Dynamic Detection Method of Fatigue Crack Growth Based on Image Comparison

doi:10.3901/JME.2024.18.024

Abstract

Abstract: A dynamic crack growth detection method based on image comparison is proposed to detect the fatigue cracks on the surface of aviation aluminum alloy. The crack tip location is detected by using the scheme of times N gray difference and double threshold setting, and the crack growth curve is obtained. Fatigue tests are carried out to collect crack images under different surface states. Compared with the traditional static crack detection algorithm, the feasibility of the dynamic crack detection method to detect cracks under complex surface states is verified. Compared with the direct reading method, the relative error is less than 4%, and the accuracy of the algorithm is verified. Furthermore, the gray difference scheme, threshold value determination and number of difference in different surface states are discussed, which provides a reference for automatic crack detection in multiple surface states. The difference times N of white surface state is 2, the difference times N of black surface state is 1, and the difference times N of scratches and stains surface state is 2, which can better reflect the crack growth state.

Key words: image comparison, fatigue crack, dynamic detection, grayscale deviation, crack growth

CLC Number:

SUN Shiyong, ZHU Dianli, LI Jiaqi, FAN Junling, YANG Rui, ZHAO Yanguang. Dynamic Detection Method of Fatigue Crack Growth Based on Image Comparison[J]. Journal of Mechanical Engineering, 2024, 60(18): 24-31.

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