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This book provides control engineers and workers in industrial and academic research establishments interested in process engineering with a means to build up a practical and functional supervisory control environment and to use sophisticated models to get the best use out of their process data. Several applications to academic and small-scale-industrial processes are discussed and the development of a supervision platform for an industrial plant is presented.
Data-Driven and Model-Based Methods for Fault Detection and Diagnosis covers techniques that improve the quality of fault detection and enhance monitoring through chemical and environmental processes. The book provides both the theoretical framework and technical solutions. It starts with a review of relevant literature, proceeds with a detailed description of developed methodologies, and then discusses the results of developed methodologies, and ends with major conclusions reached from the analysis of simulation and experimental studies. The book is an indispensable resource for researchers in academia and industry and practitioners working in chemical and environmental engineering to do their work safely. - Outlines latent variable based hypothesis testing fault detection techniques to enhance monitoring processes represented by linear or nonlinear input-space models (such as PCA) or input-output models (such as PLS) - Explains multiscale latent variable based hypothesis testing fault detection techniques using multiscale representation to help deal with uncertainty in the data and minimize its effect on fault detection - Includes interval PCA (IPCA) and interval PLS (IPLS) fault detection methods to enhance the quality of fault detection - Provides model-based detection techniques for the improvement of monitoring processes using state estimation-based fault detection approaches - Demonstrates the effectiveness of the proposed strategies by conducting simulation and experimental studies on synthetic data
This book systematically presents a comprehensive framework and effective techniques for in-depth analysis, clear design procedure, and efficient implementation of diagnosis and prognosis algorithms for hybrid systems. It offers an overview of the fundamentals of diagnosis\prognosis and hybrid bond graph modeling. This book also describes hybrid bond graph-based quantitative fault detection, isolation and estimation. Moreover, it also presents strategies to track the system mode and predict the remaining useful life under multiple fault condition. A real world complex hybrid system—a vehicle steering control system—is studied using the developed fault diagnosis methods to show practical significance. Readers of this book will benefit from easy-to-understand fundamentals of bond graph models, concepts of health monitoring, fault diagnosis and failure prognosis, as well as hybrid systems. The reader will gain knowledge of fault detection and isolation in complex systems including those with hybrid nature, and will learn state-of-the-art developments in theory and technologies of fault diagnosis and failure prognosis for complex systems.
These Proceedings provide a general overview as well as detailed information on the developing field of reliability and safety of technical processes in automatically controlled processes. The plenary papers present the state-of-the-art and an overview in the areas of aircraft and nuclear power stations, because these safety-critical system domains possess the most highly developed fault management and supervision schemes. Additional plenary papers covered the recent developments in analytical redundancy. In total there are 95 papers presented in these Proceedings.
This book presents bond graph model-based fault detection with a focus on hybrid system models. The book addresses model design, simulation, control and model-based fault diagnosis of multidisciplinary engineering systems. The text beings with a brief survey of the state-of-the-art, then focuses on hybrid systems. The author then uses different bond graph approaches throughout the text and provides case studies.
Information Processing is a key area of research and development and the symposium presented state-of-the-art reports on some of the areas which are of relevance in automatic control: fault diagnosis and system reliability. Papers also covered the role of expert systems and other knowledge based systems, which are needed, to cope with the vast quantities of data generated by large scale systems. This volume should be considered essential reading for anyone involved in this rapidly developing area.
Model based control has emerged as an important way to improve plant efficiency in the process industries, while meeting processing and operating policy constraints. The reader of Methods of Model Based Process Control will find state of the art reports on model based control technology presented by the world's leading scientists and experts from industry. All the important issues that a model based control system has to address are covered in depth, ranging from dynamic simulation and control-relevant identification to information integration. Specific emerging topics are also covered, such as robust control and nonlinear model predictive control. In addition to critical reviews of recent advances, the reader will find new ideas, industrial applications and views of future needs and challenges. Audience: A reference for graduate-level courses and a comprehensive guide for researchers and industrial control engineers in their exploration of the latest trends in the area.
The development of computational intelligence (CI) systems was inspired by observable and imitable aspects of intelligent activity of human being and nature. The essence of the systems based on computational intelligence is to process and interpret data of various nature so that that CI is strictly connected with the increase of available data as well as capabilities of their processing, mutually supportive factors. Developed theories of computational intelligence were quickly applied in many fields of engineering, data analysis, forecasting, biomedicine and others. They are used in images and sounds processing and identifying, signals processing, multidimensional data visualization, steering of objects, analysis of lexicographic data, requesting systems in banking, diagnostic systems, expert systems and many other practical implementations. This book consists of 15 contributed chapters by subject experts who are specialized in the various topics addressed in this book. The special chapters have been brought out in the broad areas of Control Systems, Power Electronics, Computer Science, Information Technology, modeling and engineering applications. Special importance was given to chapters offering practical solutions and novel methods for the recent research problems in the main areas of this book, viz. Control Systems, Modeling, Computer Science, IT and engineering applications. This book will serve as a reference book for graduate students and researchers with a basic knowledge of control theory, computer science and soft-computing techniques. The resulting design procedures are emphasized using Matlab/Simulink software.
Social work supervision has been identified as one of the most important factors in determining the job satisfaction levels of social workers and the quality of service to clients. As an indirect but vital factor in the social work process, it is surprising that supervision has not received as much attention as other components of social work practice, such as social work research or administration. A book on social work supervision is desperately needed to bridge the gap between the demands of the field and the absence of literature. Social Work Supervision: Contexts and Concepts aims to provide readers with basic knowledge of theories, research, and practice of supervision. The book will address the needs of social work supervisors, frontline practitioners, students, and educators. The book is ideally suited as a text for graduate courses on social work supervision, as it contains a comprehensive literature review of the historical development, theories and models, and empirical research studies of the subject. Equally important, this is a book from practice experience in supervision that enhances the competence of supervisory practice. It will help social workers, supervisors, and administrators to realize and revitalize their "mission" in social work, that is, to benefit clients. Key Features: * Presents social work supervision as a rational, effective, and interactive process focusing on the whole person of the social worker * Discusses the history, the nature and definitions, and the theoretical models of social work supervision * Explores the major functions of social work supervision—administrative, educational, and supportive * Addresses the specific format and structure of supervision sessions
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.