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| Damage identification of truss structure based on strain mode and sparse Bayesian learning |
| Received:November 12, 2020 Revised:February 16, 2021 |
| View Full Text View/Add Comment Download reader |
| DOI：10.7511/jslx20201112001 |
| KeyWord:structural damage identification strain mode sparse Bayesian learning space truss structure |
| Author | Institution |
| 仇树茂 |
西北工业大学 力学与土木建筑学院, 西安 |
| 杨海峰 |
西北工业大学 力学与土木建筑学院, 西安 |
| 吴子燕 |
西北工业大学 力学与土木建筑学院, 西安 |
| 李梦莹 |
西北工业大学 力学与土木建筑学院, 西安 |
| 悦峰 |
西北工业大学 力学与土木建筑学院, 西安 |
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| Abstract: |
| When the traditional sparse Bayesian learning algorithm is adopted for structure damage identification, the stiffness damage parameters of each element need to be updated iteratively.The problems such as low computational efficiency and high requirements for completeness of mode shapes will be very serious when there are many structural elements.In order to solve the above problems, a two-step method for damage identification is proposed.Firstly, the modal strain difference index is used to judge the suspected damage elements.Secondly, the element stiffness damage parameters are taken as the target to establish a multi-level sparse Bayesian learning model for structural damage identification.Then the damage location and severity of suspected damage elements are identified using the sparse Bayesian learning algorithm.A space truss structure is used to verify object, the effectiveness of the proposed method for identification of single damage and multi-damage. |
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