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An online input force time history reconstruction algorithm using dynamic principal component analysis
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DOI：10.1016/j.ymssp.2017.06.031.png)
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The knowledge of dynamic loads acting on a structure is always required for many practical engineering problems, such as structural strength analysis, health monitoring and fault diagnosis, and vibration isolation. In this paper, we present an online input force time history reconstruction algorithm using Dynamic Principal Component Analysis (DPCA) from the acceleration time history response measurements using moving windows. We also present an optimal sensor placement algorithm to place limited sensors at dynamically sensitive spatial locations. The major advantage of the proposed input force identification algorithm is that it does not require finite element idealization of structure unlike the earlier formulations and therefore free from physical modelling errors. We have considered three numerical examples to validate the accuracy of the proposed DPCA based method. Effects of measurement noise, multiple force identification, different kinds of loading, incomplete measurements, and high noise levels are investigated in detail. Parametric studies have been carried out to arrive at optimal window size and also the percentage of window overlap. Studies presented in this paper clearly establish the merits of the proposed algorithm for online load identification. (C) 2017 Elsevier Ltd. All rights reserved.
Keyword:
Force identification
Principal component analysis
Scaled principal coordinate time history
Effective independence method
Deconvolution
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IF:
8.9
论文数:
1.3W
被引数:
6.6W
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