کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
561741 | 875322 | 2010 | 14 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Damage classification and estimation in experimental structures using time series analysis and pattern recognition Damage classification and estimation in experimental structures using time series analysis and pattern recognition](/preview/png/561741.png)
Developed for studying long sequences of regularly sampled data, time series analysis methods are being increasingly investigated for the use of Structural Health Monitoring (SHM). In this research, Autoregressive (AR) models were used to fit the acceleration time histories obtained from two experimental structures: a 3-storey bookshelf structure and the ASCE Phase II Experimental SHM Benchmark Structure, in undamaged and limited number of damaged states. The coefficients of the AR models were considered to be damage-sensitive features and used as input into an Artificial Neural Network (ANN). The ANN was trained to classify damage cases or estimate remaining structural stiffness. The results showed that the combination of AR models and ANNs are efficient tools for damage classification and estimation, and perform well using small number of damage-sensitive features and limited sensors.
Journal: Mechanical Systems and Signal Processing - Volume 24, Issue 5, July 2010, Pages 1556–1569