Universiti Teknologi Malaysia Institutional Repository

Comparative analysis of different weight matrices in subspace system identification for structural health monitoring

Shokravi, H. and Bakhary, N. H. (2017) Comparative analysis of different weight matrices in subspace system identification for structural health monitoring. In: Global Congress on Construction, Material and Structural Engineering 2017, GCoMSE 2017, 28 August - 29 August 2017, Johor Bahru, Johor.

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Official URL: http://dx.doi.org/10.1088/1757-899X/271/1/012092

Abstract

Subspace System Identification (SSI) is considered as one of the most reliable tools for identification of system parameters. Performance of a SSI scheme is considerably affected by the structure of the associated identification algorithm. Weight matrix is a variable in SSI that is used to reduce the dimensionality of the state-space equation. Generally one of the weight matrices of Principle Component (PC), Unweighted Principle Component (UPC) and Canonical Variate Analysis (CVA) are used in the structure of a SSI algorithm. An increasing number of studies in the field of structural health monitoring are using SSI for damage identification. However, studies that evaluate the performance of the weight matrices particularly in association with accuracy, noise resistance, and time complexity properties are very limited. In this study, the accuracy, noise-robustness, and time-efficiency of the weight matrices are compared using different qualitative and quantitative metrics. Three evaluation metrics of pole analysis, fit values and elapsed time are used in the assessment process. A numerical model of a mass-spring-dashpot and operational data is used in this research paper. It is observed that the principal components obtained using PC algorithms are more robust against noise uncertainty and give more stable results for the pole distribution. Furthermore, higher estimation accuracy is achieved using UPC algorithm. CVA had the worst performance for pole analysis and time efficiency analysis. The superior performance of the UPC algorithm in the elapsed time is attributed to using unit weight matrices. The obtained results demonstrated that the process of reducing dimensionality in CVA and PC has not enhanced the time efficiency but yield an improved modal identification in PC.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:damage detection, efficiency, equations of state
Subjects:T Technology > TA Engineering (General). Civil engineering (General)
Divisions:Civil Engineering
ID Code:97025
Deposited By: Narimah Nawil
Deposited On:12 Sep 2022 07:10
Last Modified:12 Sep 2022 07:10

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