Damage Identification Method Using Wavelet Transforms and Functional Distraction Shape Degradation

Early diagnosis of structural damage can protect against loss of life and prolong the lifespan of structures. This has attracted scholars to have paid a lot of attention to the use of monitoring the health of the structure to identify damages in the structure. A popular method for detecting structural damage is wavelet transform which detects faults by analyzing structural responses. A Wavelet Transform fault detection technique employing functional deflection shape difference is presented in this research. To detect and locate damage, a Continuous Wavelet Transform of two dimensions is used to disintegrate the variation between both the functional deflection shapes of the intact as well as damaged structures. Mathematical modeling of a metal plate is used to demonstrate the efficacy of this technique. Whenever the decomposition signal is noisy, the placement of damage influences the detection performance of damage. This method eliminates the issue of border distortion caused by the application of conventional functional deflection shapes. The methodology demonstrates the simplicity of the proposed techniques, while the results demonstrate their precision