Performance Monitoring and Fault Detection in Control Systems PDF Download
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Author: Matthew Lamont Tyler
Publisher:
ISBN:
Category : Electronic dissertations
Languages : en
Pages : 494
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Book Description
Author: Matthew Lamont Tyler
Publisher:
ISBN:
Category : Electronic dissertations
Languages : en
Pages : 494
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Book Description
Author: J. E. Seem
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Rolf Isermann
Publisher: Springer Science & Business Media
ISBN: 3540303685
Category : Technology & Engineering
Languages : en
Pages : 478
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Book Description
With increasing demands for efficiency and product quality plus progress in the integration of automatic control systems in high-cost mechatronic and safety-critical processes, the field of supervision (or monitoring), fault detection and fault diagnosis plays an important role. The book gives an introduction into advanced methods of fault detection and diagnosis (FDD). After definitions of important terms, it considers the reliability, availability, safety and systems integrity of technical processes. Then fault-detection methods for single signals without models such as limit and trend checking and with harmonic and stochastic models, such as Fourier analysis, correlation and wavelets are treated. This is followed by fault detection with process models using the relationships between signals such as parameter estimation, parity equations, observers and principal component analysis. The treated fault-diagnosis methods include classification methods from Bayes classification to neural networks with decision trees and inference methods from approximate reasoning with fuzzy logic to hybrid fuzzy-neuro systems. Several practical examples for fault detection and diagnosis of DC motor drives, a centrifugal pump, automotive suspension and tire demonstrate applications.
Author: Qiaolin Yuan
Publisher:
ISBN:
Category :
Languages : en
Pages : 216
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Book Description
Author: Steven X. Ding
Publisher: Springer Nature
ISBN: 3662620049
Category : Technology & Engineering
Languages : en
Pages : 664
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Book Description
The major objective of this book is to introduce advanced design and (online) optimization methods for fault diagnosis and fault-tolerant control from different aspects. Under the aspect of system types, fault diagnosis and fault-tolerant issues are dealt with for linear time-invariant and time-varying systems as well as for nonlinear and distributed (including networked) systems. From the methodological point of view, both model-based and data-driven schemes are investigated.To allow for a self-contained study and enable an easy implementation in real applications, the necessary knowledge as well as tools in mathematics and control theory are included in this book. The main results with the fault diagnosis and fault-tolerant schemes are presented in form of algorithms and demonstrated by means of benchmark case studies. The intended audience of this book are process and control engineers, engineering students and researchers with control engineering background.
Author: A.D. Pouliezos
Publisher: Springer Science & Business Media
ISBN: 9401583005
Category : Technology & Engineering
Languages : en
Pages : 571
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Book Description
This book presents a detailed and up-to-date exposition of fault monitoring methods in industrial processes and structures. The following approaches are explained in considerable detail: Model-based methods (simple tests, analytical redundancy, parameter estimation); knowledge-based methods; artificial neural network methods; and nondestructive testing, etc. Each approach is complemented by specific case studies from various industrial sectors (aerospace, chemical, nuclear, etc.), thus bridging theory and practice. This volume will be a valuable tool in the hands of professional and academic engineers. It can also be recommended as a supplementary postgraduate textbook. For scientists whose work involves automatic process control and supervision, statistical process control, applied statistics, quality control, computer-assisted predictive maintenance and plant monitoring, and structural reliability and safety.
Author: L.H. Chiang
Publisher: Springer Science & Business Media
ISBN: 1447103475
Category : Technology & Engineering
Languages : en
Pages : 281
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Book Description
Early and accurate fault detection and diagnosis for modern chemical plants can minimize downtime, increase the safety of plant operations, and reduce manufacturing costs. This book presents the theoretical background and practical techniques for data-driven process monitoring. It demonstrates the application of all the data-driven process monitoring techniques to the Tennessee Eastman plant simulator, and looks at the strengths and weaknesses of each approach in detail. A plant simulator and problems allow readers to apply process monitoring techniques.
Author: Mufeed Mahmoud
Publisher: Springer Science & Business Media
ISBN: 3540003185
Category : Technology & Engineering
Languages : en
Pages : 238
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Book Description
Modern technological systems rely on sophisticated control functions to meet increased performance requirements. For such systems, Fault Tolerant Control Systems (FTCS) need to be developed. Active FTCS are dependent on a Fault Detection and Identification (FDI) process to monitor system performance and to detect and isolate faults in the systems. The main objective of this book is to study and to validate some important issues in real-time Active FTCS by means of theoretical analysis and simulation. Several models are presented to achieve this objective, taking into consideration practical aspects of the system to be controlled, performance deterioration in FDI algorithms, and limitations in reconfigurable control laws.
Author: L.H. Chiang
Publisher: Springer Science & Business Media
ISBN: 9781852333270
Category : Technology & Engineering
Languages : en
Pages : 300
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Book Description
Early and accurate fault detection and diagnosis for modern chemical plants can minimize downtime, increase the safety of plant operations, and reduce manufacturing costs. This book presents the theoretical background and practical techniques for data-driven process monitoring. It demonstrates the application of all the data-driven process monitoring techniques to the Tennessee Eastman plant simulator, and looks at the strengths and weaknesses of each approach in detail. A plant simulator and problems allow readers to apply process monitoring techniques.
Author: Michael Edward Cholette
Publisher:
ISBN:
Category :
Languages : en
Pages : 378
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Book Description
Ensuring the reliable operation of engineering systems has long been a subject of great practical and academic interest. This interest is clearly demonstrated by the preponderance of literature in the area of Fault Detection and Diagnosis (FDD) and Fault Tolerant Control (FTC), spanning the past three decades. However, increasingly stringent performance and safety requirements have led to engineering systems with progressively increasing complexity. This complexity has rendered many traditional FDD and FTC methods exceedingly cumbersome, often to the point of infeasibility. This thesis aims to enable FDD and FTC for complex engineering systems of interacting dynamic subsystems. For such systems, generic FDD/FTC methods have remained elusive. Effects caused by nonlinearities, interactions between subsystems and varying usage patterns complicate FDD and FTC. The goal of this thesis is to develop methods for FDD and FTC that will allow decoupling of anomalies occurred inside the monitored system from those occurred in the systems affecting the monitored system, as well as enabling performance recovery of the monitored system. In pursuit of these goals, FDD and FTC methods are explored that can account for operating regime-dependent effects in monitoring, diagnosis, prognosis and performance recovery for two classes of machines: those that operate in modes that can change only at distinct times (which often occur in manufacturing operations such as drilling, milling, turning) and for those that operate in regimes that are continuously varying (such as automotive systems or electric motors). For machines that operate in modes that can change only at distinct times, a degradation model is postulated which describes how the system degrades over time for each operating regime. Using the framework of Hidden Markov Models (HMMs), modeling and identification tools are developed that enable identification a HMM of degradation for each machine operation. In the sequel, monitoring and prognosis methods that naturally follow from the framework of HMMs are also presented. The modeling and monitoring methodology is then applied to a real-world semiconductor manufacturing process using data provided by a major manufacturer. For machines that operate in regimes that are continuously varying, a behavioral model is postulated that describes the input-output dynamics of the normal system in different operating regimes. Monitoring methods are presented that have the capability to account for operating regime-dependent modeling accuracies and isolate faults that have not been anticipated and for which no fault models are available. By conducting fault detection in a regime-dependent fashion, changes in modeling errors that are due to operating regime changes can be successfully distinguished from changes that are due to truly faulty operation caused by changes in the system dynamics. Enabled by this, unanticipated faults can be isolated through proliferation of the fault detection through the various subsystems of the anomalous system. The FDD methodology is applied to detect and diagnose faults for a multiple-input multiple-output Exhaust Gas Recirculation system in a diesel engine. Finally, methods to facilitate the recovery of normal system behavior are detailed. Using the same local model structure that was pursued for behavioral models, it is envisioned that the nominal controller will be reconfigured to attempt to recover nominal behavior as much as possible. To enable this reconfiguration, methods for automated design of closed-loop controllers for the local modeling structure are presented. Using a model-predictive approach with rigorous stability considerations, it is shown that the controllers can track a reference trajectory. Such a trajectory could be generated by any model that satisfies the control objectives, for normal or faulty systems. The controllers are then demonstrated on a benchmark nonlinear system that is nonlinear in the control.
