Condition Monitoring And Nonlinear Frequency Analysis Based Fault Detection Of Mechanical Vibration Systems
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| Author | : Hogir Rafiq |
| Publisher | : Springer Nature |
| Total Pages | : 206 |
| Release | : 2023-08-26 |
| Genre | : Technology & Engineering |
| ISBN | : 365842480X |
Hogir Rafiq proposes two approaches, the signal processing based condition monitoring approaches with applications to fault detection in gear systems, and application of deep mathematical and system theoretical methods to fault detection. The author develops the multivariate empirical mode decomposition (MEMD) algorithm to enhance the capability of extracting fault features and theoretical problems in nonlinear frequency analysis methods, respectively. The effectiveness has been demonstrated by an experimental study on a wind turbine gearbox test rig.
| Author | : Michèle Basseville |
| Publisher | : |
| Total Pages | : 568 |
| Release | : 1993 |
| Genre | : Mathematics |
| ISBN | : |
Presents mathematical tools and techniques for solving change detection problems in wide domains like signal processing, controlled systems and monitoring. The book covers a wide class of stochastic processes, including scalar independent observations and multidimensional dependent ARMA.
| Author | : Robert Bond Randall |
| Publisher | : John Wiley & Sons |
| Total Pages | : 409 |
| Release | : 2011-03-25 |
| Genre | : Technology & Engineering |
| ISBN | : 0470977582 |
"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.
| Author | : Tshilidzi Marwala |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 247 |
| Release | : 2012-01-25 |
| Genre | : Technology & Engineering |
| ISBN | : 1447123808 |
Condition Monitoring Using Computational Intelligence Methods promotes the various approaches gathered under the umbrella of computational intelligence to show how condition monitoring can be used to avoid equipment failures and lengthen its useful life, minimize downtime and reduce maintenance costs. The text introduces various signal-processing and pre-processing techniques, wavelets and principal component analysis, for example, together with their uses in condition monitoring and details the development of effective feature extraction techniques classified into frequency-, time-frequency- and time-domain analysis. Data generated by these techniques can then be used for condition classification employing tools such as: • fuzzy systems; rough and neuro-rough sets; neural and Bayesian networks;hidden Markov and Gaussian mixture models; and support vector machines.
| Author | : Hasmat Malik |
| Publisher | : Springer Nature |
| Total Pages | : 499 |
| Release | : 2020-01-17 |
| Genre | : Technology & Engineering |
| ISBN | : 9811515328 |
This book addresses a range of complex issues associated with condition monitoring (CM), fault diagnosis and detection (FDD) in smart buildings, wide area monitoring (WAM), wind energy conversion systems (WECSs), photovoltaic (PV) systems, structures, electrical systems, mechanical systems, smart grids, etc. The book’s goal is to develop and combine all advanced nonintrusive CMFD approaches on a common platform. To do so, it explores the main components of various systems used for CMFD purposes. The content is divided into three main parts, the first of which provides a brief introduction, before focusing on the state of the art and major research gaps in the area of CMFD. The second part covers the step-by-step implementation of novel soft computing applications in CMFD for electrical and mechanical systems. In the third and final part, the simulation codes for each chapter are included in an extensive appendix to support newcomers to the field.
| Author | : Hosameldin Ahmed |
| Publisher | : John Wiley & Sons |
| Total Pages | : 456 |
| Release | : 2020-01-07 |
| Genre | : Technology & Engineering |
| ISBN | : 1119544629 |
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.
| Author | : Alkiviadis S. Paipetis |
| Publisher | : CRC Press |
| Total Pages | : 526 |
| Release | : 2012-01-26 |
| Genre | : Technology & Engineering |
| ISBN | : 0415621313 |
Non-destructive evaluation (NDE) methods have dominated most of the fields of applied research and technology over the last twenty years. These techniques provide information on the functional efficiency of materials and structures without causing any structural impact on the structure itself. Their use enables the monitoring of the structural integrity, the structural condition as well as the service in-duced degradation of materials and structures during their service life. In this respect, they address a vast field of applications ranging from the aerospace and automotive industry to civil engineering structures and material quality control. This volume comprises scientific papers presented during the Fifth Conference on Emerging Technologies in Non-Destructive Testing (Ioannina, Greece, 19–21 September 2011). A broad spectrum of related research was presented during the course of the conference, including optical, acoustic, thermal, electrical and electromagnetic methods together with imaging tomographic and signal processing techniques. Special attention was given to NDE for Civil Engineering Structures and for the first time in the conference series, a multiple session on NDE for the protection of cultural heritage was organized. Emerging Technologies in Non-Destructive Testing V contains contributions by experts in this field from 22 different countries worldwide. Reflecting the stateof-the-art in Non-Destructive Evaluation, the book will prove to be a valuable companion to students, engineers and industrial partners who are active in the field of non-destructive evaluation and testing. This volume will also provide students and researchers with insight into the focal points of contemporary research efforts in the field of non-destructive evaluation.
| Author | : Tahar Fakhfakh |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 621 |
| Release | : 2012-03-19 |
| Genre | : Technology & Engineering |
| ISBN | : 3642287689 |
Condition monitoring of machines in non-stationary operations (CMMNO) can be seen as the major challenge for research in the field of machinery diagnostics. Condition monitoring of machines in non-stationary operations is the title of the presented book and the title of the Conference held in Hammamet - Tunisia March 26 – 28, 2012. It is the second conference under this title, first took place in Wroclaw - Poland , March 2011. The subject CMMNO comes directly from industry needs and observation of real objects. Most monitored and diagnosed objects used in industry works in non-stationary operations condition. The non-stationary operations come from fulfillment of machinery tasks, for which they are designed for. All machinery used in different kind of mines, transport systems, vehicles like: cars, buses etc, helicopters, ships and battleships and so on work in non-stationary operations. The papers included in the book are shaped by the organizing board of the conference and authors of the papers. The papers are divided into five sections, namely: Condition monitoring of machines in non-stationary operations Modeling of dynamics and fault in systems Signal processing and Pattern recognition Monitoring and diagnostic systems Noise and vibration of machines The presented book gives the back ground to the main objective of the CMMNO 2012 conference that is to bring together scientific community to discuss the major advances in the field of machinery condition monitoring in non-stationary conditions.
| Author | : Jerome P. Lynch |
| Publisher | : Woodhead Publishing |
| Total Pages | : 678 |
| Release | : 2022-07-19 |
| Genre | : Technology & Engineering |
| ISBN | : 0081026978 |
Sensor Technologies for Civil Infrastructure, Volume 1: Sensing Hardware and Data Collection Methods for Performance Assessment, Second Edition, provides an overview of sensor hardware and its use in data collection. The first chapters provide an introduction to sensing for structural performance assessment and health monitoring, and an overview of commonly used sensors and their data acquisition systems. Further chapters address different types of sensor including piezoelectric transducers, fiber optic sensors, acoustic emission sensors, and electromagnetic sensors, and the use of these sensors for assessing and monitoring civil infrastructures. The new edition now includes chapters on machine learning methods and reliability analysis for structural health monitoring. All chapters have been revised to include the latest advances in materials (such as piezoelectric and mechanoluminescent materials), technologies (such as LIDAR), and applications. - Describes sensing hardware and data collection, covering a variety of sensors including LIDAR - Examines fiber optic systems, acoustic emission, piezoelectric sensors, electromagnetic sensors, terahertz technologies, ultrasonic methods, and radar and millimeter wave technology - Covers strain gauges, micro-electro-mechanical systems (MEMS), multifunctional materials and nanotechnology for sensing, and vision-based sensing and lasers - Includes new chapters on machine learning methods and reliability analysis
| Author | : Fakher Chaari |
| Publisher | : Springer |
| Total Pages | : 483 |
| Release | : 2015-07-16 |
| Genre | : Technology & Engineering |
| ISBN | : 3319204637 |
The book provides readers with a snapshot of recent research and technological trends in the field of condition monitoring of machinery working under a broad range of operating conditions. Each chapter, accepted after a rigorous peer-review process, reports on an original piece of work presented and discussed at the 4th International Conference on Condition Monitoring of Machinery in Non-stationary Operations, CMMNO 2014, held on December 15-16, 2014, in Lyon, France. The contributions have been grouped into three different sections according to the main subfield (signal processing, data mining or condition monitoring techniques) they are related to. The book includes both theoretical developments as well as a number of industrial case studies, in different areas including, but not limited to: noise and vibration; vibro-acoustic diagnosis; signal processing techniques; diagnostic data analysis; instantaneous speed identification; monitoring and diagnostic systems; and dynamic and fault modeling. This book not only provides a valuable resource for both academics and professionals in the field of condition monitoring, it also aims at facilitating communication and collaboration between the two groups.
