{"product_id":"9781119544623","title":"Condition Monitoring with Vibration Signals Compressive Sampling and Learning Algorithms for Rotating Machines","description":"\u003ch3\u003eIEEE Press\u003c\/h3\u003e\u003ch1\u003eCondition Monitoring with Vibration Signals\u003c\/h1\u003e\u003ch2\u003eCompressive Sampling and Learning Algorithms for Rotating Machines\u003c\/h2\u003e\u003ch3\u003eHosameldin Ahmed | Asoke K. Nandi\u003c\/h3\u003e\u003cdiv\u003e\u003cb\u003eTechnology \u0026amp; Engineering \/ Signals \u0026amp; Signal Processing\u003c\/b\u003e\u003c\/div\u003e\u003cbr\u003e\u003cdiv\u003e\n\u003cp\u003e\u003cb\u003eProvides an extensive, up-to-date treatment of techniques used for machine condition monitoring\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eClear 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. \u003c\/p\u003e \u003cp\u003e\u003ci\u003eCondition Monitoring with Vibration Signals: Compressive Sampling and Learning Algorithms for Rotating Machines\u003c\/i\u003e 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.\u003c\/p\u003e \u003cul\u003e \u003cli\u003eCovers the fundamental as well as the state-of-the-art approaches to machine condition monitoring�guiding readers from the basics of rotating machines to the generation of knowledge using vibration signals\u003c\/li\u003e \u003cli\u003eProvides new methods, including machine learning and compressive sampling, which offer significant improvements in accuracy with reduced computational costs\u003c\/li\u003e \u003cli\u003eFeatures learning algorithms that can be used for fault diagnosis and prognosis\u003c\/li\u003e \u003cli\u003eIncludes previously and recently developed dimensionality reduction techniques and classification algorithms\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003ci\u003eCondition Monitoring with Vibration Signals: Compressive Sampling and Learning Algorithms for Rotating Machines\u003c\/i\u003e is an excellent book for research students, postgraduate students, industrial practitioners, and researchers.\u003c\/p\u003e\n\u003c\/div\u003e\u003cdiv\u003e \u003cp\u003e\u003cb\u003eHOSAMELDIN AHMED, Ph.D.,\u003c\/b\u003e has recently completed his Ph.D. degree in Electronic and Computer Engineering under the supervision of Professor Nandi at Brunel University London, UK. His research interests lie in the areas of signal processing, compressive sampling, and machine learning with applications to vibration-based machine condition monitoring.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eASOKE K. NANDI, Ph.D.,\u003c\/b\u003e is the Chair and Head of Electronic and Computer Engineering at Brunel University London, UK. He has held academic positions at Oxford, Imperial College London, Strathclyde, and Liverpool, as well as a Finland Distinguished Professorship in Jyvaskyla (Finland). Professor Nandi co-discovered the three particles known as W+, W- and Z0 which verified the unification of the electromagnetic force and the nuclear weak force and led to the award of the 1984 Nobel Prize for Physics to his two team leaders. He has authored over 600 technical publications, including 240 journal papers as well as five books. Professor Nandi is a Fellow of The Royal Academy of Engineering (UK).\u003c\/p\u003e\n\u003c\/div\u003e\u003cbr\u003e\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublication Date: \u003c\/td\u003e\n\u003ctd\u003e14 January 2020\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublisher: \u003c\/td\u003e\n\u003ctd\u003eWiley\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eImprint: \u003c\/td\u003e\n\u003ctd\u003eWiley-IEEE Press\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eISBN-13: \u003c\/td\u003e\n\u003ctd\u003e9781119544623\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFormat: \u003c\/td\u003e\n\u003ctd\u003eHardback\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePage Count: \u003c\/td\u003e\n\u003ctd\u003e448\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eWeight (oz): \u003c\/td\u003e\n\u003ctd\u003e34.4\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":44312157782156,"sku":"9781119544623","price":132.26,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9781119544623.jpg?v=1780154133","url":"https:\/\/lateknightbooks.com\/products\/9781119544623","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}