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ZJUS-A
Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering)  2000, Vol. 1 Issue (3): 291-299    DOI: 10.1631/jzus.2000.0291
Science & Engineering     
INFLUENCE OF MEASUREMENT ERRORS ON STRUCTURAL DAMAGE IDENTIFICATION USING ARTIFICIAL NEURAL NETWORKS
WANG Bai-sheng, NI Yi-qing, KO Jan-ming
Dept.of Civil Engineering, Zhejiang University, Hangzhou, 310027, China; Dept.of Civil and Structural Engineering, Hong Kong Polytechnic University, Hong Kong, China
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Abstract  The effect of measurement errors on structural damage identification using artificial neural networks (ANN) was investigated in this study. By using back-propagation (BP) networks with proper input vectors, numerical simulation tests for damage detection on a six-storey frame were conducted with measurement errors in deterministic as well as probabilistic senses. The identifiability using ANN for damage location and extent was studied for the cases of measurement errors with different degrees. The results showed that there exists a critical level of measurement error beyond which the probability of correct identification is sharply decreased. The identifiability using the neural networks in the presence of modeling and measurement errors is finally verified using experimental data on a two-storey steel frame.

Key words： structural damage identification      artificial neural network      measurement error     
Received: 12 January 1999     
CLC:  TU312.3  
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WANG Bai-sheng
NI Yi-qing
KO Jan-ming
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WANG Bai-sheng, NI Yi-qing, KO Jan-ming. INFLUENCE OF MEASUREMENT ERRORS ON STRUCTURAL DAMAGE IDENTIFICATION USING ARTIFICIAL NEURAL NETWORKS. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2000, 1(3): 291-299.

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http://www.zjujournals.com/xueshu/zjus-a/10.1631/jzus.2000.0291     OR     http://www.zjujournals.com/xueshu/zjus-a/Y2000/V1/I3/291

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