Fault Detection With Bayesian Network

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Bayesian Networks In Fault Diagnosis: Practice And Application

Author : Baoping Cai
Publisher : World Scientific
ISBN 13 : 9813271507
Total Pages : 418 pages
Book Rating : 4.8/5 (132 download)

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Book Synopsis Bayesian Networks In Fault Diagnosis: Practice And Application by : Baoping Cai

Download or read book Bayesian Networks In Fault Diagnosis: Practice And Application written by Baoping Cai and published by World Scientific. This book was released on 2018-08-24 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fault diagnosis is useful for technicians to detect, isolate, identify faults, and troubleshoot. Bayesian network (BN) is a probabilistic graphical model that effectively deals with various uncertainty problems. This model is increasingly utilized in fault diagnosis.This unique compendium presents bibliographical review on the use of BNs in fault diagnosis in the last decades with focus on engineering systems. Subsequently, eleven important issues in BN-based fault diagnosis methodology, such as BN structure modeling, BN parameter modeling, BN inference, fault identification, validation, and verification are discussed in various cases.Researchers, professionals, academics and graduate students will better understand the theory and application, and benefit those who are keen to develop real BN-based fault diagnosis system.

Bayesian Networks

Author : Olivier Pourret
Publisher : John Wiley & Sons
ISBN 13 : 9780470994542
Total Pages : 446 pages
Book Rating : 4.9/5 (945 download)

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Book Synopsis Bayesian Networks by : Olivier Pourret

Download or read book Bayesian Networks written by Olivier Pourret and published by John Wiley & Sons. This book was released on 2008-04-30 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Networks, the result of the convergence of artificial intelligence with statistics, are growing in popularity. Their versatility and modelling power is now employed across a variety of fields for the purposes of analysis, simulation, prediction and diagnosis. This book provides a general introduction to Bayesian networks, defining and illustrating the basic concepts with pedagogical examples and twenty real-life case studies drawn from a range of fields including medicine, computing, natural sciences and engineering. Designed to help analysts, engineers, scientists and professionals taking part in complex decision processes to successfully implement Bayesian networks, this book equips readers with proven methods to generate, calibrate, evaluate and validate Bayesian networks. The book: Provides the tools to overcome common practical challenges such as the treatment of missing input data, interaction with experts and decision makers, determination of the optimal granularity and size of the model. Highlights the strengths of Bayesian networks whilst also presenting a discussion of their limitations. Compares Bayesian networks with other modelling techniques such as neural networks, fuzzy logic and fault trees. Describes, for ease of comparison, the main features of the major Bayesian network software packages: Netica, Hugin, Elvira and Discoverer, from the point of view of the user. Offers a historical perspective on the subject and analyses future directions for research. Written by leading experts with practical experience of applying Bayesian networks in finance, banking, medicine, robotics, civil engineering, geology, geography, genetics, forensic science, ecology, and industry, the book has much to offer both practitioners and researchers involved in statistical analysis or modelling in any of these fields.

Data-Driven Fault Detection and Reasoning for Industrial Monitoring

Author : Jing Wang
Publisher : Springer Nature
ISBN 13 : 9811680442
Total Pages : 277 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Data-Driven Fault Detection and Reasoning for Industrial Monitoring by : Jing Wang

Download or read book Data-Driven Fault Detection and Reasoning for Industrial Monitoring written by Jing Wang and published by Springer Nature. This book was released on 2022-01-03 with total page 277 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.

Bayesian Networks for Reliability Engineering

Author : Baoping Cai
Publisher : Springer
ISBN 13 : 9811365164
Total Pages : 259 pages
Book Rating : 4.8/5 (113 download)

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Book Synopsis Bayesian Networks for Reliability Engineering by : Baoping Cai

Download or read book Bayesian Networks for Reliability Engineering written by Baoping Cai and published by Springer. This book was released on 2019-02-28 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a bibliographical review of the use of Bayesian networks in reliability over the last decade. Bayesian network (BN) is considered to be one of the most powerful models in probabilistic knowledge representation and inference, and it is increasingly used in the field of reliability. After focusing on the engineering systems, the book subsequently discusses twelve important issues in the BN-based reliability methodologies, such as BN structure modeling, BN parameter modeling, BN inference, validation, and verification. As such, it is a valuable resource for researchers and practitioners in the field of reliability engineering.

Fault Detection and Diagnosis in Industrial Systems

Author : L.H. Chiang
Publisher : Springer Science & Business Media
ISBN 13 : 1447103475
Total Pages : 281 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Fault Detection and Diagnosis in Industrial Systems by : L.H. Chiang

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.

Fault Detection, Diagnosis and Prognosis

Author : Fausto Pedro García Márquez
Publisher : BoD – Books on Demand
ISBN 13 : 1789842131
Total Pages : 177 pages
Book Rating : 4.7/5 (898 download)

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Book Synopsis Fault Detection, Diagnosis and Prognosis by : Fausto Pedro García Márquez

Download or read book Fault Detection, Diagnosis and Prognosis written by Fausto Pedro García Márquez and published by BoD – Books on Demand. This book was released on 2020-02-05 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the main concepts, state of the art, advances, and case studies of fault detection, diagnosis, and prognosis. This topic is a critical variable in industry to reach and maintain competitiveness. Therefore, proper management of the corrective, predictive, and preventive politics in any industry is required. This book complements other subdisciplines such as economics, finance, marketing, decision and risk analysis, engineering, etc. The book presents real case studies in multiple disciplines. It considers the main topics using prognostic and subdiscipline techniques. It is essential to link these topics with the areas of finance, scheduling, resources, downtime, etc. to increase productivity, profitability, maintainability, reliability, safety, and availability, and reduce costs and downtime. Advances in mathematics, modeling, computational techniques, dynamic analysis, etc. are employed analytically. Computational techniques, dynamic analysis, probabilistic methods, and mathematical optimization techniques are expertly blended to support the analysis of prognostic problems with defined constraints and requirements. The book is intended for graduate students and professionals in industrial engineering, business administration, industrial organization, operations management, applied microeconomics, and the decisions sciences, either studying maintenance or needing to solve large, specific, and complex maintenance management problems as part of their jobs. The work will also be of interest to researches from academia.

Applied Smoothing Techniques for Data Analysis

Author : Adrian W. Bowman
Publisher : OUP Oxford
ISBN 13 : 0191545694
Total Pages : 205 pages
Book Rating : 4.1/5 (915 download)

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Book Synopsis Applied Smoothing Techniques for Data Analysis by : Adrian W. Bowman

Download or read book Applied Smoothing Techniques for Data Analysis written by Adrian W. Bowman and published by OUP Oxford. This book was released on 1997-08-14 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book describes the use of smoothing techniques in statistics, including both density estimation and nonparametric regression. Considerable advances in research in this area have been made in recent years. The aim of this text is to describe a variety of ways in which these methods can be applied to practical problems in statistics. The role of smoothing techniques in exploring data graphically is emphasised, but the use of nonparametric curves in drawing conclusions from data, as an extension of more standard parametric models, is also a major focus of the book. Examples are drawn from a wide range of applications. The book is intended for those who seek an introduction to the area, with an emphasis on applications rather than on detailed theory. It is therefore expected that the book will benefit those attending courses at an advanced undergraduate, or postgraduate, level, as well as researchers, both from statistics and from other disciplines, who wish to learn about and apply these techniques in practical data analysis. The text makes extensive reference to S-Plus, as a computing environment in which examples can be explored. S-Plus functions and example scripts are provided to implement many of the techniques described. These parts are, however, clearly separate from the main body of text, and can therefore easily be skipped by readers not interested in S-Plus.

Advancements in Smart City and Intelligent Building

Author : Qiansheng Fang
Publisher : Springer
ISBN 13 : 9811367337
Total Pages : 624 pages
Book Rating : 4.8/5 (113 download)

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Book Synopsis Advancements in Smart City and Intelligent Building by : Qiansheng Fang

Download or read book Advancements in Smart City and Intelligent Building written by Qiansheng Fang and published by Springer. This book was released on 2019-04-03 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book entitled “Advancements in Smart City and Intelligent Building” is the Proceedings of the International Conference on Smart City and Intelligent Building (ICSCIB 2018) held in Hefei, China, September 15-16, 2018. It contains 58 papers in total categorized into 8 different tracks, on Building Energy Efficiency, Construction Robot and Automation, Intelligent Community and Urban Safety, Intelligentialization of Heating Ventilation Air Conditioning System, Information Technology and Intelligent Transportation Systems, New Generation Intelligent Building Platform Techniques, Smart Home and Utility, and Smart Underground Space, which cover a wide range areas of smart cities and intelligent buildings. ICSCIB2018 provided an international forum for professionals, academics, and researchers to present the latest developments from interdisciplinary theoretical studies, computational algorithm developments and engineering applications in smart cities and smart buildings. This academic event featured many opportunities to network with colleagues from around the world in a wonderful environment. Its program covered invitation and presentations from scientists, researchers, and practitioners who have been working in the related areas to establish platforms for collaborative research projects in these fields. The conference invited leaders from industry and academia to exchange and share their experiences, present research results, explore collaborations and to spark new ideas, with the aim of developing new projects and exploiting new technology in these fields, and bridge theoretical studies and emerging applications in various science and engineering branches. This book addresses the recent development and achievement in the field of smart city and intelligent building. It is primarily intended for researchers and students for undergraduate and postgraduate programs in the background of multiple disciplines including computer science, information systems, information technology, automatic control and automation, electrical and electronic engineering, and telecommunications who wish to develop and share their ideas, knowledge and new findings in smart city and intelligent building.

Risk Assessment and Decision Analysis with Bayesian Networks

Author : Norman Fenton
Publisher : CRC Press
ISBN 13 : 1351978977
Total Pages : 661 pages
Book Rating : 4.3/5 (519 download)

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Book Synopsis Risk Assessment and Decision Analysis with Bayesian Networks by : Norman Fenton

Download or read book Risk Assessment and Decision Analysis with Bayesian Networks written by Norman Fenton and published by CRC Press. This book was released on 2018-09-03 with total page 661 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the first edition of this book published, Bayesian networks have become even more important for applications in a vast array of fields. This second edition includes new material on influence diagrams, learning from data, value of information, cybersecurity, debunking bad statistics, and much more. Focusing on practical real-world problem-solving and model building, as opposed to algorithms and theory, it explains how to incorporate knowledge with data to develop and use (Bayesian) causal models of risk that provide more powerful insights and better decision making than is possible from purely data-driven solutions. Features Provides all tools necessary to build and run realistic Bayesian network models Supplies extensive example models based on real risk assessment problems in a wide range of application domains provided; for example, finance, safety, systems reliability, law, forensics, cybersecurity and more Introduces all necessary mathematics, probability, and statistics as needed Establishes the basics of probability, risk, and building and using Bayesian network models, before going into the detailed applications A dedicated website contains exercises and worked solutions for all chapters along with numerous other resources. The AgenaRisk software contains a model library with executable versions of all of the models in the book. Lecture slides are freely available to accredited academic teachers adopting the book on their course.

2021 IEEE 19th International Conference on Industrial Informatics (INDIN)

Author : IEEE Staff
Publisher :
ISBN 13 : 9781728143965
Total Pages : pages
Book Rating : 4.1/5 (439 download)

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Book Synopsis 2021 IEEE 19th International Conference on Industrial Informatics (INDIN) by : IEEE Staff

Download or read book 2021 IEEE 19th International Conference on Industrial Informatics (INDIN) written by IEEE Staff and published by . This book was released on 2021-07-21 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: INDIN focuses on recent developments, deployments, technology trends, and research results in Industrial Informatics related fields from both industry and academia

Signal Processing for Fault Detection and Diagnosis in Electric Machines and Systems

Author : Mohamed Benbouzid
Publisher : IET
ISBN 13 : 1785619578
Total Pages : 283 pages
Book Rating : 4.7/5 (856 download)

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Book Synopsis Signal Processing for Fault Detection and Diagnosis in Electric Machines and Systems by : Mohamed Benbouzid

Download or read book Signal Processing for Fault Detection and Diagnosis in Electric Machines and Systems written by Mohamed Benbouzid and published by IET. This book was released on 2020-12-09 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains 5 chapters that discusses the following topics: Parametric signal processing approach; The signal demodulation techniques; Kullback-Leibler divergence for incipient fault diagnosis; Higher-order spectra and Fault detection and diagnosis based on principal component analysis.

Bayesian Methods for Hackers

Author : Cameron Davidson-Pilon
Publisher : Addison-Wesley Professional
ISBN 13 : 0133902927
Total Pages : 551 pages
Book Rating : 4.1/5 (339 download)

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Book Synopsis Bayesian Methods for Hackers by : Cameron Davidson-Pilon

Download or read book Bayesian Methods for Hackers written by Cameron Davidson-Pilon and published by Addison-Wesley Professional. This book was released on 2015-09-30 with total page 551 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master Bayesian Inference through Practical Examples and Computation–Without Advanced Mathematical Analysis Bayesian methods of inference are deeply natural and extremely powerful. However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice–freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You’ll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you’ve mastered these techniques, you’ll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes • Learning the Bayesian “state of mind” and its practical implications • Understanding how computers perform Bayesian inference • Using the PyMC Python library to program Bayesian analyses • Building and debugging models with PyMC • Testing your model’s “goodness of fit” • Opening the “black box” of the Markov Chain Monte Carlo algorithm to see how and why it works • Leveraging the power of the “Law of Large Numbers” • Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning • Using loss functions to measure an estimate’s weaknesses based on your goals and desired outcomes • Selecting appropriate priors and understanding how their influence changes with dataset size • Overcoming the “exploration versus exploitation” dilemma: deciding when “pretty good” is good enough • Using Bayesian inference to improve A/B testing • Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.

Fault-Diagnosis Systems

Author : Rolf Isermann
Publisher : Springer Science & Business Media
ISBN 13 : 3540303685
Total Pages : 478 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Fault-Diagnosis Systems by : Rolf Isermann

Download or read book Fault-Diagnosis Systems written by Rolf Isermann and published by Springer Science & Business Media. This book was released on 2006-01-16 with total page 478 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.

Neural Network Models of Cognition

Author : J.W. Donahoe
Publisher : Elsevier
ISBN 13 : 0080537367
Total Pages : 601 pages
Book Rating : 4.0/5 (85 download)

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Book Synopsis Neural Network Models of Cognition by : J.W. Donahoe

Download or read book Neural Network Models of Cognition written by J.W. Donahoe and published by Elsevier. This book was released on 1997-09-26 with total page 601 pages. Available in PDF, EPUB and Kindle. Book excerpt: This internationally authored volume presents major findings, concepts, and methods of behavioral neuroscience coordinated with their simulation via neural networks. A central theme is that biobehaviorally constrained simulations provide a rigorous means to explore the implications of relatively simple processes for the understanding of cognition (complex behavior). Neural networks are held to serve the same function for behavioral neuroscience as population genetics for evolutionary science. The volume is divided into six sections, each of which includes both experimental and simulation research: (1) neurodevelopment and genetic algorithms, (2) synaptic plasticity (LTP), (3) sensory/hippocampal systems, (4) motor systems, (5) plasticity in large neural systems (reinforcement learning), and (6) neural imaging and language. The volume also includes an integrated reference section and a comprehensive index.

Capturing Connectivity and Causality in Complex Industrial Processes

Author : Fan Yang
Publisher : Springer Science & Business Media
ISBN 13 : 3319053809
Total Pages : 99 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Capturing Connectivity and Causality in Complex Industrial Processes by : Fan Yang

Download or read book Capturing Connectivity and Causality in Complex Industrial Processes written by Fan Yang and published by Springer Science & Business Media. This book was released on 2014-04-01 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: This brief reviews concepts of inter-relationship in modern industrial processes, biological and social systems. Specifically ideas of connectivity and causality within and between elements of a complex system are treated; these ideas are of great importance in analysing and influencing mechanisms, structural properties and their dynamic behaviour, especially for fault diagnosis and hazard analysis. Fault detection and isolation for industrial processes being concerned with root causes and fault propagation, the brief shows that, process connectivity and causality information can be captured in two ways: · from process knowledge: structural modeling based on first-principles structural models can be merged with adjacency/reachability matrices or topology models obtained from process flow-sheets described in standard formats; and · from process data: cross-correlation analysis, Granger causality and its extensions, frequency domain methods, information-theoretical methods, and Bayesian networks can be used to identify pair-wise relationships and network topology. These methods rely on the notion of information fusion whereby process operating data is combined with qualitative process knowledge, to give a holistic picture of the system.

Computational Web Intelligence

Author : Yan-Qing Zhang
Publisher : World Scientific
ISBN 13 : 9812562435
Total Pages : 584 pages
Book Rating : 4.8/5 (125 download)

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Book Synopsis Computational Web Intelligence by : Yan-Qing Zhang

Download or read book Computational Web Intelligence written by Yan-Qing Zhang and published by World Scientific. This book was released on 2004 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: This review volume introduces the novel intelligent Web theory calledcomputational Web intelligence (CWI) based on computationalintelligence (CI) and Web technology (WT). It takes an in-depth lookat hybrid Web intelligence (HWI), which is based on artificialbiological and computational intelligence with Web technology and isused to build hybrid intelligent Web systems that serve wired andwireless users more efficiently.

Bayesian Networks

Author : Marco Scutari
Publisher : CRC Press
ISBN 13 : 1000410382
Total Pages : 275 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Bayesian Networks by : Marco Scutari

Download or read book Bayesian Networks written by Marco Scutari and published by CRC Press. This book was released on 2021-07-28 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explains the material step-by-step starting from meaningful examples Steps detailed with R code in the spirit of reproducible research Real world data analyses from a Science paper reproduced and explained in detail Examples span a variety of fields across social and life sciences Overview of available software in and outside R