Crack Defect Detection of Smart Meter Terminals Based on X-ray Non-Destructive Testing

Cracks in smart meter terminal connectors are difficult to detect due to their small size and complex structure, potentially leading to electrical failures and safety risks. X-ray imaging has become a widely used non-destructive testing (NDT) technique due to its ability to penetrate materials and reveal internal defects. This paper presents an automated crack detection method for smart meter terminals, leveraging image processing techniques and clustering analysis. The proposed method utilizes edge extraction and entropy-based analysis to enhance defect localization while addressing the challenges of image noise and non-uniform intensity variations. To improve robustness, an adaptive thresholding strategy combined with DBSCAN clustering is employed to distinguish cracks from noise. Experimental evaluations demonstrate that the proposed approach effectively detects cracks of different sizes and locations, achieving higher accuracy and robustness compared to conventional methods.