A Novel Method for Crack Detection in Steel Cantilever Beam Using Wavelet Analysis by Combination Mode Shapes

Abstract

The first step in Structures Health Monitoring (SHM), are determining the location, intensity and type of damage in structures. Crack is a damage that often occurs in structural elements and may cause serious ruptures in the structure. One of the important approaches is the wavelet analysis of vibration modes structures. In this study, it has been performed the crack detection method in steel cantilever beam structure, using an optimized wavelet-based model. The wavelet analysis has been performed based on the higher orders of the structure's mode shapes. The results show that the proposed method is able to accurately detect all kinds of cracks, in which the cracks location are variable. In this study also, cracks with length of 20%, 10%, 5% and 2% of the beam's depth have been considered and one of the most prominent results is introducing a method for detecting robust and environmental noisy cracks. The proposed method is capable of accurately detecting crack in the cantilever beams in noisy conditions about 20 dB of SNR.

Structure‐Crack Detection and Digital Twin Demonstration Based on Triboelectric Nanogenerator for Intelligent Maintenance

“…Effective monitoring methods can detect device damage in the early stages, so maintenance can be done timely. For the crack damage of cantilevers, some researchers have proposed to utilize the changes of natural frequency or amplitude to detect defection, for example, a frequency‐based methodology for cantilever crack detection, [ 11 ] a method for crack identification in cantilever structure by utilizing the structure's mode shapes, [ 23 ] and spotting cantilever's crack based on the first three natural frequencies in fast Fourier transform. [ 24 ] Compared with non‐defective cantilevers, the natural frequency and amplitude changes of cantilevers with cracks at different positions are diverse.…”

Fault detection in rotor system by discrete wavelet neural network algorithm

“…Operational deflection shapes can be used to identify the abnormalities or changes in the system. Curvature of mode shape is one of the characteristics that can be used to detect the crack (Lim and Leong, 2013; Rouhollah Pour et al, 2018). Operational deflection shapes can detect the presence of unbalance (Ganeriwala et al, 2009, 2011) in the rotor system and defects such as misalignment (Zhang et al, 2013).…”

“…Empirical wavelet transforms along with HHTs are used to identify cracks in the gear tooth (Merainani et al, 2017). Transmissibility of wavelets and frequency bands used to detect cracks in the cantilever beam (Chouinard et al, 2019; Li et al, 2017; Rouhollah Pour et al, 2018) estimated the reliability of WTs in detection of cracks by analysing mode shapes.…”

A Hybrid Model of 1-D Signal Adaptive Filter Based on the Complex Use of Huang Transform and Wavelet Analysis

“…The detail coefficients contain the information about the noise component in the most cases, thus these coefficients are processed to remove the noise component. Reconstruction of the denoised signal is performed with the use of both the approximation coefficients and the processed detail coefficients at levels of the wavelet decomposition from 1 to N. The wavelet analysis technique is widely used in different area of the scientific research [7][8][9][10][11][12][13][14]. The effectiveness of this technique implementation depends on the choice of the type of the used wavelet, level of the wavelet decomposition and determination of the thresholding coefficient value for detail coefficient processing.…”