behaviour of the system. The soil sample response is unknown at the start of the test , can vary throughout a test and depends on various parameters, many of which are unobservable. This research investigates the issues faced in developing accurate control of dynamic triaxial testing equipment. Models of the load frame and various nonlinear soil sample responses are built for the purpose of simulation and controller design. Various control strategies are developed, implemented and tested, including the use of PID control, adaptive repetitive control and sliding mode control techniques. The recursive least squares algorithm is investigated and used for online identification in order to compensate for unknown and time varying plant parameters. Simulation and testing methods are investigated and several control methods are tested in simulation, on the target triaxial load frame using and finally using embedded processing hardware. Development and implementation techniques are also used including rapid prototyping and hardware-in-the-loop testing.
7
Jiffri, Shakir. "Advanced passive and active methods for vibration control in rotating machines." Thesis, University of Nottingham, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.582112.
Abstract:
Effective control of vibration in rotating machinery is a major concern in many industries and research institutions. With the ever-increasing drive for higher operating speeds, the need for developing vibration mitigation methods that cater for the arduous operating conditions that consequently arise is paramount. Phenomena that may have been insignificant in relatively low-speed rotating machines begin to gain importance with increasing speed, an example of which is the gyroscopic effect. This thesis is aimed at enriching the knowledge base on rotordynamic vibration control. Independent Modal Control (IMC) is addressed, within the context of rotating machinery. A study is performed on various actuation technologies that may be used to implement active vibration control. The well-known problem of balancing rotating machinery is also considered. The first-order modal filters based on Structure Preserving Transformations (SPTs) are capable of decoupling a rotor dynamic system into individual modes of vibration, such that IMC may be performed. Unlike traditional control schemes, the method based on first-order modal filters does not require the imposition of highly restrictive conditions on the system (classical damping). As a result, gyroscopic effects - which are substantial in high-speed rotating machinery - and non-classical damping may be fully accounted for in the modal domain. The main problem pertaining to this method arises from the fact that the response of the controlled system is linked with the stability of the modal filters. As such, if the filters are unstable, the controlled response is eventually overcome by noise. This thesis explores the spectral properties of the modal filter with a view to understanding the factors that affect its stability; some interesting findings on the filter eigenvalues are presented. Furthermore, the question as to whether filter stability is an essential requirement is addressed. The relationship between the rotordynamic system and the modal filter is also investigated. An illustration of the techniques developed in relation to IMC using first-order modal filters is presented in the form of a FE simulation on a realistic aero-engine model. The implementation of active vibration control in a dynamic system is realised through the application of control forces by actuators. In the case of rotating machines, these would normally be located at the bearings. Actuation may be achieved from a variety of technologies such as electromagnetic, piezoelectric, magnetostrictive, ultrasonic etc. This thesis conducts a study on some popular actuation technologies, with the aim of finding an effective alternative to the ubiquitous squeeze film damper. The merits and drawbacks of the various technologies are compared. Also, some novel design concepts are proposed, and (in some cases) their viability demonstrated through calculations. It is well-known that rotor unbalance is usually the main source of vibration in rotating machines. Thus, improvements in procedures for balancing such machines are continuously being sought. With increasing in-service operating speeds and ever more stringent standards, traditional balancing methods progressively become inadequate. One of the reasons for this is the inability of balancing tests to capture the contribution of patterns of unbalance that excite higher modes of vibration, as the tests speeds are usually lower than in-service speeds. This thesis proposes a robust balancing approach that utilises additional information on rotor unbalance, in the form of a covariance matrix, to improve the balancing procedure. The method is illustrated in a FE model of a rotating machine, and is shown to be superior to the traditional method.
8
Ouyang, Dingxin. "Intelligent Road Control System Using Advanced Image Processing Techniques." University of Toledo / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1352749656.
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Gao, Yuan, and 高源. "Control of chaos in advanced motor drives." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2005. http://hub.hku.hk/bib/B45014784.
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Cédric, Peeters. "Advanced signal processing for the identification and diagnosis of the condition of rotating machinery." Thesis, Lyon, 2019. http://www.theses.fr/2019LYSEI107.
Abstract:
Cette thèse porte sur des méthodes innovantes de contrôle de l'état de santé des machines tournantes par l’analyse des signaux vibratoires. En effet, la surveillance de l’état de santé des machines contribue à des améliorations substantielles des points de vue économique et de sureté. Afin d’y aboutir, l’une des manières les plus populaires est de recueillir les vibrations de la machine. La plupart de ces vibrations sont directement liées au comportement périodique des sous-systèmes de la machine tels que les arbres de rotation, engrenages, champs électriques rotationnels, etc. Cette connaissance peut être exploitée afin de concevoir une méthodologie adaptée à chaque type de défaut. Cette thèse s’intéresse aux étapes de la mise en œuvre de cette méthodologie. En règle générale, la première condition préalable à l’analyse avancée de l’information récoltée est la disponibilité de la vitesse instantanée de rotation. Cette vitesse doit être connue car la plupart des techniques du traitement du signal sont adaptées aux conditions de fonctionnement stationnaires. Ainsi, la connaissance de la vitesse permettra de compenser les fluctuations de vitesse, par exemple par le ré-échantillonnage angulaire du signal de vibration. Malgré l’existence d’outils de mesure permettant l’estimation de la vitesse tels que les codeurs et les tachymètres, cette thèse étudie le potentiel d’estimer la vitesse instantanée de rotation à partir des signaux vibratoires. Après l'estimation de la vitesse et le ré-échantillonnage angulaire, une étape suivante courante consiste à séparer le signal en composantes déterministes et stochastiques. Dans ce sens, l’efficacité et l’applicabilité de la procédure d'édition du cepstre sont analysées. Ensuite, différentes méthodes de filtrage sont appliquées au signal résiduel afin d’améliorer le rapport signal sur bruit. Pour cette fin, les méthodes existantes utilisant des critères conventionnels sont étudiées en parallèles avec une nouvelle méthodologie aveugle de filtrage. La dernière étape du processus de traitement consiste à diagnostiquer le défaut potentiel. Ainsi, des indicateurs statistiques sont calculés sur le signal obtenu après traitement et suivis dans le temps pour vérifier leurs variations. Dans de nombreux cas, la signature du défaut présente un comportement cyclostationaire. Par conséquent, cette thèse examine également différentes techniques d'analyse de la cyclostationarité. Enfin, les performances des différentes méthodes de traitement sont validées sur deux ensembles de données expérimentales de vibrations issues de boîtes de vitesses d’éoliennesThis Ph.D. dissertation targets innovative methods for vibration-based condition monitoring of rotating machinery. Substantial benefits can be achieved from an economical and a safety point of view using condition monitoring. One of the most popular methods to gather information about the state of machine parts is through the analysis of machine vibrations. Most of these vibrations are directly linked to periodical behavior of subsystems within the machine like e.g. rotating shafts, gears, rotating electrical fields, etc. This knowledge can be exploited to enable faultdependent processing schemes. This dissertation investigates how to implement and utilize these processing schemes and details the steps in such a procedure. Typically, the first prerequisite for advanced analysis is the availability of the instantaneous rotation speed. This speed needs to be known since most frequency-based analysis techniques assume stationary behavior. Knowledge of the speed thus allows for compensating speed fluctuations, for example through angular resampling of the vibration signal. While there are hardware-based solutions for speed estimation using angle encoders or tachometers, this thesis investigates the potential in vibration signals for speed estimation. After speed estimation and angular resampling, a common next step is to separate the signal into deterministic and stochastic components. The cepstrum editing procedure is examined for its efficacy and applicability. Afterwards, different filtering methods are inspected as to improve the signal-to-noise ratio of the signal content of interest. Existing methods using conventional criteria are investigated together with a novel blind filtering methodology. The final step in the multi-step processing scheme is to search for the potential fault. Statistical indicators can be calculated on the processed time domain signal and tracked over time to check for increases. In many cases, the fault signature exhibits cyclostationary behavior. Therefore this dissertation also examines different cyclostationary analysis techniques. Lastly, the performance of the different processing methods is validated on two experimental vibration data sets of wind turbine gearboxes
Books on the topic "Advanced machine controls":
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R, Hill Malcolm. Soviet advanced manufacturing technology and western export controls. Aldershot, Hants, England: Avebury, 1991.
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Lynch, Mike. Computer numerical control: Advanced techniques. New York: McGraw-Hill, 1992.
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1959-, Wang Lihui, and Xi Jeff 1958-, eds. Smart devices and machines for advanced manufacturing. London: Springer, 2008.
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Irschik, Hans, Michael Krommer, Valerii P. Matveenko, and Alexander K. Belyaev, eds. Dynamics and Control of Advanced Structures and Machines. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-79325-8.
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Irschik, Hans, and Kurt Schlacher, eds. Advanced Dynamics and Control of Structures and Machines. Vienna: Springer Vienna, 2004. http://dx.doi.org/10.1007/978-3-7091-2774-2.
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Matveenko, Valerii P., Michael Krommer, Alexander K. Belyaev, and Hans Irschik, eds. Dynamics and Control of Advanced Structures and Machines. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-90884-7.
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Irschik, Hans, Alexander Belyaev, and Michael Krommer, eds. Dynamics and Control of Advanced Structures and Machines. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-43080-5.
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Hans, Irschik, and Schlacher Kurt, eds. Advanced dynamics and control of structures and machines. Wien: Springer, 2004.
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Irschik, Hans, Michael Krommer, and Alexander K. Belyaev, eds. Advanced Dynamics and Model-Based Control of Structures and Machines. Vienna: Springer Vienna, 2012. http://dx.doi.org/10.1007/978-3-7091-0797-3.
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A, Franklin Judy, Mitchell Tom M. 1951-, and Thrun Sebastian 1967-, eds. Recent advances in robot learning. Boston: Kluwer Academic Publishers, 1996.
Book chapters on the topic "Advanced machine controls":
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De Doncker, Rik W., Duco W. J. Pulle, and André Veltman. "Control of Synchronous Machine Drives." In Advanced Electrical Drives, 179–219. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-48977-9_7.
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De Doncker, Rik W., Duco W. J. Pulle, and André Veltman. "Control of Induction Machine Drives." In Advanced Electrical Drives, 285–337. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-48977-9_9.
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De Doncker, Rik, Duco W. J. Pulle, and André Veltman. "Control of Synchronous Machine Drives." In Advanced Electrical Drives, 193–237. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-0181-6_7.
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De Doncker, Rik, Duco W. J. Pulle, and André Veltman. "Control of Induction Machine Drives." In Advanced Electrical Drives, 303–60. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-0181-6_9.
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Szulc, Michał, Jerzy Kasprzyk, and Jacek Loska. "Creep Testing Machine Identification for Power System Load Optimization." In Advanced, Contemporary Control, 113–22. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-35170-9_11.
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Kondaka, Lakshmisudha, Adwait Rangnekar, Akshay Shetty, and Yash Zawar. "ARTFDS–Advanced Railway Track Fault Detection System Using Machine Learning." In Inventive Systems and Control, 609–24. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1012-8_41.
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Fimmers, Christian, Simon Storms, and Christian Brecher. "Energy-Flexible Machine Control Interfaces." In Advances in Production Research, 563–73. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03451-1_55.
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Pietroni, Paolo, Barbara Torcianti, A. Bruni, and Cristalli Cristalli. "Advanced Dimensional Control on Washing Machine Sealing through Profilometry." In Advances in Intelligent and Soft Computing, 369–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23154-4_41.
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Glumineau, Alain, and Jesús de León Morales. "Dynamical Models of AC Machines." In Advances in Industrial Control, 1–44. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14586-0_1.
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Glumineau, Alain, and Jesús de León Morales. "Observability Property of AC Machines." In Advances in Industrial Control, 45–78. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14586-0_2.
Conference papers on the topic "Advanced machine controls":
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Ezell, N. Dianne, Brandon Wilson, Pradeep Ramuhalli, Wesley Williams, and Christian Petrie. "Non-Nuclear Advanced Controls Testbed." In 13th Nuclear Plant Instrumentation, Control & Human-Machine Interface Technologies (NPIC&HMIT 2023). Illinois: American Nuclear Society, 2023. http://dx.doi.org/10.13182/npichmit23-41567.
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Wasfy, Tamer M., Ayman M. Wasfy, Hazim El-Mounayri, and Daniel Aw. "Virtual Training Environment for a 3-Axis CNC Milling Machine." In ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/detc2005-84689.
Abstract:
A virtual training environment for a 3-axis CNC milling machine is presented. The key elements of the environment are: (a) textured 3D photo-realistic virtual models of the machines and lab; (b) machine simulator for the machines’ controls and moving parts; (c) semi-empirical model of the machining operation; (d) hierarchical knowledge-base for process training; (e) unstructured knowledge-base for lecture delivery; (f) natural-language human-like intelligent virtual tutors. Applications of the AVML include: training students to operate manufacturing machines in a safe environment, allowing students and researchers to view and interact with highly accurate physical simulation of manufacturing machines, and optimization of the manufacturing process plan by testing various plans on the virtual machine before actual machining. The virtual training environment will significantly reduce the cost and increase the accessibility and safety of advanced manufacturing training.
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Hunko, Wesley S., and Lewis N. Payton. "Implementing Computer Numerical Controls Affordably at a Four Year University." In ASME 2016 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/imece2016-66152.
Abstract:
Additive manufacturing, fundamentally, is computerized numerical controls using a specialized printer head as the “tool”. Any new curriculum implementing “additive manufacturing” stands upon the fundamental and advanced work done before in computer numerical controls. Although there certainly is a need for end user laboratories based upon purchased printers, the challenge in designing curriculums that support developing the next generation of additive manufacturing must also include computer numerical controls. The best designers must be able to picture the entire system when developing new systems. During the late twentieth and early twenty-first centuries, the “hands-on” engineering laboratories typical of the post-World War II engineering campus gave way to computerized laboratories and simulation. Traditional engineering assets (lathes, mills, drill presses, etc.) were retired as they aged without replacement in favor of computer laboratories full of PC’s and software. As the 20th century ended, there was a realization that computer simulation is no substitute for “cutting metal” or “making things”. Designers need to understand process in order to communicate with technologists from trade schools and industry. Even a simple engineering drawing can often simply not be created due to process limitations (e.g., a perfectly drawn internal 90-degree angle in a CAD drawing does not occur in nature OR a machine shop). As the four year universities shut down their hands on programs, the two year programs implemented complex computer numerical controls curriculums to train operators for industry. The incredibly expensive equipment needed to do this is funded by state governments trying to attract industry to the state. The four year universities, responsible for creating the next generation of manufacturing machines, do not have access to THIS generations machines. The National Science Foundation and state governments don’t see the need for upper level engineering students to have ready access to machines that cost up to a million dollars each. The universities fortunate to have CNC machines usually keep them locked away from the students for safety of the machines and the students. Technicians make things for the students on the limited number or machines available. There is no understanding of the machines and very little understanding of the processes the machines are doing. An earlier paper by the authors described a way to implement an affordable undergraduate “manual” innovation laboratory. This article describes an affordable way for upper level universities to implement an effective machine design atmosphere for subtractive and additive manufacturing. The students modify existing machines from that earlier laboratory into multi-axis CNC machines. Students have successfully built five axis mills, lathes with live tooling and now a unique metal printing machine. The goal is not to create operators, but to enable designers of the next generation of machines. At the very least, students are immediately useful as design engineers when hired by companies making the most advanced (and expensive) additive/subtractive machines. The emphasis is not on expensive super machines but on very capable simple machines as emphasized in the Toyota Production System. One specific, inexpensive example will be provided for other institutions to utilize. The result has been an affordable laboratory that supports undergraduate students, graduate research students, and the university as a whole while teaching the design and control of computer numerical machines.
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Wright, Alan D., and Mark J. Balas. "Design of Modern Controls for the Controlled Advanced Research Turbine (CART)." In ASME 2003 Wind Energy Symposium. ASMEDC, 2003. http://dx.doi.org/10.1115/wind2003-1041.
Abstract:
Control can improve the performance of wind turbines by enhancing energy capture and reducing dynamic loads. At the National Renewable Energy Laboratory, we are designing control algorithms for regulation of turbine speed and power using state-space control methods. In this paper, we describe the design of a control algorithm for regulation of rotor speed in full-load operation (region 3) for the Controlled Advanced Research Turbine (CART). This turbine is a two-bladed, teetering hub, upwind machine, adapted for testing a variety of control algorithms. We base our control design on simple linear models of a turbine, which contain rotor and generator rotation, drivetrain torsion, rotor flap, and tower fore-aft bending degrees of freedom. We account for wind-speed fluctuations using disturbance accommodating control (DAC). We show the capability of these control schemes to stabilize the modeled turbine modes via pole placement while using state estimation to reduce the required number of turbine measurements. We test these algorithms through simulation, incorporating them into two simulation codes and simulating the controlled system for various operating conditions. Finally, we report conclusions to this work and outline future studies.
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Boring, Ronald. "Human Factors for Advanced Reactors." In 14th International Conference on Applied Human Factors and Ergonomics (AHFE 2023). AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1003781.
Abstract:
Existing light water reactors in the U.S. are primarily large baseload electricity generating facilities. The concept of operations for these plants remains largely unchanged since the advent of commercial nuclear power—the main control room serves as the hub of plant activities and is staffed with multiple licensed operators who work in tandem under the shift supervisor, and staff such as field workers support the control room remotely. While newer plants have brought the advent of digital human-machine interfaces to replace earlier analog and mechanical instrumentation and controls, much of the control process remains unchanged and manual. It is simply a newer version of legacy concepts. Advanced reactors potentially bring considerable changes to the size, fuel type, automation, and staffing of nuclear power plants, necessitating a fundamental shift not just from analog to digital, but further from human to automation, from onsite to remote, from control to monitoring, and from many to few operators. Despite this multitude of parallel evolutions in reactor designs, many of the vendors developing the next generation of reactors represent smaller research and development enterprises. It is therefore not feasible to address all aspects of plant design at the same time. In particular, the competing design aspects of new reactors present a significant challenge to the development of robust and human factored systems at the plant. As vendors develop new reactor designs, much of the early focus is naturally on the fuel and reactor system technology. Looming behind these early advances is the daunting prospect of first-of-a-kind control concepts that have not yet been developed or validated. A failure to address the human element of reactor design early will lead to missed opportunities. The quickest development process is the replication of existing concepts of operations at legacy plants, even when such systems were long ago surpassed by better human-machine technologies outside the nuclear industry. Conversely, attempting to undertake novel concepts of operations late in the design life cycle of a plant could result in protracted development efforts and delays in licensing and deployment. This does not have to happen, and it is imperative that human factors be considered now, early in the design of new reactors.
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Maleki, Ehsan, Brice Pridgen, Jing Qi Xiong, and William Singhose. "Dynamic Analysis and Control of a Portable Cherrypicker." In ASME 2010 Dynamic Systems and Control Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/dscc2010-4241.
Abstract:
Cherrypickers are an important class of machines that can lift people to great heights. Understanding the dynamics and stability of these machines is crucial for efficient and safe operation. A dynamic model has been developed to capture the oscillatory dynamics of the machine as a function of the configuration and mass properties. Simulation studies reveal the complex dynamic behavior of the machine. In many cases, the oscillation of the endpoint bucket causes difficulties and dangers for the operators. An input-shaping controller has been added to the system to decrease the oscillatory dynamics. A portable cherrypicker is being developed for use in both education and research. The cherrypicker will be used as an experimental testbed in an advanced controls course at the Massachusetts Institute of Technology. The MIT students will use the machine to verify their theoretical models of the dynamic behavior, as well as evaluate control systems they develop to improve performance. Concurrently, students at the Georgia Institute of Technology will use the machine in teleoperation mode to conduct similar experiments. The MIT and Georgia Tech students will work together to conduct meaningful research on the cherrypicker testbed for their course projects. This paper describes the developments and results of the project to date.
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Miller, Don W., Steven A. Arndt, Leonard J. Bond, Donald D. Dudenhoeffer, Bruce P. Hallbert, David E. Holcomb, Richard T. Wood, Joseph A. Naser, John O’Hara, and Edward L. Quinn. "Roadmap for Research, Development, and Demonstration of Instrumentation, Controls, and Human-Machine Interface Technologies." In 16th International Conference on Nuclear Engineering. ASMEDC, 2008. http://dx.doi.org/10.1115/icone16-48756.
Abstract:
Instrumentation, controls, and human-machine interfaces are essential enabling technologies that strongly influence nuclear power plant performance and operational costs. The nuclear power industry is currently engaged in a transition from traditional analog-based instrumentation, controls, and human-machine interface (ICHMI) systems to implementations employing digital technologies. This transition has primarily occurred in an ad hoc fashion through individual system upgrades at existing plants and has been constrained by a number of concerns. Although international implementation of evolutionary nuclear power plants and the progression toward new plants in the United States have spurred design of more fully digital plantwide ICHMI systems, the experience base in the nuclear power application domain is limited. Additionally, design and development programs by the U.S. Department of Energy (DOE) for advanced reactor concepts, such as the Generation IV Program and Next Generation Nuclear Plant (NGNP), introduce different plant conditions and unique plant configurations that increase the need for enhanced ICHMI capabilities to fully achieve programmatic goals related to economic competitiveness, safety and reliability, sustainability, and proliferation resistance and physical protection. As a result, there are challenges that need to be addressed to enable the nuclear power industry to effectively and efficiently complete the transition to safe and comprehensive use of digital technology.
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Rengan, Bharathan Kasthuri. "Smart Acquiring Platform in Contactless Payments using Advanced Machine Learning : Security Controls using Device Recognition, Geo Fencing and Customer on File." In 2023 IEEE Long Island Systems, Applications and Technology Conference (LISAT). IEEE, 2023. http://dx.doi.org/10.1109/lisat58403.2023.10179552.
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Anifowose, Fatai Adesina, Saeed Saad Alshahrani, and Mokhles Mustafa Mezghani. "Linear and Nonlinear Controls of Wireline Logs on Automated Grain Size Estimation Using Machine Learning Approach." In SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/205802-ms.
Abstract:
Abstract Wireline logs have been utilized to indirectly estimate various reservoir properties, such as porosity, permeability, saturation, cementation factor, and lithology. Attempts have been made to correlate Gamma-ray, density, neutron, spontaneous potential, and resistivity logs with lithology. The current approach to estimate grain size, the traditional core description, is time-consuming, labor-intensive, qualitative, and subjective. An alternative approach is essential given the utility of grain size in petrophysical characterization and identification of depositional environments. This paper proposes to fill the gap by studying the linear and nonlinear influences of wireline logs on reservoir rock grain size. We used the observed influences to develop and optimize respective linear and machine learning models to estimate reservoir rock grain size for a new well or targeted reservoir sections. The linear models comprised logistic regression and linear discriminant analysis while the machine learning method is random forest (RF). We will present the preliminary results comparing the linear and machine learning methods. We used anonymized wireline and archival core description datasets from nine wells in a clastic reservoir. Seven wells were used to train the models and the remaining two to test their classification performance. The grain size-types range from clay to granules. While sedimentologists have used gamma-ray logs to guide grain size qualification, the RF model recommended sonic, neutron, and density logs as having the most significant grain size in the nonlinear domain. The comparative results of the models' performance comparison showed that considering the subjectivity and bias associated with the visual core description approach, the RF model gave up to an 89% correct classification rate. This suggested looking beyond the linear influences of the wireline logs on reservoir rock grain size. The apparent relative stability of the RF model compared to the linear ones also confirms the feasibility of the machine learning approach. This is an acceptable and promising result. Future research will focus on conducting more rigorous quality checks on the grain size data, possibly introduce more heterogeneity, and explore more advanced algorithms. This will help to address the uncertainty in the grain size data more effectively and improve the models performance. The outcome of this study will reduce the limitations in the traditional core description and may eventually reduce the need for extensive core description processes.
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Godumagadda, A., A. Groh, E. Corne, and P. Kasireddy. "A Platform for Data Science and Analytics at the Edge." In IADC/SPE International Drilling Conference and Exhibition. SPE, 2024. http://dx.doi.org/10.2118/217722-ms.
Abstract:
Summary Increased digitalization in industry has brought forth a myriad of applications for data science and analytics over the past decade. As needs for advanced modeling and analytics have grown, this onshore drilling contractor embarked on a journey to centralize data acquisition, aggregation, transmission, and modeling into one platform located on-location. This paper explains how the combination of both data exchange and modeling has allowed for the development of three novel controls applications that are combinations of traditional programming and industrial control logic. This opens doors to make advanced data science modeling, such as machine learning and online learning, available directly to existing rig control systems that do not have these capabilities. The flexibility of this system offers significant opportunity for applying advanced analytics and data science tools at the rig site. Rig control systems are no longer limited by traditional industrial controllers but have the ability to interface with performance applications written in traditional programming languages. Applications running on our edge servers, integrated as input/output to the control systems, removes the limitations of the PLCs (programmable logic controllers) and allows us to "modernize" our control system without having to replace existing PLCs.
Reports on the topic "Advanced machine controls":
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Hovakimyan, Naira, Hunmin Kim, Wenbin Wan, and Chuyuan Tao. Safe Operation of Connected Vehicles in Complex and Unforeseen Environments. Illinois Center for Transportation, August 2022. http://dx.doi.org/10.36501/0197-9191/22-016.
Abstract:
Autonomous vehicles (AVs) have a great potential to transform the way we live and work, significantly reducing traffic accidents and harmful emissions on the one hand and enhancing travel efficiency and fuel economy on the other. Nevertheless, the safe and efficient control of AVs is still challenging because AVs operate in dynamic environments with unforeseen challenges. This project aimed to advance the state-of-the-art by designing a proactive/reactive adaptation and learning architecture for connected vehicles, unifying techniques in spatiotemporal data fusion, machine learning, and robust adaptive control. By leveraging data shared over a cloud network available to all entities, vehicles proactively adapted to new environments on the proactive level, thus coping with large-scale environmental changes. On the reactive level, control-barrier-function-based robust adaptive control with machine learning improved the performance around nominal models, providing performance and control certificates. The proposed research shaped a robust foundation for autonomous driving on cloud-connected highways of the future.
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Donald D Dudenhoeffer and Burce P Hallbert. Technology Roadmap Instrumentation, Control, and Human-Machine Interface to Support DOE Advanced Nuclear Energy Programs. Office of Scientific and Technical Information (OSTI), March 2007. http://dx.doi.org/10.2172/983948.
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Montero, Elkin Christian, Daniel Muñoz, and Anderson Téllez. Ventajas en costos, tiempo y mantenimiento a laboratorios, al diseñar plantas para el aprendizaje de la automatización y control de procesos industriales. Escuela Tecnológica Instituto Técnico Central, 2013. http://dx.doi.org/10.55411/2023.46.
Abstract:
One of the most important skills to an industrial levet is the control of industrial processes this in order to reach a good automation , the current industry needs trained personnel in these areas because most of the current machines are intelligent and increasingly most technologically advanced and automated undergraduate in this area is seer, by the electronics in your field somewhat analogous , as discreet as famous with PID control form that was borra in the early nineteenth century and today still a big boom industrial leve!. From AUTOMATOOLS have seen this need and the importance for students of Escuela Tecnologica and other universities and institutions interested in improving learning of control and process automation, with comprehensive training in these fields. AUTOMATOOLS it aims to cover the causes that prevent a breakthrough theme have both practical and theoretical because sometirnes time becomes the worst enemy when it comes to learning from these materials.
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Yang, Yu, and Hen-Geul Yeh. Electrical Vehicle Charging Infrastructure Design and Operations. Mineta Transportation Institute, July 2023. http://dx.doi.org/10.31979/mti.2023.2240.
Abstract:
California aims to achieve five million zero-emission vehicles (ZEVs) on the road by 2030 and 250,000 electrical vehicle (EV) charging stations by 2025. To reduce barriers in this process, the research team developed a simulation-based system for EV charging infrastructure design and operations. The increasing power demand due to the growing EV market requires advanced charging infrastructures and operating strategies. This study will deliver two modules in charging station design and operations, including a vehicle charging schedule and an infrastructure planning module for the solar-powered charging station. The objectives are to increase customers’ satisfaction, reduce the power grid burden, and maximize the profitability of charging stations using state-of-the-art global optimization techniques, machine-learning-based solar power prediction, and model predictive control (MPC). The proposed research has broad societal impacts and significant intellectual merits. First, it meets the demand for green transportation by increasing the number of EV users and reducing the transportation sector’s impacts on climate change. Second, an optimal scheduling tool enables fast charging of EVs and thus improves the mobility of passengers. Third, the designed planning tools enable an optimal design of charging stations equipped with a solar panel and battery energy storage system (BESS) to benefit nationwide transportation system development.