期刊
ADVANCES IN STRUCTURAL ENGINEERING
卷 19, 期 6, 页码 908-927出版社
SAGE PUBLICATIONS INC
DOI: 10.1177/1369433216630370
关键词
damage identification; genetic algorithm; global sensitivity analysis; goal attainment algorithm; multi-objective optimization; random sampling-high dimensional model representation; structural health monitoring
资金
- MHRD, India
Structural damage identification and quantification of damage using non-destructive methods are important aspects for any civil, mechanical and aerospace engineering structures. In this study, a novel damage identification algorithm has been developed using random sampling-high dimensional model representation approach. A global sensitivity analysis based on random sampling-high dimensional model representation is adopted for important parameter screening purpose. Three different structures ( spring mass damper system, simply supported beam and fibre-reinforced polymer composite bridge deck) have been used for various single and multiple damage conditions to validate the proposed algorithm. The performance of this method is found to be quite satisfactory in the realm of damage detection in structures. The random sampling-high dimensional model representation-based approach for meta-model formation is particularly useful in damage identification as it works well when large numbers of input parameters are involved. In this study, two different optimization methods have been used and their relative capability to identify damage has been discussed. Performance of this damage identification algorithm under the influence of noise has also been addressed in this article.
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