Download or read book Process Fault Detection and Diagnosis Using Neural Network expert System Hybrid Approach written by Nitin Mannikar and published by . This book was released on 1994 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Fault Diagnosis written by Józef Korbicz and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 936 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive work presents the status and likely development of fault diagnosis, an emerging discipline of modern control engineering. It covers fundamentals of model-based fault diagnosis in a wide context, providing a good introduction to the theoretical foundation and many basic approaches of fault detection.
Download or read book Fault Detection and Diagnosis Using Hybrid Artificial Neural Network Based Method written by Alibek Kopbayev and published by . This book was released on 2022 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis proposes a novel approach to fault detection and diagnosis (FDD) that is focused on artificial neural network (ANN). Unlike traditional methods for FDD, neural networks can take advantage of large amounts of complex process data and extract core features to help detect and diagnose faults. In the first part of this work, a hybrid model was developed to improve efficiency and feasibility of neural networks by combining Kernel Principal Analysis (kPCA) and deep neural network. The hybrid model was successfully validated by Tennessee Eastman Process. The second part of the research focuses on a specific application to gas leak detection and classification. In this scenario, a convolutional network (ConvNet) was used as a feature extraction tool prior to network training due to the visual nature of data. The model was shown to accurately predict leaks and leak sizes; furthermore, further model optimizations were performed and evaluated. The proposed approach is superior to other FDD approaches due to its performance and optimization flexibility.
Download or read book Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods written by Chris Aldrich and published by Springer Science & Business Media. This book was released on 2013-06-15 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique text/reference describes in detail the latest advances in unsupervised process monitoring and fault diagnosis with machine learning methods. Abundant case studies throughout the text demonstrate the efficacy of each method in real-world settings. The broad coverage examines such cutting-edge topics as the use of information theory to enhance unsupervised learning in tree-based methods, the extension of kernel methods to multiple kernel learning for feature extraction from data, and the incremental training of multilayer perceptrons to construct deep architectures for enhanced data projections. Topics and features: discusses machine learning frameworks based on artificial neural networks, statistical learning theory and kernel-based methods, and tree-based methods; examines the application of machine learning to steady state and dynamic operations, with a focus on unsupervised learning; describes the use of spectral methods in process fault diagnosis.
Download or read book Intelligent Quality Systems written by Duc T. Pham and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although the tenn quality does not have a precise and universally accepted definition, its meaning is generally well understood: quality is what makes the difference between success and failure in a competitive world. Given the importance of quality, there is a need for effective quality systems to ensure that the highest quality is achieved within given constraints on human, material or financial resources. This book discusses Intelligent Quality Systems, that is quality systems employing techniques from the field of Artificial Intelligence (AI). The book focuses on two popular AI techniques, expert or knowledge-based systems and neural networks. Expert systems encapsulate human expertise for solving difficult problems. Neural networks have the ability to learn problem solving from examples. The aim of the book is to illustrate applications of these techniques to the design and operation of effective quality systems. The book comprises 8 chapters. Chapter 1 provides an introduction to quality control and a general discussion of possible AI-based quality systems. Chapter 2 gives technical information on the key AI techniques of expert systems and neural networks. The use of these techniques, singly and in a combined hybrid fonn, to realise intelligent Statistical Process Control (SPC) systems for quality improvement is the subject of Chapters 3-5. Chapter 6 covers experimental design and the Taguchi method which is an effective technique for designing quality into a product or process. The application of expert systems and neural networks to facilitate experimental design is described in this chapter.
Download or read book A Hybrid Approach for Power Plant Fault Diagnostics written by Tamiru Alemu Lemma and published by Springer. This book was released on 2017-12-30 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a hybrid approach to fault detection and diagnostics. It presents a detailed analysis related to practical applications of the fault detection and diagnostics framework, and highlights recent findings on power plant nonlinear model identification and fault diagnostics. The effectiveness of the methods presented is tested using data acquired from actual cogeneration and cooling plants (CCPs). The models presented were developed by applying Neuro-Fuzzy (NF) methods. The book offers a valuable resource for researchers and practicing engineers alike.
Download or read book Fault Diagnosis of Nonlinear Systems Using a Hybrid Approach written by Ehsan Sobhani-Tehrani and published by Springer. This book was released on 2009-06-06 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
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.
Download or read book Artificial Intelligence in Process Fault Diagnosis written by Richard J. Fickelscherer and published by John Wiley & Sons. This book was released on 2024-02-21 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence in Process Fault Diagnosis A comprehensive guide to the future of process fault diagnosis Automation has revolutionized every aspect of industrial production, from the accumulation of raw materials to quality control inspections. Even process analysis itself has become subject to automated efficiencies, in the form of process fault analyzers, i.e., computer programs capable of analyzing process plant operations to identify faults, improve safety, and enhance productivity. Prohibitive cost and challenges of application have prevented widespread industry adoption of this technology, but recent advances in artificial intelligence promise to place these programs at the center of manufacturing process analysis. Artificial Intelligence in Process Fault Diagnosis brings together insights from data science and machine learning to deliver an effective introduction to these advances and their potential applications. Balancing theory and practice, it walks readers through the process of choosing an ideal diagnostic methodology and the creation of intelligent computer programs. The result promises to place readers at the forefront of this revolution in manufacturing. Artificial Intelligence in Process Fault Diagnosis readers will also find: Coverage of various AI-based diagnostic methodologies elaborated by leading experts Guidance for creating programs that can prevent catastrophic operating disasters, reduce downtime after emergency process shutdowns, and more Comprehensive overview of optimized best practices Artificial Intelligence in Process Fault Diagnosis is ideal for process control engineers, operating engineers working with processing industrial plants, and plant managers and operators throughout the various process industries.
Download or read book Artificial Neural Networks for the Modelling and Fault Diagnosis of Technical Processes written by Krzysztof Patan and published by Springer Science & Business Media. This book was released on 2008-06-24 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: An unappealing characteristic of all real-world systems is the fact that they are vulnerable to faults, malfunctions and, more generally, unexpected modes of - haviour. This explains why there is a continuous need for reliable and universal monitoring systems based on suitable and e?ective fault diagnosis strategies. This is especially true for engineering systems,whose complexity is permanently growing due to the inevitable development of modern industry as well as the information and communication technology revolution. Indeed, the design and operation of engineering systems require an increased attention with respect to availability, reliability, safety and fault tolerance. Thus, it is natural that fault diagnosis plays a fundamental role in modern control theory and practice. This is re?ected in plenty of papers on fault diagnosis in many control-oriented c- ferencesand journals.Indeed, a largeamount of knowledgeon model basedfault diagnosis has been accumulated through scienti?c literature since the beginning of the 1970s. As a result, a wide spectrum of fault diagnosis techniques have been developed. A major category of fault diagnosis techniques is the model based one, where an analytical model of the plant to be monitored is assumed to be available.
Download or read book Application of Signal Processing Tools and Artificial Neural Network in Diagnosis of Power System Faults written by Nabamita Banerjee Roy and published by CRC Press. This book was released on 2021-07-21 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explores methods of fault identification through programming and simulation in MATLAB Examines signal processing tools and their applications with examples Provides knowledge of artificial neural networks and their applications with illustrations Uses PNN and BPNN to identify the different types of faults and obtain their corresponding locations Discusses the programming of signal processing using Wavelet Transform and S-Transform
Download or read book A fault detection method for FADS system based on interval valued neutrosophic sets belief rule base and D S evidence reasoning written by Qianlei Jia and published by Infinite Study. This book was released on with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fault detection, with the characteristics of strong uncertainty and randomness, has always been one of the research hotspots in the field of aerospace. Considering that devices will inevitably encounter various unknown interference in the process of use, which greatly limits the performance of many traditional fault detection methods. Therefore, the main aim of this paper is to address this problem from the perspective of uncertainty and randomness of measurement signal. In information engineering, interval-valued neutrosophic sets (IVNSs), belief rule base (BRB), and Dempster-Shafer (D-S) evidence reasoning are always characterized by the strong ability in revealing uncertainty, but each has its drawbacks. As a result, the three theories are firstly combined in this paper to form a powerful fault detection algorithm. Besides, a series of innovations are proposed to improve the method, including a new score function based on p-norm for IVNSs and a new approach of calculating the similarity between IVNSs, which are both proved by authoritative prerequisites. To illustrate the effectiveness of the proposed method, flush air data sensing (FADS), a technologically advanced airborne sensor, is adopted in this paper. The aerodynamic model of FADS is analyzed in detail using knowledge of aerodynamics under subsonic and supersonic conditions, meanwhile, the high-precision model is established based on the aerodynamic database obtained from CFD software.
Download or read book Combined Expert System neural Networks Method for Process Fault Diagnosis written by and published by . This book was released on 1995 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: A two-level hierarchical approach for process fault diagnosis is an operating system employs a function-oriented approach at a first level and a component characteristic-oriented approach at a second level, where the decision-making procedure is structured in order of decreasing intelligence with increasing precision. At the first level, the diagnostic method is general and has knowledge of the overall process including a wide variety of plant transients and the functional behavior of the process components. An expert system classifies malfunctions by function to narrow the diagnostic focus to a particular set of possible faulty components that could be responsible for the detected functional misbehavior of the operating system. At the second level, the diagnostic method limits its scope to component malfunctions, using more detailed knowledge of component characteristics. Trained artificial neural networks are used to further narrow the diagnosis and to uniquely identify the faulty component by classifying the abnormal condition data as a failure of one of the hypothesized components through component characteristics. Once an anomaly is detected, the hierarchical structure is used to successively narrow the diagnostic focus from a function misbehavior, i.e., a function oriented approach, until the fault can be determined, i.e., a component characteristic-oriented approach.
Download or read book Data driven Methods for Fault Detection and Diagnosis in Chemical Processes written by Evan L. Russell and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: Early and accurate fault detection and diagnosis for modern chemical plants can minimise downtime, increase the safety of plant operations, and reduce manufacturing costs. The process-monitoring techniques that have been most effective in practice are based on models constructed almost entirely from process data. The goal of the book is to present the theoretical background and practical techniques for data-driven process monitoring. Process-monitoring techniques presented include: Principal component analysis; Fisher discriminant analysis; Partial least squares; Canonical variate analysis. The text demonstrates the application of all of the data-driven process monitoring techniques to the Tennessee Eastman plant simulator - demonstrating the strengths and weaknesses of each approach in detail. This aids the reader in selecting the right method for his process application. Plant simulator and homework problems in which students apply the process-monitoring techniques to a nontrivial simulated process, and can compare their performance with that obtained in the case studies in the text are included. A number of additional homework problems encourage the reader to implement and obtain a deeper understanding of the techniques. The reader will obtain a background in data-driven techniques for fault detection and diagnosis, including the ability to implement the techniques and to know how to select the right technique for a particular application.
Download or read book Algorithms for Fault Detection and Diagnosis written by Francesco Ferracuti and published by MDPI. This book was released on 2021-03-19 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the increasing demand for security and reliability in manufacturing and mechatronic systems, early detection and diagnosis of faults are key points to reduce economic losses caused by unscheduled maintenance and downtimes, to increase safety, to prevent the endangerment of human beings involved in the process operations and to improve reliability and availability of autonomous systems. The development of algorithms for health monitoring and fault and anomaly detection, capable of the early detection, isolation, or even prediction of technical component malfunctioning, is becoming more and more crucial in this context. This Special Issue is devoted to new research efforts and results concerning recent advances and challenges in the application of “Algorithms for Fault Detection and Diagnosis”, articulated over a wide range of sectors. The aim is to provide a collection of some of the current state-of-the-art algorithms within this context, together with new advanced theoretical solutions.
Download or read book Machine Learning Based Fault Diagnosis for Industrial Engineering Systems written by Rui Yang and published by CRC Press. This book was released on 2022-06-16 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides advanced techniques for precision compensation and fault diagnosis of precision motion systems and rotating machinery. Techniques and applications through experiments and case studies for intelligent precision compensation and fault diagnosis are offered along with the introduction of machine learning and deep learning methods. Machine Learning-Based Fault Diagnosis for Industrial Engineering Systems discusses how to formulate and solve precision compensation and fault diagnosis problems. The book includes experimental results on hardware equipment used as practical examples throughout the book. Machine learning and deep learning methods used in intelligent precision compensation and intelligent fault diagnosis are introduced. Applications to deal with relevant problems concerning CNC machining and rotating machinery in industrial engineering systems are provided in detail along with applications used in precision motion systems. Methods, applications, and concepts offered in this book can help all professional engineers and students across many areas of engineering and operations management that are involved in any part of Industry 4.0 transformation.
Download or read book Masters Theses in the Pure and Applied Sciences written by Wade H. Shafer and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: Masters Theses in the Pure and Applied Sciences was first conceived, published, and disseminated by the Center for Information and Numerical Data Analysis and Synthesis (CINDAS)* at Purdue University in 1957, starting its coverage of theses with the academic year 1955. Beginning with Volume 13, the printing and dis semination phases of the activity were transferred to University Microfilms/Xerox of Ann Arbor, Michigan, with the thought that such an arrangement would be more beneficial to the academic and general scientific and technical community. After five years of this joint undertaking we had concluded that it was in the interest of all concerned if the printing and distribution of the volumes were handled by an international publishing house to assure improved service and broader dissemination. Hence, starting with Volume 18, Masters Theses in the Pure and Applied Sciences has been disseminated on a worldwide basis by Plenum Publishing Corporation of New York, and in the same year the coverage was broadened to include Canadian universities. All back issues can also be ordered from Plenum. We have reported in Volume 39 (thesis year 1994) a total of 13,953 thesis titles from 21 Canadian and 159 United States universities. We are sure that this broader base for these titles reported will greatly enhance the value of this impor tant annual reference work. While Volume 39 reports theses submitted in 1994, on occasion, certain uni versities do report theses submitted in previous years but not reported at the time.
