Smart Sensors, Measurement and Instrumentation

Transcription

1 Smart Sensors, Measurement and Instrumentation Volume 26 Series editor Subhas Chandra Mukhopadhyay Department of Engineering, Faculty of Science and Engineering Macquarie University Sydney, NSW Australia

2 More information about this series at

3 Ruqiang Yan Xuefeng Chen Subhas Chandra Mukhopadhyay Editors Structural Health Monitoring An Advanced Signal Processing Perspective 123

4 Editors Ruqiang Yan School of Instrument Science and Engineering Southeast University Nanjing China Subhas Chandra Mukhopadhyay Department of Engineering Macquarie University Sydney, NSW Australia Xuefeng Chen School of Mechanical Engineering Xi an Jiaotong University Xi an China ISSN ISSN (electronic) Smart Sensors, Measurement and Instrumentation ISBN ISBN (ebook) DOI / Library of Congress Control Number: Springer International Publishing AG 2017 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

5 Preface The past decades have seen increasing attention from the research community worldwide on structural health monitoring (SHM). The efforts have promoted the continued advancement of sensing as well as signal processing technologies. In addition to commonly used time and frequency domain techniques, advanced signal processing techniques, such as wavelet transform and sparse representation, have been investigated as new tools for health monitoring of various mechanical or structural systems. However, many challenges and problems remain unsolved as of now or not fully addressed for SHM when signal processing techniques are applied to dealing with data measured from the system. For example, the complication of mechanical or structural systems results in complexity of the monitoring signals. Also, background noises weaken the effective condition signal and thus hinder the interpretation of the condition information. Furthermore, the specialization of each monitoring object leads to the predicament that a single signal processing technique cannot be effective for any SHM demands, which is also the reason why there are many advanced signal processing methods to be researched by academy and industry. The book aims at introducing some advanced signal processing techniques that can be used in the field of structural health monitoring. The book contains invited chapters from researchers, who are experts in applying signal processing technique to solve structural health monitoring problems. It starts with an introduction on basic knowledge of structural health monitoring, followed by traditional frequency domain analysis, which is discussed for crack detection and rotor balance correction. Then some newly developed signal processing techniques, including wavelet transform, time-frequency analysis, compressive sensing and sparse representation, empirical mode decomposition, local mean decomposition and stochastic resonance, are introduced in theory with applications to various mechanical and structural systems. These advanced signal processing techniques are believed to be beneficial to structural health monitoring. v

6 vi Preface We would like to thank all the authors for their contribution and sharing of their knowledge. We do sincerely hope that the readers will find this book interesting and useful in their research on advanced signal processing for structural health monitoring. Nanjing, China Xi an, China Sydney, NSW, Australia Ruqiang Yan Xuefeng Chen Subhas Chandra Mukhopadhyay

7 Contents Advanced Signal Processing for Structural Health Monitoring... 1 Ruqiang Yan, Xuefeng Chen and Subhas C. Mukhopadhyay Signal Post-processing for Accurate Evaluation of the Natural Frequencies G.R. Gillich and I.C. Mituletu Holobalancing Method and Its Improvement by Reselection of Balancing Object Yuhe Liao and Liangsheng Qu Wavelet Transform Based on Inner Product for Fault Diagnosis of Rotating Machinery Shuilong He, Yikun Liu, Jinglong Chen and Yanyang Zi Wavelet Based Spectral Kurtosis and Kurtogram: A Smart and Sparse Characterization of Impulsive Transient Vibration Binqiang Chen, Wangpeng He and Nianyin Zeng Time-Frequency Manifold for Machinery Fault Diagnosis Qingbo He and Xiaoxi Ding Matching Demodulation Transform and Its Application in Machine Fault Diagnosis Xuefeng Chen and Shibin Wang Compressive Sensing: A New Insight to Condition Monitoring of Rotary Machinery Gang Tang, Huaqing Wang, Yanliang Ke and Ganggang Luo Sparse Representation of the Transients in Mechanical Signals Zhongkui Zhu, Wei Fan, Gaigai Cai, Weiguo Huang and Juanjuan Shi vii

8 viii Contents Fault Diagnosis of Rotating Machinery Based on Empirical Mode Decomposition Yaguo Lei Bivariate Empirical Mode Decomposition and Its Applications in Machine Condition Monitoring Wenxian Yang Time-Frequency Demodulation Analysis Based on LMD and Its Applications Yanxue Wang, Xuefeng Chen and Yanyang Zi On the Use of Stochastic Resonance in Mechanical Fault Signal Detection X.F. Zhang, N.Q. Hu, L. Zhang, X.F. Wu, L. Hu and Z. Cheng

9 About the Editors Dr. Ruqiang Yan (S 04-M 06-SM 11) received his Ph.D. degree from the University of Massachusetts Amherst in 2007, and his M.S. and B.S. degrees from the University of Science and Technology of China (USTC) in 2002 and 1997, respectively. He was a Guest Researcher at the National Institute of Standards and Technology (NIST) in Dr. Yan joined the School of Instrument Science and Engineering at the Southeast University, China as a Professor in October He is co-author of the book Wavelets: Theory and Applications for Manufacturing and has published over 100 refereed journal and conference papers. He was co-guest editor for special issues related to structural health monitoring in various journals. He received the New Century Excellent Talents in University Award from the Ministry of Education in China, in His research interests include instrumentation design, nonlinear time-series analysis, multi-domain signal processing, and energy-efficient sensing and sensor networks for the condition monitoring and health diagnosis of large-scale, complex, dynamical systems. Dr. Yan was an Instrumentation and Measurement Society (IMS) AdCom member ( ). He is currently the Vice President for Technical & Standards Activities of the IMS. He is also co-chair of the Technical Committee (TC-7) on Signals and Systems in Measurement. He is an Associate Editor of the IEEE Transactions on Instrumentation and Measurement. He ix

10 x About the Editors received recognition of the transactions Outstanding Reviewer of 2011, 2014 Outstanding Associate Editor, and 2015 Outstanding Associate Editor. Dr. Xuefeng Chen (M 12) is Full Professor and Dean of School of Mechanical Engineering in Xi an Jiaotong University, P.R. China, where he received his Ph.D. degree in Mechanical Engineering in He works as the executive director of the Fault Diagnosis Branch in China Mechanical Engineering Society. Besides, he is also a member of ASME and IEEE, and the chair of IEEE the Xian and Chengdu Joint Section Instrumentation and Measurement Society Chapter. He has authored over 100 SCI publications in areas of composite structure, aeroengine, wind power equipment, etc. He won National Excellent Doctoral Thesis Award in 2007, First Technological Invention Award of Ministry of Education in 2008, Second National Technological Invention Award in 2009, First Provincial Teaching Achievement Award in 2013, First Technological Invention Award of Ministry of Education in 2015, and he received National Science Fund for Distinguished Young Scholars in 2012 and was awarded as Science & Technology Award for Chinese Youth in Additionally, he hosted a National Key 973 Research Program of China as principal scientist in Dr. Subhas Chandra Mukhopadhyay (M 97, SM 02, F 11) graduated from the Department of Electrical Engineering, Jadavpur University, Calcutta, India with a Gold medal and received the Master of Electrical Engineering degree from Indian Institute of Science, Bangalore, India. He has Ph.D. (Eng.) degree from Jadavpur University, India and Doctor of Engineering degree from Kanazawa University, Japan. Currently he is working as Professor of Mechanical/Electronics Engineering and Discipline Leader of the Mechatronics Degree Programme of the Department of Engineering, Macquarie University, Sydney, Australia. He has over 26 years of teaching and research experiences.

11 About the Editors xi His fields of interest include smart sensors and sensing technology, wireless sensor networks, Internet of Things, electromagnetics, control engineering, magnetic bearing, fault current limiter, electrical machines and numerical field calculation. He has authored/co-authored over 400 papers in different international journals, conferences and book chapter. He has edited 15 conference proceedings. He has also edited 15 special issues of international journals as lead guest editor and 27 books with Springer-Verlag. He was awarded numerous awards throughout his career and attracted over NZ $4.2 M on different research projects. He has delivered 292 seminars including keynote, tutorial, invited and special seminars. He is a Fellow of IEEE (USA), a Fellow of IET (UK) and a Fellow of IETE (India). He is a Topical Editor of IEEE Sensors Journal and an Associate Editor IEEE Transactions on Instrumentation. He has organized many international conferences either as general chair or technical programme chair. He is the Ex-Chair of the IEEE Instrumentation and Measurement Society New Zealand Chapter. He chairs the IEEE IMS Technical Committee 18 on Environmental Measurements. He is a Distinguished Lecturer of the IEEE Sensors Council for