A mode shape sensitivity-based method for damage detection of structures with closely-spaced eigenvalues. (28th February 2022)

• Record Type: Journal Article
• Authors: Hassani, Sahar; Mousavi, Mohsen; Gandomi, Amir H.
• Is Part Of: Measurement. Volume 190(2022)
• Publication Date: 2022-02-28
• Subjects: Structural health monitoring -- Damage detection -- Modal residual vector -- Closely-spaced eigenvalues -- Optimisation algorithm; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2021.110644
• Languages: English
• ISSNs: 0263-2241

Abstract

Abstract: A new optimisation problem is proposed to facilitate a fast and reliable damage detection of structures with closely-spaced eigenvalues. The first stage of the proposed method identifies the most probable defective elements resulting in the elimination of healthy members from further investigation. This will further reduce the computational efforts of computing damage indices regarding the defective elements. The second stage of the proposed method exploits the proposed objective function to update the damage indices of the identified defective elements from the first stage. Two truss structures with multiple damaged elements in different damage scenarios are studied where measurements with different levels of noise are used as input to the proposed algorithm. Numerical results and comparison with previous studies demonstrate the superiority of the proposed method in damage detection of structures with closely-spaced eigenvalues. Highlights: A method is proposed for damage detection of structures with closely-spaced modes. A new sensitivity-based objective function is established for damage quantification. Data from the lowest repeated modes are used for damage detection. Two spatial trusses retrofitted with and without lumped masses are studied. It is shown that the proposed method is superior to some other methods.