› › Fault Diagnosis Of Gear Trains Using A New Technique For Condition Monitoring Of Rotating Machinery

Rotating Machinery, Structural Health Monitoring, Shock and Vibration, Volume 5

Author : Tom Proulx

Publisher : Springer

Page : 554 pages

File Size : 24,55 MB

Release : 2011-03-22

Category : Technology & Engineering

ISBN : 9781441994271

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Book Description

Rotating Machinery, Structural Health Monitoring, Shock and Vibration, Volume 5 Proceedings of the 29th IMAC, A Conference and Exposition on Structural Dynamics, 2011, the fifth volume of six from the Conference, brings together 35 contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Rotating Machinery, Structural Health Monitoring, as well as Shock and Vibration, along with other structural engineering areas.



Advances in Condition Monitoring of Machinery in Non-Stationary Operations

Author : Giorgio Dalpiaz

Publisher : Springer Science & Business Media

Page : 678 pages

File Size : 32,24 MB

Release : 2013-10-05

Category : Technology & Engineering

ISBN : 3642393489

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Book Description

This book presents the processing of the third edition of the Condition Monitoring of Machinery in Non-Stationary Operations (CMMNO13), which was held in Ferrara, Italy. This yearly event merges an international community of researchers who met – in 2011 in Wroclaw (Poland) and in 2012 in Hammamet (Tunisia) – to discuss issues of diagnostics of rotating machines operating in complex motion and/or load conditions. The growing interest of the industrial world on the topics covered by the CMMNO13 involves the fields of packaging, automotive, agricultural, mining, processing and wind machines in addition to that of the systems for data acquisition. The participation of speakers and visitors from industry makes the event an opportunity for immediate assessment of the potential applications of advanced methodologies for the signal analysis. Signals acquired from machines often contain contributions from several different components as well as noise. Therefore, the major challenge of condition monitoring is to point out the signal content that is related to the state of the monitored component particularly in non-stationary conditions.



Condition Monitoring with Vibration Signals

Author : Hosameldin Ahmed

Publisher : John Wiley & Sons

Page : 456 pages

File Size : 32,33 MB

Release : 2020-01-07

Category : Technology & Engineering

ISBN : 1119544629

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Book Description

Provides an extensive, up-to-date treatment of techniques used for machine condition monitoring Clear and concise throughout, this accessible book is the first to be wholly devoted to the field of condition monitoring for rotating machines using vibration signals. It covers various feature extraction, feature selection, and classification methods as well as their applications to machine vibration datasets. It also presents new methods including machine learning and compressive sampling, which help to improve safety, reliability, and performance. Condition Monitoring with Vibration Signals: Compressive Sampling and Learning Algorithms for Rotating Machines starts by introducing readers to Vibration Analysis Techniques and Machine Condition Monitoring (MCM). It then offers readers sections covering: Rotating Machine Condition Monitoring using Learning Algorithms; Classification Algorithms; and New Fault Diagnosis Frameworks designed for MCM. Readers will learn signal processing in the time-frequency domain, methods for linear subspace learning, and the basic principles of the learning method Artificial Neural Network (ANN). They will also discover recent trends of deep learning in the field of machine condition monitoring, new feature learning frameworks based on compressive sampling, subspace learning techniques for machine condition monitoring, and much more. Covers the fundamental as well as the state-of-the-art approaches to machine condition monitoringguiding readers from the basics of rotating machines to the generation of knowledge using vibration signals Provides new methods, including machine learning and compressive sampling, which offer significant improvements in accuracy with reduced computational costs Features learning algorithms that can be used for fault diagnosis and prognosis Includes previously and recently developed dimensionality reduction techniques and classification algorithms Condition Monitoring with Vibration Signals: Compressive Sampling and Learning Algorithms for Rotating Machines is an excellent book for research students, postgraduate students, industrial practitioners, and researchers.



Vibration-based Condition Monitoring

Author : Robert Bond Randall

Publisher : John Wiley & Sons

Page : 409 pages

File Size : 17,18 MB

Release : 2011-03-25

Category : Technology & Engineering

ISBN : 0470977582

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Book Description

"Without doubt the best modern and up-to-date text on the topic, wirtten by one of the world leading experts in the field. Should be on the desk of any practitioner or researcher involved in the field of Machine Condition Monitoring" Simon Braun, Israel Institute of Technology Explaining complex ideas in an easy to understand way, Vibration-based Condition Monitoring provides a comprehensive survey of the application of vibration analysis to the condition monitoring of machines. Reflecting the natural progression of these systems by presenting the fundamental material and then moving onto detection, diagnosis and prognosis, Randall presents classic and state-of-the-art research results that cover vibration signals from rotating and reciprocating machines; basic signal processing techniques; fault detection; diagnostic techniques, and prognostics. Developed out of notes for a course in machine condition monitoring given by Robert Bond Randall over ten years at the University of New South Wales, Vibration-based Condition Monitoring: Industrial, Aerospace and Automotive Applications is essential reading for graduate and postgraduate students/ researchers in machine condition monitoring and diagnostics as well as condition monitoring practitioners and machine manufacturers who want to include a machine monitoring service with their product. Includes a number of exercises for each chapter, many based on Matlab, to illustrate basic points as well as to facilitate the use of the book as a textbook for courses in the topic. Accompanied by a website www.wiley.com/go/randall housing exercises along with data sets and implementation code in Matlab for some of the methods as well as other pedagogical aids. Authored by an internationally recognised authority in the area of condition monitoring.







Machinery Condition Monitoring

Author : Amiya Ranjan Mohanty

Publisher : CRC Press

Page : 282 pages

File Size : 45,91 MB

Release : 2014-12-22

Category : Science

ISBN : 1466593059

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Book Description

Find the Fault in the Machines Drawing on the author’s more than two decades of experience with machinery condition monitoring and consulting for industries in India and abroad, Machinery Condition Monitoring: Principles and Practices introduces the practicing engineer to the techniques used to effectively detect and diagnose faults in machines. Providing the working principle behind the instruments, the important elements of machines as well as the technique to understand their conditions, this text presents every available method of machine fault detection occurring in machines in general, and rotating machines in particular. A Single-Source Solution for Practice Machinery Conditioning Monitoring Since vibration is one of the most widely used fault detection techniques, the book offers an assessment of vibration analysis and rotor-dynamics. It also covers the techniques of wear and debris analysis, and motor current signature analysis to detect faults in rotating mechanical systems as well as thermography, the nondestructive test NDT techniques (ultrasonics and radiography), and additional methods. The author includes relevant case studies from his own experience spanning over the past 20 years, and detailing practical fault diagnosis exercises involving various industries ranging from steel and cement plants to gas turbine driven frigates. While mathematics is kept to a minimum, he also provides worked examples and MATLAB® codes. This book contains 15 chapters and provides topical information that includes: A brief overview of the maintenance techniques Fundamentals of machinery vibration and rotor dynamics Basics of signal processing and instrumentation, which are essential for monitoring the health of machines Requirements of vibration monitoring and noise monitoring Electrical machinery faults Thermography for condition monitoring Techniques of wear debris analysis and some of the nondestructive test (NDT) techniques for condition monitoring like ultrasonics and radiography Machine tool condition monitoring Engineering failure analysis Several case studies, mostly on failure analysis, from the author’s consulting experience Machinery Condition Monitoring: Principles and Practices presents the latest techniques in fault diagnosis and prognosis, provides many real-life practical examples, and empowers you to diagnose the faults in machines all on your own.





Mechanical Fault Diagnosis and condition monitoring

Author : R. Collacott

Publisher : Springer Science & Business Media

Page : 505 pages

File Size : 11,54 MB

Release : 2012-12-06

Category : Science

ISBN : 9400957238

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Book Description

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.



Introduction of Intelligent Machine Fault Diagnosis and Prognosis

Author : O-Suk Yang

Publisher :

Page : 0 pages

File Size : 20,45 MB

Release : 2009

Category : Automatic test equipment

ISBN : 9781606922637

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Book Description

Condition monitoring, fault diagnosis and prognosis of machinery have received considerable attention in recent years and they are increasingly becoming important in industry because of the need to increase reliability and decrease possible loss of production due to the fault of equipments. Early fault detection, diagnosis and prognosis can increase equipment availability and performance, reduce consequential damage, prolong machine life and reduce spare parts inventories and break down maintenance. With the development of the artificial intelligence techniques, many intelligent systems have been employed to assist the maintenance management task to correctly interpret the fault data. The book is very easy to study; even if the reader is a beginner in the fault diagnosis area, they do not need special prerequisite knowledge to understand the contents of this book. The book is equipped with software under MATLAB and offers many examples which are related to fault diagnosis processes. It will be very useful to readers who want to study feature-based intelligent machine fault diagnosis and prognosis techniques. The book is dedicated to graduate students of mechanical and electrical engineering, computer science and for practising engineers.