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Book Real Time Fault Monitoring of Industrial Processes

Download or read book Real Time Fault Monitoring of Industrial Processes written by A.D. Pouliezos and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 571 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Real Time Fault Monitoring of Industrial Processes

Download or read book Real Time Fault Monitoring of Industrial Processes written by Anastasios Pouliezos and published by Springer. This book was released on 2012-12-22 with total page 542 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Data Driven Fault Detection for Industrial Processes

Download or read book Data Driven Fault Detection for Industrial Processes written by Zhiwen Chen and published by Springer. This book was released on 2017-01-02 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: Zhiwen Chen aims to develop advanced fault detection (FD) methods for the monitoring of industrial processes. With the ever increasing demands on reliability and safety in industrial processes, fault detection has become an important issue. Although the model-based fault detection theory has been well studied in the past decades, its applications are limited to large-scale industrial processes because it is difficult to build accurate models. Furthermore, motivated by the limitations of existing data-driven FD methods, novel canonical correlation analysis (CCA) and projection-based methods are proposed from the perspectives of process input and output data, less engineering effort and wide application scope. For performance evaluation of FD methods, a new index is also developed.

Book Soft Sensors for Monitoring and Control of Industrial Processes

Download or read book Soft Sensors for Monitoring and Control of Industrial Processes written by Luigi Fortuna and published by Springer Science & Business Media. This book was released on 2007-05-31 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews current design paths for soft sensors, and guides readers in evaluating different choices. The book presents case studies resulting from collaborations between the authors and industrial partners. The solutions presented, some of which are implemented on-line in industrial plants, are designed to cope with a wide range of applications from measuring system backup and what-if analysis through real-time prediction for plant control to sensor diagnosis and validation.

Book Data Driven Fault Detection and Reasoning for Industrial Monitoring

Download or read book Data Driven Fault Detection and Reasoning for Industrial Monitoring written by Jing Wang and published by Springer. This book was released on 2022-01-04 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book assesses the potential of data-driven methods in industrial process monitoring engineering. The process modeling, fault detection, classification, isolation, and reasoning are studied in detail. These methods can be used to improve the safety and reliability of industrial processes. Fault diagnosis, including fault detection and reasoning, has attracted engineers and scientists from various fields such as control, machinery, mathematics, and automation engineering. Combining the diagnosis algorithms and application cases, this book establishes a basic framework for this topic and implements various statistical analysis methods for process monitoring. This book is intended for senior undergraduate and graduate students who are interested in fault diagnosis technology, researchers investigating automation and industrial security, professional practitioners and engineers working on engineering modeling and data processing applications. This is an open access book.

Book Fault Detection and Diagnosis in Industrial Systems

Download or read book Fault Detection and Diagnosis in Industrial Systems written by L.H. Chiang and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Real Time Microcomputer Control of Industrial Processes

Download or read book Real Time Microcomputer Control of Industrial Processes written by S.G. Tzafestas and published by Springer Science & Business Media. This book was released on 1990-08-31 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: The introduction of the microprocessor in computer and system engineering has motivated the development of many new concepts and has simplified the design of many modern industrial systems. During the first decade of their life. microprocessors have shown a tremendous evolution in all possible directions (technology. power. functionality. I/O handling. etc). Of course putting the microprocessors and their environmental devices into properly operating systems is a complex and difficult task requiring high skills for melding and integrating hardware. and systemic components. software This book was motivated by the editors' feeling that a cohesive reference is needed providing a good coverage of modern industrial applications of microprocessor-based real time control, together with latest advanced methodological issues. Unavoidably a single volume cannot be exhaustive. but the present book contains a sufficient number of important real-time applications. The book is divided in two sections. Section I deals with general hardware. software and systemic topics. and involves six chapters. Chapter 1. by Gupta and Toong. presents an overview of the development of microprocessors during their first twelve years of existence. Chapter 2. by Dasgupta. deals with a number of system software concepts for real time microprocessor-based systems (task scheduling. memory management. input-output aspects. programming language reqUirements.

Book Fault Detection in a Continuous Production Line Using Adaptive Control Chart Limits

Download or read book Fault Detection in a Continuous Production Line Using Adaptive Control Chart Limits written by Sara Mae Wilson and published by . This book was released on 2020 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fourth industrial revolution, known as Industry 4.0, has emerged in the past few decades. With its focus on digitization and interconnectivity between devices, data collection, and operator behavior, implementing Industry 4.0 in a factory gives manufacturers the ability to monitor manufacturing processes in real-time. By monitoring processes in real-time, operators can boost productivity and reduce waste by identifying issues in the manufacturing line faster and more frequently. This research was based on work completed at Industrial ML, a Cambridge-based, machine learning company that offers real-time production and quality monitoring to factories via their platform. The data used is from the manufacturing line of one of IML's clients, Industrial Steel, based in Japan. This thesis presents a comprehensive method for analyzing equipment data from a manufacturing line to determine which process control charts and equations are best-suited for real-time monitoring of the line. By evaluating the performance of X-Bar Charts, regressions, and S Charts in monitoring the various processes on the Industrial Steel manufacturing line, a different monitoring method was created. This method utilizes S Charts with 95th and 99th percentile limits calculated from historical data as upper limits and no lower limits to accommodate the low variance nature of many processes. This method's efficacy was tested by calculating the fraction of points from numerous long periods of continuous production (8 hours or more) that lay within these historical data percentile limits. For the variables analyzed, the percentile limits contained 95-99% of the data points. Some of the data ranges showed a higher variance of the data from the sensors; a set of higher variance limits were set for these ranges. A set of process control rules, adapted from the WECO rules, were established to guide how to determine out of control points on these S Charts with percentile limits.

Book Condition Monitoring and Diagnostic Engineering Management

Download or read book Condition Monitoring and Diagnostic Engineering Management written by A. Starr and published by Elsevier. This book was released on 2001-09-14 with total page 1021 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Proceedings contains the papers presented at the 14th International Conference on Condition Monitoring and Diagnostic Engineering Management (COMADEM 2001), held in Manchester, UK, on 4-6 September 2001. COMADEM 2001 builds on the excellent reputation of previous conferences in this series, and is essential for anyone working in the field of condition monitoring and maintenance management.The scope of the conference is truly interdisciplinary. The Proceedings contains papers from six continents, written by experts in industry and academia the world over, bringing together the latest thoughts on topics including: Condition-based maintenance Reliability centred maintenance Asset management Industrial case studies Fault detection and diagnosis Prognostics Non-destructive evaluation Integrated diagnostics Vibration Oil and debris analysis Tribology Thermal techniques Risk assessment Structural health monitoring Sensor technology Advanced signal processing Neural networks Multivariate statistics Data compression and fusion This Proceedings also contains a wealth of industrial case studies, and the latest developments in education, training and certification. For more information on COMADEM's aims and scope, please visit http://www.comadem.com

Book Fault Detection and Diagnosis in Engineering Systems

Download or read book Fault Detection and Diagnosis in Engineering Systems written by Janos Gertler and published by CRC Press. This book was released on 2017-11-22 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: Featuring a model-based approach to fault detection and diagnosis in engineering systems, this book contains up-to-date, practical information on preventing product deterioration, performance degradation and major machinery damage.;College or university bookstores may order five or more copies at a special student price. Price is available upon request.

Book Fault Detection and Diagnosis in Industrial Systems

Download or read book Fault Detection and Diagnosis in Industrial Systems written by L.H. Chiang and published by Springer Science & Business Media. This book was released on 2000-12-11 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Advances in Condition Monitoring  Optimization and Control for Complex Industrial Processes

Download or read book Advances in Condition Monitoring Optimization and Control for Complex Industrial Processes written by Zhiwei Gao and published by MDPI. This book was released on 2021-09-01 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book documents 25 papers collected from the Special Issue “Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes”, highlighting recent research trends in complex industrial processes. The book aims to stimulate the research field and be of benefit to readers from both academic institutes and industrial sectors.

Book Fault Detection  Supervision and Safety of Technical Processes 2003  SAFEPROCESS 2003

Download or read book Fault Detection Supervision and Safety of Technical Processes 2003 SAFEPROCESS 2003 written by Marcel Staroswiecki and published by Elsevier. This book was released on 2004-02-27 with total page 1210 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Empirical Approach to Machine Learning

Download or read book Empirical Approach to Machine Learning written by Plamen P. Angelov and published by Springer. This book was released on 2018-10-17 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a ‘one-stop source’ for all readers who are interested in a new, empirical approach to machine learning that, unlike traditional methods, successfully addresses the demands of today’s data-driven world. After an introduction to the fundamentals, the book discusses in depth anomaly detection, data partitioning and clustering, as well as classification and predictors. It describes classifiers of zero and first order, and the new, highly efficient and transparent deep rule-based classifiers, particularly highlighting their applications to image processing. Local optimality and stability conditions for the methods presented are formally derived and stated, while the software is also provided as supplemental, open-source material. The book will greatly benefit postgraduate students, researchers and practitioners dealing with advanced data processing, applied mathematicians, software developers of agent-oriented systems, and developers of embedded and real-time systems. It can also be used as a textbook for postgraduate coursework; for this purpose, a standalone set of lecture notes and corresponding lab session notes are available on the same website as the code. Dimitar Filev, Henry Ford Technical Fellow, Ford Motor Company, USA, and Member of the National Academy of Engineering, USA: “The book Empirical Approach to Machine Learning opens new horizons to automated and efficient data processing.” Paul J. Werbos, Inventor of the back-propagation method, USA: “I owe great thanks to Professor Plamen Angelov for making this important material available to the community just as I see great practical needs for it, in the new area of making real sense of high-speed data from the brain.” Chin-Teng Lin, Distinguished Professor at University of Technology Sydney, Australia: “This new book will set up a milestone for the modern intelligent systems.” Edward Tunstel, President of IEEE Systems, Man, Cybernetics Society, USA: “Empirical Approach to Machine Learning provides an insightful and visionary boost of progress in the evolution of computational learning capabilities yielding interpretable and transparent implementations.”

Book Fault Diagnosis Systems

Download or read book Fault Diagnosis Systems written by Rolf Isermann and published by Springer Science & Business Media. This book was released on 2005-10-13 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book On Line Fault Detection and Supervision in the Chemical Process Industries

Download or read book On Line Fault Detection and Supervision in the Chemical Process Industries written by P.S. Dhurjati and published by Pergamon. This book was released on 1993-04-13 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Addresses the application of quality management to the chemical process industry, in about 50 selected papers from an April 1991 symposium in Newark, Delaware. They discuss strategies for the detection and diagnosis of process faults; modeling, validation, and interpretation of process trends; neural networks in process supervision and fault diagnosis; and other aspects. Reproduced from the authors' copies. Annotation copyright by Book News, Inc., Portland, OR

Book Real Time Fault Detection and Diagnosis Using Intelligent Monitoring and Supervision Systems

Download or read book Real Time Fault Detection and Diagnosis Using Intelligent Monitoring and Supervision Systems written by Gustavo Pérez Alvarez and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In monitoring and supervision schemes, fault detection and diagnosis characterize high efficiency and quality production systems. To achieve such properties, these structures are based on techniques that allow detection and diagnosis of failures in real time. Detection signals faults and diagnostics provide the root cause and location. Fault detection is based on signal and process mathematical models, while fault diagnosis is focused on systems theory and process modeling. Monitoring and supervision complement each other in fault management, thus enabling normal and continuous operation. Its application avoids stopping productive processes by early detection of failures and by applying real-time actions to eliminate them, such as predictive and proactive maintenance based on process conditions. The integration of all these methodologies enables intelligent monitoring and supervision systems, enabling real-time fault detection and diagnosis. Their high performance is associated with statistical decision-making techniques, expert systems, artificial neural networks, fuzzy logic and computational procedures, making them efficient and fully autonomous in making decisions in the real-time operation of a production system.