A Comparative Analysis of Signal Decomposition Techniques for Structural Health Monitoring on an Experimental Benchmark

被引:78
作者
Civera, Marco [1 ]
Surace, Cecilia [2 ]
机构
[1] Politecn Torino, Dept Mech & Aerosp Engn DIMEAS, Corso Duca Abruzzi 24, I-10129 Turin, Italy
[2] Politecn Torino, Dept Struct Geotech & Bldg Engn DISEG, Corso Duca Abruzzi 24, I-10129 Turin, Italy
关键词
signal processing; structural health monitoring; adaptive mode decomposition methods; time-frequency analysis; damage detection; empirical mode decomposition; Hilbert Vibration Decomposition; variational mode decomposition;
D O I
10.3390/s21051825
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Signal Processing is, arguably, the fundamental enabling technology for vibration-based Structural Health Monitoring (SHM), which includes damage detection and more advanced tasks. However, the investigation of real-life vibration measurements is quite compelling. For a better understanding of its dynamic behaviour, a multi-degree-of-freedom system should be efficiently decomposed into its independent components. However, the target structure may be affected by (damage-related or not) nonlinearities, which appear as noise-like distortions in its vibrational response. This response can be nonstationary as well and thus requires a time-frequency analysis. Adaptive mode decomposition methods are the most apt strategy under these circumstances. Here, a shortlist of three well-established algorithms has been selected for an in-depth analysis. These signal decomposition approaches-namely, the Empirical Mode Decomposition (EMD), the Hilbert Vibration Decomposition (HVD), and the Variational Mode Decomposition (VMD)-are deemed to be the most representative ones because of their extensive use and favourable reception from the research community. The main aspects and properties of these data-adaptive methods, as well as their advantages, limitations, and drawbacks, are discussed and compared. Then, the potentialities of the three algorithms are assessed firstly on a numerical case study and then on a well-known experimental benchmark, including nonlinear cases and nonstationary signals.
引用
收藏
页码:1 / 35
页数:33
相关论文
共 88 条
[1]   Performance comparison of Variational Mode Decomposition over Empirical Wavelet Transform for the classification of power quality disturbances using Support Vector Machine [J].
Aneesh, C. ;
Kumar, Sachin ;
Hisham, P. M. ;
Soman, K. P. .
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGIES, ICICT 2014, 2015, 46 :372-380
[2]   Structural system identification based on variational mode decomposition [J].
Bagheri, Abdollah ;
Ozbulut, Osman E. ;
Harris, Devin K. .
JOURNAL OF SOUND AND VIBRATION, 2018, 417 :182-197
[3]   Empirical mode decomposition and its variants: a review with applications in structural health monitoring [J].
Barbosh, Mohamed ;
Singh, Premjeet ;
Sadhu, Ayan .
SMART MATERIALS AND STRUCTURES, 2020, 29 (09)
[4]   First-Order Eigen-Perturbation Techniques for Real-Time Damage Detection of Vibrating Systems: Theory and Applications [J].
Bhowmik, Basuraj ;
Tripura, Tapas ;
Hazra, Budhaditya ;
Pakrashi, Vikram .
APPLIED MECHANICS REVIEWS, 2019, 71 (06)
[5]   Real-time unified single- and multi-channel structural damage detection using recursive singular spectrum analysis [J].
Bhowmik, Basuraj ;
Krishnan, Manu ;
Hazra, Budhaditya ;
Pakrashi, Vikram .
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL, 2019, 18 (02) :563-589
[6]   ESTIMATING AND INTERPRETING THE INSTANTANEOUS FREQUENCY OF A SIGNAL .1. FUNDAMENTALS [J].
BOASHASH, B .
PROCEEDINGS OF THE IEEE, 1992, 80 (04) :520-538
[7]   Decomposition of non-stationary signals into varying time scales: Some aspects of the EMD and HVD methods [J].
Braun, S. ;
Feldman, M. .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2011, 25 (07) :2608-2630
[8]   Notes on the theory of modulation [J].
Carson, JR .
PROCEEDINGS OF THE INSTITUTE OF RADIO ENGINEERS, 1922, 10 (01) :57-64
[9]   Modal parameter identification of Tsing Ma suspension bridge under typhoon victor: EMD-HT method [J].
Chen, J ;
Xu, YL ;
Zhang, RC .
JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS, 2004, 92 (10) :805-827
[10]  
Chen J, 2009, ADV DATA SCI ADAPT, V1, P601