Singular spectrum analysis based structural damage detection from nonlinear vibration measurements containing noise

2015 ◽  
Vol 63 (5) ◽  
pp. 402-414
Author(s):  
Liu Liu ◽  
Yun-Ju Yan ◽  
Bogdan I. Epureanu ◽  
Kiran D'Souza
Keyword(s):  
Damage Detection ◽  
Nonlinear Vibration ◽  
Spectrum Analysis ◽  
Structural Damage ◽  
Singular Spectrum Analysis ◽  
Structural Damage Detection ◽  
Vibration Measurements ◽  
Singular Spectrum

scholarly journals A new approach for structural damage detection exploring the singular spectrum analysis

2016 ◽  
Vol 28 (9) ◽  
pp. 1160-1174 ◽  
Author(s):  
Mario A de Oliveira ◽  
Jozue Vieira Filho ◽  
Vicente Lopes ◽  
Daniel J Inman
Keyword(s):  
Time Series ◽  
Structural Health Monitoring ◽  
Damage Detection ◽  
Health Monitoring ◽  
Spectrum Analysis ◽  
Structural Damage ◽  
Singular Spectrum Analysis ◽  
Reconstruction Process ◽  
Structural Health ◽  
Singular Spectrum

This article presents a novel approach for damage detection applied to structural health monitoring systems exploring the residues obtained from singular spectrum analysis. In this technique, a lead zirconate titanate patch acting as actuator excites the structure, and three other patches are used as sensors to receive the structural responses. This method is based on a high-frequency excitation range in order to overcome the problem caused when the low-vibration modes are excited. In this method, a wideband chirp signal, with low amplitude and variable frequency, is used to excite the structure. The response signals are acquired in the time domain, and the singular spectrum analysis procedure is performed. The residues obtained between the reconstructed and original time series are used to compute statistical metrics. The residues calculated from singular spectrum analysis are used to compute the root mean square deviation and correlation coefficient deviation metric indices, rendering the damage detection approach more reliable. Tests were carried out on an aluminum plate, and the results have demonstrated the effectiveness of the proposed method making it an excellent approach for structural health monitoring applications. The results exploring different numbers of components used during the reconstruction process of time series are obtained, and the highlights are presented.

A numerical–experimental study for structural damage detection in CFRP plates using remote vibration measurements

2017 ◽  
Vol 8 (1) ◽  
pp. 33-47 ◽  
Author(s):  
Guilherme Ferreira Gomes ◽  
Yohan Alí Diaz Mendéz ◽  
Sebastião Simões da Cunha ◽  
Antônio Carlos Ancelotti
Keyword(s):  
Experimental Study ◽  
Damage Detection ◽  
Structural Damage ◽  
Structural Damage Detection ◽  
Vibration Measurements

Application of Singular Spectrum Analysis to Bridge Structure Health Monitoring and Damage Detection

2012 ◽  
Author(s):  
Chin-Hsiung Loh ◽  
Shu-Hsien Chao
Keyword(s):  
Damage Detection ◽  
Spectrum Analysis ◽  
Null Space ◽  
Singular Spectrum Analysis ◽  
Weather Condition ◽  
Detection Algorithm ◽  
Assessment Method ◽  
Data Series ◽  
Time Data ◽  
Singular Spectrum

Singular Spectrum Analysis (SSA) is a novel technique and has proven to be a powerful tool for time data series analysis. It takes singular value decomposition (SVD) of Hankel matrix embedded by analyzed time data series and decomposes the data into several simple, independent and identifiable components. In this paper, first, the coupling degree of the 1st and 2nd singular values through the composition of the analyzed signal in SSA is used as two important values to detect damage. Besides, based on the extracted sub-space or null-space from SVD of analytic matrix, damage detection algorithm is developed by considering the orthonormality between the sub-space and null-space. The proposed algorithms are verified using non-stationary response data of a model bridge (data from scouring test of a bridge) and field experiment of a bridge during abnormal weather condition. Discussion on the proposed methods with different assessment method to identify the occurrence of damage using SSI-DATA and SSI-COV to identified the system dynamic characteristics are also made.

Integrating Singular Spectrum Analysis with Damage Detection of Structure

2013 ◽  
Vol 569-570 ◽  
pp. 831-838
Author(s):  
Siu Seong Law ◽  
Kun Liu
Keyword(s):  
Damage Detection ◽  
Spectrum Analysis ◽  
Singular Spectrum Analysis ◽  
Integrated Approach ◽  
Measurement Noise ◽  
Truss Structure ◽  
Sensitivity Matrix ◽  
Response Sensitivity ◽  
Singular Spectrum ◽  
Measured Response

The response sensitivity-based method for damage detection is integrated with the singular spectrum analysis (SSA) technique for an improvement of the identification results. The measured response of the structure is SSA decomposed, and the response sensitivity matrix as well as the computed response vectors are projected into the corresponding decomposition subspace to form the identification equations, and components containing the least measurement noise and most damage information can be selected to detect local damages in the structure. The proposed integrated approach is illustrated with a planar truss structure with discussions on the effectiveness of a single and multiple decomposed component of the measured response in the damage detection.

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