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| Regularization methods for solving modal sensitivity-based damage equations: a comparative study |
| Received:December 07, 2020 Revised:January 10, 2021 |
| View Full Text View/Add Comment Download reader |
| DOI：10.7511/jslx20201207002 |
| KeyWord:structural damage identification modal parameters damage equations sensitivity regularization |
| Author | Institution |
| 孙健敏 |
合肥工业大学 土木与水利工程学院, 合肥 |
| 李丹 |
合肥工业大学 土木与水利工程学院, 合肥 |
| 颜王吉 |
澳门大学 智慧城市物联网国家重点实验室, 澳门 |
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| Abstract: |
| Modal parameters are most widely applied in structural damage identification using vibration responses.Structural damage equations can be established based on the modal sensitivity, and the location and degree of damage can then be obtained by solving the equations.The damage equations are generally ill-conditioned, which may lead to wrong results, because of the incompleteness of modal parameters and noise in practice.To cope with these shortcomings, regularization methods are introduced to guarantee correctness of the solutions of the ill-posed damage equations.However, there is no comprehensive investigation and comparison on the basic principles, differences and connections of various regularization methods and their applications in structural damage identification.This study investigates several commonly-used regularization methods, and compares their applicability for solving modal sensitivity-based damage equations.The effects of the degree of damage, the noise level, and the number of measured points are discussed.This work provides the basis for the selection of regularization methods in structural damage identification.Two numerical case studies of a continuous beam and a frame are carried out.It is demonstrated that L1-norm regularization and Bayesian regularization method are more robust than truncated singular value decomposition and L2-norm regularization method in solving damage equations, and that L1-norm regularization method is more suitable for the application of damage identification, which can produce less false positive damage and is less affected by noise and the number of measurement points. |
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