Intelligent Fault Diagnosis and Remaining Useful Life Prediction of Rotating Machinery

Author: Yaguo Lei

Publisher: Butterworth-Heinemann

ISBN: 0128115351

Category: Technology & Engineering

Page: 376

View: 9408

Intelligent Fault Diagnosis and Remaining Useful Life Prediction of Rotating Machinery provides a comprehensive introduction of intelligent fault diagnosis and RUL prediction based on the current achievements of the author's research group. The main contents include multi-domain signal processing and feature extraction, intelligent diagnosis models, clustering algorithms, hybrid intelligent diagnosis strategies, and RUL prediction approaches, etc. This book presents fundamental theories and advanced methods of identifying the occurrence, locations, and degrees of faults, and also includes information on how to predict the RUL of rotating machinery. Besides experimental demonstrations, many application cases are presented and illustrated to test the methods mentioned in the book. This valuable reference provides an essential guide on machinery fault diagnosis that helps readers understand basic concepts and fundamental theories. Academic researchers with mechanical engineering or computer science backgrounds, and engineers or practitioners who are in charge of machine safety, operation, and maintenance will find this book very useful. Provides a detailed background and roadmap of intelligent diagnosis and RUL prediction of rotating machinery, involving fault mechanisms, vibration characteristics, health indicators, and diagnosis and prognostics Presents basic theories, advanced methods, and the latest contributions in the field of intelligent fault diagnosis and RUL prediction Includes numerous application cases, and the methods, algorithms, and models introduced in the book are demonstrated by industrial experiences

Intelligent Fault Diagnosis and Prognosis for Engineering Systems

Author: George Vachtsevanos,Frank L. Lewis,Michael Roemer,Andrew Hess,Biqing Wu

Publisher: Wiley

ISBN: 9780471729990

Category: Technology & Engineering

Page: 456

View: 2043

Expert guidance on theory and practice in condition-based intelligent machine fault diagnosis and failure prognosis Intelligent Fault Diagnosis and Prognosis for Engineering Systems gives a complete presentation of basic essentials of fault diagnosis and failure prognosis, and takes a look at the cutting-edge discipline of intelligent fault diagnosis and failure prognosis technologies for condition-based maintenance. It thoroughly details the interdisciplinary methods required to understand the physics of failure mechanisms in materials, structures, and rotating equipment, and also presents strategies to detect faults or incipient failures and predict the remaining useful life of failing components. Case studies are used throughout the book to illustrate enabling technologies. Intelligent Fault Diagnosis and Prognosis for Engineering Systems offers material in a holistic and integrated approach that addresses the various interdisciplinary components of the field--from electrical, mechanical, industrial, and computer engineering to business management. This invaluably helpful book: * Includes state-of-the-art algorithms, methodologies, and contributions from leading experts, including cost-benefit analysis tools and performance assessment techniques * Covers theory and practice in a way that is rooted in industry research and experience * Presents the only systematic, holistic approach to a strongly interdisciplinary topic

Machinery Prognostics and Prognosis Oriented Maintenance Management

Author: Jihong Yan

Publisher: John Wiley & Sons

ISBN: 1118638727

Category: Technology & Engineering

Page: 375

View: 6356

This book gives a complete presentatin of the basic essentials of machinery prognostics and prognosis oriented maintenance management, and takes a look at the cutting-edge discipline of intelligent failure prognosis technologies for condition-based maintenance. Latest research results and application methods are introduced for signal processing, reliability moelling, deterioration evaluation, residual life prediction and maintenance-optimization as well as applications of these methods.

Diagnostics and Prognostics of Engineering Systems: Methods and Techniques

Methods and Techniques

Author: Kadry, Seifedine

Publisher: IGI Global

ISBN: 146662096X

Category: Technology & Engineering

Page: 461

View: 5634

Industrial Prognostics predicts an industrial system’s lifespan using probability measurements to determine the way a machine operates. Prognostics are essential in determining being able to predict and stop failures before they occur. Therefore the development of dependable prognostic procedures for engineering systems is important to increase the system’s performance and reliability. Diagnostics and Prognostics of Engineering Systems: Methods and Techniques provides widespread coverage and discussions on the methods and techniques of diagnosis and prognosis systems. Including practical examples to display the method’s effectiveness in real-world applications as well as the latest trends and research, this reference source aims to introduce fundamental theory and practice for system diagnosis and prognosis.

From Prognostics and Health Systems Management to Predictive Maintenance 1

Monitoring and Prognostics

Author: Rafael Gouriveau,Kamal Medjaher,Noureddine Zerhouni

Publisher: Wiley-ISTE

ISBN: 9781848219373

Category: Technology & Engineering

Page: 182

View: 3647

This book addresses the steps needed to monitor health assessment systems and the anticipation of their failures: choice and location of sensors, data acquisition and processing, health assessment and prediction of the duration of residual useful life. The digital revolution and mechatronics foreshadowed the advent of the 4.0 industry where equipment has the ability to communicate. The ubiquity of sensors (300,000 sensors in the new generations of aircraft) produces a flood of data requiring us to give meaning to information and leads to the need for efficient processing and a relevant interpretation. The process of traceability and capitalization of data is a key element in the context of the evolution of the maintenance towards predictive strategies.

Mechanical Fault Diagnosis and condition monitoring

Author: R. Collacott

Publisher: Springer Science & Business Media

ISBN: 9400957238

Category: Science

Page: 496

View: 4725

Although the most sophisticated fault diagnosis and condition monitoring systems have their origin in the aerospace and nuclear energy industries, their use is by no means restricted to such areas of 'high technology'. Modern machinery in most industrial plants is now so complex and expensive that mechanics find it increas ingly difficult to detect failure by, for instance, recognising changes in sound 'signatures', and few plants can afford the luxury of regular 'stripping down'. Increasingly, therefore, eady-warning devices are being employed in an effort to prevent catastrophic breakdown. This book provides the first co-ordinated compilation of fault diagnosis and con dition monitoring devices. It proceeds in three logical steps. The eady chapters deal with those conditions which contribute to deterioration and the consequent likely development of faults. The middle part of the book considers the various tech niques of monitoring and discusses the criteria for their selection in different situ ations. The final chapters provide a guide to the interpretation of the information signals deriving from monitoring, relating to reliability science and the mathematics of probability, and thus providing decision data on which management can act.

Bayesian Signal Processing

Classical, Modern, and Particle Filtering Methods

Author: James V. Candy

Publisher: John Wiley & Sons

ISBN: 1119125456

Category: Technology & Engineering

Page: 640

View: 7545

Presents the Bayesian approach to statistical signal processing for a variety of useful model sets This book aims to give readers a unified Bayesian treatment starting from the basics (Bayes’ rule) to the more advanced (Monte Carlo sampling), evolving to the next-generation model-based techniques (sequential Monte Carlo sampling). This next edition incorporates a new chapter on “Sequential Bayesian Detection,” a new section on “Ensemble Kalman Filters” as well as an expansion of Case Studies that detail Bayesian solutions for a variety of applications. These studies illustrate Bayesian approaches to real-world problems incorporating detailed particle filter designs, adaptive particle filters and sequential Bayesian detectors. In addition to these major developments a variety of sections are expanded to ``fill-in-the gaps" of the first edition. Here metrics for particle filter (PF) designs with emphasis on classical ``sanity testing" lead to ensemble techniques as a basic requirement for performance analysis. The expansion of information theoretic metrics and their application to PF designs is fully developed and applied. These expansions of the book have been updated to provide a more cohesive discussion of Bayesian processing with examples and applications enabling the comprehension of alternative approaches to solving estimation/detection problems. The second edition of Bayesian Signal Processing features: “Classical” Kalman filtering for linear, linearized, and nonlinear systems; “modern” unscented and ensemble Kalman filters; and the “next-generation” Bayesian particle filters Sequential Bayesian detection techniques incorporating model-based schemes for a variety of real-world problems Practical Bayesian processor designs including comprehensive methods of performance analysis ranging from simple sanity testing and ensemble techniques to sophisticated information metrics New case studies on adaptive particle filtering and sequential Bayesian detection are covered detailing more Bayesian approaches to applied problem solving MATLAB® notes at the end of each chapter help readers solve complex problems using readily available software commands and point out other software packages available Problem sets to test readers’ knowledge and help them put their new skills into practice Bayesian Signal Processing, Second Edition is written for all students, scientists, and engineers who investigate and apply signal processing to their everyday problems. JAMES V. CANDY, PhD, is Chief Scientist for Engineering, a Distinguished Member of the Technical Staff, founder, and former director of the Center for Advanced Signal & Image Sciences at the Lawrence Livermore National Laboratory. He is also an Adjunct Full Professor at the University of California, Santa Barbara, a Fellow of the IEEE, and a Fellow of the Acoustical Society of America. Dr. Candy has published more than 225 journal articles, book chapters, and technical reports. He is also the author of Signal Processing: Model-Based Approach, Signal Processing: A Modern Approach, and Model-Based Signal Processing (Wiley 2006). Dr. Candy was awarded the IEEE Distinguished Technical Achievement Award for his development of model-based signal processing and the Acoustical Society of America Helmholtz-Rayleigh Interdisciplinary Silver Medal for his contributions to acoustical signal processing and underwater acoustics.

Collaborative Design and Planning for Digital Manufacturing

Author: Lihui Wang,Andrew Yeh Ching Nee

Publisher: Springer Science & Business Media

ISBN: 1848822871

Category: Technology & Engineering

Page: 413

View: 3447

Collaborative design has attracted much attention in the research community in recent years. With increasingly decentralized manufacturing systems and processes, more collaborative approaches and systems are needed to support distributed manufacturing operations. "Collaborative Design and Planning for Digital Manufacturing" presents a focused collection of quality chapters on the state-of-the-art research efforts in the area of collaborative design and planning, as well as their practical applications towards digital manufacturing. "Collaborative Design and Planning for Digital Manufacturing" provides both a broad-based review of the key areas of research in digital manufacturing, and an in-depth treatment of particular methodologies and systems, from collaborative design to distributed planning, monitoring and control. Recent development and innovations in this area provide a pool of focused research efforts, relevant to a wide readership from academic researchers to practicing engineers.

Prognostics and Health Management of Engineering Systems

An Introduction

Author: Nam-Ho Kim,Dawn An,Joo-Ho Choi

Publisher: Springer

ISBN: 3319447424

Category: Science

Page: 347

View: 6449

This book introduces the methods for predicting the future behavior of a system’s health and the remaining useful life to determine an appropriate maintenance schedule. The authors introduce the history, industrial applications, algorithms, and benefits and challenges of PHM (Prognostics and Health Management) to help readers understand this highly interdisciplinary engineering approach that incorporates sensing technologies, physics of failure, machine learning, modern statistics, and reliability engineering. It is ideal for beginners because it introduces various prognostics algorithms and explains their attributes, pros and cons in terms of model definition, model parameter estimation, and ability to handle noise and bias in data, allowing readers to select the appropriate methods for their fields of application.Among the many topics discussed in-depth are:• Prognostics tutorials using least-squares• Bayesian inference and parameter estimation• Physics-based prognostics algorithms including nonlinear least squares, Bayesian method, and particle filter• Data-driven prognostics algorithms including Gaussian process regression and neural network• Comparison of different prognostics algorithms divThe authors also present several applications of prognostics in practical engineering systems, including wear in a revolute joint, fatigue crack growth in a panel, prognostics using accelerated life test data, fatigue damage in bearings, and more. Prognostics tutorials with a Matlab code using simple examples are provided, along with a companion website that presents Matlab programs for different algorithms as well as measurement data. Each chapter contains a comprehensive set of exercise problems, some of which require Matlab programs, making this an ideal book for graduate students in mechanical, civil, aerospace, electrical, and industrial engineering and engineering mechanics, as well as researchers and maintenance engineers in the above fields.

Data Mining and Analysis in the Engineering Field

Author: Bhatnagar, Vishal

Publisher: IGI Global

ISBN: 1466660872

Category: Computers

Page: 405

View: 725

Particularly in the fields of software engineering, virtual reality, and computer science, data mining techniques play a critical role in the success of a variety of projects and endeavors. Understanding the available tools and emerging trends in this field is an important consideration for any organization. Data Mining and Analysis in the Engineering Field explores current research in data mining, including the important trends and patterns and their impact in fields such as software engineering. With a focus on modern techniques as well as past experiences, this vital reference work will be of greatest use to engineers, researchers, and practitioners in scientific-, engineering-, and business-related fields.

Pelton Turbines

Author: Zhengji Zhang

Publisher: Springer

ISBN: 3319319094

Category: Technology & Engineering

Page: 311

View: 4753

This book concerns the theoretical foundations of hydro mechanics of Pelton turbines from a viewpoint of engineering. For reference purposes all relevant flow processes and hydraulic aspects in a Pelton turbine have been analyzed completely and systematically. The analyses especially include the quantification of all possible losses existing in the Pelton turbine and the indication of most available potential for further enhancing the system efficiency. As a guideline the book therefore supports further developments of Pelton turbines with regard to their hydraulic designs and optimizations. It is thus suitable for the development and design engineers as well as those working in the field of turbo machinery. Many laws described in the book can also be directly used to simplify aspects of computational fluid dynamics (CFD) or to develop new computational methods. The well-executed examples help better understanding the related flow mechanics.

Solid State Lighting Reliability Part 2

Components to Systems

Author: Willem Dirk van Driel,Xuejun Fan,Guo Qi Zhang

Publisher: Springer

ISBN: 3319581759

Category: Technology & Engineering

Page: 606

View: 3379

In the past four years we have witnessed rapid development in technology and significant market penetration in many applications for LED systems. New processes and new materials have been introduced; new standards and new testing methods have been developed; new driver, control and sensing technologies have been integrated; and new and unknown failure modes have also been presented. In this book, Solid State Lighting Reliability Part 2, we invited the experts from industry and academia to present the latest developments and findings in the LED system reliability arena. Topics in this book cover the early failures and critical steps in LED manufacturing; advances in reliability testing and standards; quality of colour and colour stability; degradation of optical materials and the associated chromaticity maintenance; characterization of thermal interfaces; LED solder joint testing and prediction; common failure modes in LED drivers; root causes for lumen depreciation; corrosion sensitivity of LED packages; reliability management for automotive LEDs, and lightning effects on LEDs. This book is a continuation of Solid State Lighting Reliability: Components to Systems (published in 2013), which covers reliability aspects ranging from the LED to the total luminaire or system of luminaires. Together, these two books are a full set of reference books for Solid State Lighting reliability from the performance of the (sub-) components to the total system, regardless its complexity.

Prognostics and Health Management of Electronics

Author: Michael G. Pecht

Publisher: John Wiley & Sons

ISBN: 0470385839

Category: Technology & Engineering

Page: 300

View: 7736

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.

Handbook of Reliability, Availability, Maintainability and Safety in Engineering Design

Author: Rudolph Frederick Stapelberg

Publisher: Springer Science & Business Media

ISBN: 1848001754

Category: Technology & Engineering

Page: 827

View: 9205

This handbook studies the combination of various methods of designing for reliability, availability, maintainability and safety, as well as the latest techniques in probability and possibility modeling, mathematical algorithmic modeling, evolutionary algorithmic modeling, symbolic logic modeling, artificial intelligence modeling and object-oriented computer modeling.

Predictive Modular Neural Networks

Applications to Time Series

Author: Vassilios Petridis,Athanasios Kehagias

Publisher: Springer Science & Business Media

ISBN: 1461555558

Category: Science

Page: 314

View: 795

The subject of this book is predictive modular neural networks and their ap plication to time series problems: classification, prediction and identification. The intended audience is researchers and graduate students in the fields of neural networks, computer science, statistical pattern recognition, statistics, control theory and econometrics. Biologists, neurophysiologists and medical engineers may also find this book interesting. In the last decade the neural networks community has shown intense interest in both modular methods and time series problems. Similar interest has been expressed for many years in other fields as well, most notably in statistics, control theory, econometrics etc. There is a considerable overlap (not always recognized) of ideas and methods between these fields. Modular neural networks come by many other names, for instance multiple models, local models and mixtures of experts. The basic idea is to independently develop several "subnetworks" (modules), which may perform the same or re lated tasks, and then use an "appropriate" method for combining the outputs of the subnetworks. Some of the expected advantages of this approach (when compared with the use of "lumped" or "monolithic" networks) are: superior performance, reduced development time and greater flexibility. For instance, if a module is removed from the network and replaced by a new module (which may perform the same task more efficiently), it should not be necessary to retrain the aggregate network.

Signal Analysis and Prediction

Author: Ales Prochazka,N.G. Kingsbury,P.J.W. Payner,J. Uhlir

Publisher: Springer Science & Business Media

ISBN: 1461217687

Category: Technology & Engineering

Page: 502

View: 461

Methods of signal analysis represent a broad research topic with applications in many disciplines, including engineering, technology, biomedicine, seismography, eco nometrics, and many others based upon the processing of observed variables. Even though these applications are widely different, the mathematical background be hind them is similar and includes the use of the discrete Fourier transform and z-transform for signal analysis, and both linear and non-linear methods for signal identification, modelling, prediction, segmentation, and classification. These meth ods are in many cases closely related to optimization problems, statistical methods, and artificial neural networks. This book incorporates a collection of research papers based upon selected contri butions presented at the First European Conference on Signal Analysis and Predic tion (ECSAP-97) in Prague, Czech Republic, held June 24-27, 1997 at the Strahov Monastery. Even though the Conference was intended as a European Conference, at first initiated by the European Association for Signal Processing (EURASIP), it was very gratifying that it also drew significant support from other important scientific societies, including the lEE, Signal Processing Society of IEEE, and the Acoustical Society of America. The organizing committee was pleased that the re sponse from the academic community to participate at this Conference was very large; 128 summaries written by 242 authors from 36 countries were received. In addition, the Conference qualified under the Continuing Professional Development Scheme to provide PD units for participants and contributors.

Computer Vision

Algorithms and Applications

Author: Richard Szeliski

Publisher: Springer Science & Business Media

ISBN: 9781848829350

Category: Computers

Page: 812

View: 4666

Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos. More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are also analyzed using statistical models and solved using rigorous engineering techniques. Topics and features: structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses; presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects; provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, and Bayesian estimation theory; suggests additional reading at the end of each chapter, including the latest research in each sub-field, in addition to a full Bibliography at the end of the book; supplies supplementary course material for students at the associated website, Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.

Data-Driven Remaining Useful Life Prognosis Techniques

Stochastic Models, Methods and Applications

Author: Xiao-Sheng Si,Zheng-Xin Zhang,Chang-Hua Hu

Publisher: Springer

ISBN: 3662540304

Category: Technology & Engineering

Page: 430

View: 7354

This book introduces data-driven remaining useful life prognosis techniques, and shows how to utilize the condition monitoring data to predict the remaining useful life of stochastic degrading systems and to schedule maintenance and logistics plans. It is also the first book that describes the basic data-driven remaining useful life prognosis theory systematically and in detail. The emphasis of the book is on the stochastic models, methods and applications employed in remaining useful life prognosis. It includes a wealth of degradation monitoring experiment data, practical prognosis methods for remaining useful life in various cases, and a series of applications incorporated into prognostic information in decision-making, such as maintenance-related decisions and ordering spare parts. It also highlights the latest advances in data-driven remaining useful life prognosis techniques, especially in the contexts of adaptive prognosis for linear stochastic degrading systems, nonlinear degradation modeling based prognosis, residual storage life prognosis, and prognostic information-based decision-making.