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A three-volume work bringing together papers presented at 'SAFEPROCESS 2003', including four plenary papers on statistical, physical-model-based and logical-model-based approaches to fault detection and diagnosis, as well as 178 regular papers.
The first book on Prognostics and Health Management of Electronics Recently, the field of prognostics for electronic products has received increased attention due to the potential to provide early warning of system failures, forecast maintenance as needed, and reduce life cycle costs. In response to the subject's growing interest among industry, government, and academic professionals, this book provides a road map to the current challenges and opportunities for research and development in Prognostics and Health Management (PHM). The book begins with a review of PHM and the techniques being developed to enable a prognostics approach for electronic products and systems. building on this foundation, the book then presents the state of the art in sensor systems for in-situ health and usage monitoring. Next, it discusses the various models and algorithms that can be utilized in PHM. Finally, it concludes with a discussion of the opportunities in future research. Readers can use the information in this book to: Detect and isolate faults Reduce the occurrence of No Fault Found (NFF) Provide advanced warning of system failures Enable condition-based (predictive) maintenance Obtain knowledge of load history for future design, qualification, and root cause analysis Increase system availability through an extension of maintenance cycles and/or timely repair actions Subtract life cycle costs of equipment from reduction in inspection costs, down time, and inventory Prognostics and Health Management of Electronics is an indispensable reference for electrical engineers in manufacturing, systems maintenance, and management, as well as design engineers in all areas of electronics.
Guaranteeing a high system performance over a wide operating range is an important issue surrounding the design of automatic control systems with successively increasing complexity. As a key technology in the search for a solution, advanced fault detection and identification (FDI) is receiving considerable attention. This book introduces basic model-based FDI schemes, advanced analysis and design algorithms, and mathematical and control-theoretic tools. This second edition of Model-Based Fault Diagnosis Techniques contains: • new material on fault isolation and identification and alarm management; • extended and revised treatment of systematic threshold determination for systems with both deterministic unknown inputs and stochastic noises; • addition of the continuously-stirred tank heater as a representative process-industrial benchmark; and • enhanced discussion of residual evaluation which now deals with stochastic processes. Model-based Fault Diagnosis Techniques will interest academic researchers working in fault identification and diagnosis and as a text it is suitable for graduate students in a formal university-based course or as a self-study aid for practising engineers working with automatic control or mechatronic systems from backgrounds as diverse as chemical process and power engineering.
There is an increasing demand for dynamic systems to become more safe and reliable. This requirement extends beyond the normally accepted safety-critical systems of nuclear reactors and aircraft where safety is paramount important, to systems such as autonomous vehicles and fast railways where the system availability is vital. It is clear that fault diagnosis (including fault detection and isolation, FDI) has been becoming an important subject in modern control theory and practice. For example, the number of papers on FDI presented in many control-related conferences has been increasing steadily. The subject of fault detection and isolation continues to mature to an established field of research in control engineering. A large amount of knowledge on model-based fault diagnosis has been ac cumulated through the literature since the beginning of the 1970s. However, publications are scattered over many papers and a few edited books. Up to the end of 1997, there is no any book which presents the subject in an unified framework. The consequence of this is the lack of "common language", dif ferent researchers use different terminology. This problem has obstructed the progress of model-based FDI techniques and has been causing great concern in research community. Many survey papers have been published to tackle this problem. However, a book which presents the materials in a unified format and provides a comprehensive foundation of model-based FDI is urgently needed.
Theincreasingcomplexityofspacevehiclessuchassatellites,andthecostreduction measures that have affected satellite operators are increasingly driving the need for more autonomy in satellite diagnostics and control systems. Current methods for detecting and correcting anomalies onboard the spacecraft as well as on the ground are primarily manual and labor intensive, and therefore, tend to be slow. Operators inspect telemetry data to determine the current satellite health. They use various statisticaltechniques andmodels,buttheanalysisandevaluation ofthelargevolume of data still require extensive human intervention and expertise that is prone to error. Furthermore, for spacecraft and most of these satellites, there can be potentially unduly long delays in round-trip communications between the ground station and the satellite. In this context, it is desirable to have onboard fault-diagnosis system that is capable of detecting, isolating, identifying or classifying faults in the system withouttheinvolvementandinterventionofoperators.Towardthisend,theprinciple goal here is to improve the ef?ciency, accuracy, and reliability of the trend analysis and diagnostics techniques through utilization of intelligent-based and hybrid-based methodologies.
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.
Presents mathematical tools and techniques for solving change detection problems in wide domains like signal processing, controlled systems and monitoring. The book covers a wide class of stochastic processes, including scalar independent observations and multidimensional dependent ARMA.
“Fault Detection and Isolation: Multi-Vehicle Unmanned System” deals with the design and development of fault detection and isolation algorithms for unmanned vehicles such as spacecraft, aerial drones and other related vehicles. Addressing fault detection and isolation is a key step towards designing autonomous, fault-tolerant cooperative control of networks of unmanned systems. This book proposes a solution based on a geometric approach, and presents new theoretical findings for fault detection and isolation in Markovian jump systems. Also discussed are the effects of large environmental disturbances, as well as communication channels, on unmanned systems. The book proposes novel solutions to difficulties like robustness issues, as well as communication channel anomalies. “Fault Detection and Isolation: Multi-Vehicle Unmanned System” is an ideal book for researchers and engineers working in the fields of fault detection, as well as networks of unmanned vehicles.
We wish to extend a warm welcome to the reader of this extended postp- ceedings publication of SAG 2004, the 1st International Workshop on Scienti?c Applications on Grid Computing. This workshop was held in September 2004, in conjunction with the 2004 IEEE/WIC/ACM International Joint Conference on Web Intelligence (WI 2004) and Intelligent Agent Technology (IAT 2004). The WI and IAT conferences have provided, for several years, a leading - ternational forum to bring together researchers and practitioners from diverse ?elds,suchascomputerscience,informationtechnology,business,education,- man factors, systems engineering, and robotics, to explore the fundamental roles as well as practical impacts of arti?cial intelligence (AI) (e.g., knowledge r- resentation, planning, knowledge discovery, and data mining, intelligent agents and social network intelligence) and advanced information technology (IT) (e.g., wireless networks, ubiquitous devices, social networks, the Wisdom Web, and data/knowledge grids), and to examine the design principles and performance characteristics of various approaches in intelligent agent technology.
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.