Vibration-Based Structural Damage Detection Using the Interactive Autodidactic School Optimization Algorithm Based on an Energy-Dissipation Method

The conventional modal strain energy (MSE), as a practical objective function, suffers from the lack of access to the damaged stiffness matrix and uses the intact stiffness matrix of the structure instead. To overcome the aforementioned deficiency of the MSE, this study proposes a reformed elastic strain energy-dissipation criterion called the augmented modal strain energy (AMSE) which is composed of relative differences of natural frequency and mode shape. In the AMSE not only the effects of the energy-dissipation criterion as a function of natural frequency but also the equilibria of the elastic strain energy as a function of mode shape are considered. Hereupon, the AMSE is implemented along with the interactive autodidactic school (IAS) optimization algorithm to investigate the effectiveness of the proposed identification method. In this regard, the AMSE is verified by assessing three benchmark truss and frame structures. The obtained results confirm the reliable performance of AMSE in both terms of intensification and diversification. Furthermore, it is observed that despite using noise-polluted modal data, the proposed AMSE not only identifies the damage location accurately, but also anticipates the extent of damage precisely. Consequently, the proposed energy-dissipation-based objective function (AMSE) is suggested, along with the IAS optimization algorithm, as a robust technique for the damage detection of structures.

Automated summary

This study proposes an improved elastic strain energy-dissipation criterion (AMSE) for structural damage detection. The AMSE is composed of relative differences in natural frequency and mode shape and is implemented with the IAS optimization algorithm. Experimental results demonstrate the reliability and accuracy of AMSE in damage detection.