Detecting cracks in automotive parts using two-dimensional wavelet transform

Gholipour, Alireza; Saadatmorad, Morteza; Masoumi Moghri, Reza; Rostami, Elyas

doi:10.48301/kssa.2026.516756.3186

Detecting cracks in automotive parts using two-dimensional wavelet transform

Articles in Press

Document Type : Original Article

Authors

alireza gholipour ¹

morteza saadatmorad ²

reza masoumi moghri ¹

elyas rostami ³

¹ Department of mechanical engineering. National University of skills (NUS). Tehran. Iran

² School of Mechanical Engineering, Babol Noshirvani University of Technology, Babol, Iran

³ Buein Zahra Technical and Engineering University

10.48301/kssa.2026.516756.3186

Abstract

Crack detection in automotive parts is an important issue in their maintenance and repair operations. Identifying and diagnosing cracks in automotive parts can help determine the health of the structure and prevent the possibility of structural failure. An efficient method to detect cracks in parts is to use wavelet transform. This paper proposes a new crack detection technique based on two-dimensional discrete wavelet transform and standard deviation obtained from its detail signals to select an optimal wavelet function. According to the findings, there is a significant relationship between the standard deviation of the statistical index and the desired detail signal obtained from the two-dimensional discrete wavelet transform to select the optimal wavelet function. In particular, the results show that by increasing the standard deviation of the detail signal matrix by a given wavelet function, the resolution of crack detection increases with that wavelet function. This result can help to better diagnose damage in automotive parts.

Keywords

Crack detection

Wavelet transform

automotive parts

Standard deviation

Optimal wavelet

Subjects