Research on the examination technology of connector pin skewing according to Blob analysis *

Abstract

Pin skew detection is an important means to ensure the reliable operation of connectors. To address the issues of low accuracy and limited applicability in existing research, this paper proposes a connector pin skew detection method based on Blob analysis. Firstly, the image is segmented by incorporating the dimensional features of the tested connector to retain the effective information region in the image, reducing the computational workload for subsequent image processing. The image is preprocessed using an improved median filtering algorithm to effectively mitigate the interference of noise on the detection process. Secondly, a locally adaptive approach is employed to dynamically adjust the threshold, and morphological processing is applied to the pin image to enhance the pin speckle features. Subsequently, Blob analysis is utilized to analyze the connector pin speckles, obtaining data on the pin skew. Different evaluation criteria for pin skew data of various connectors are established to achieve quantitative assessment. Finally, experiments are conducted for pin skew detection of single-hole rectangular, double-hole rectangular, and single-hole circular connectors. The experimental results demonstrate that the proposed connector pin skew detection method can effectively detect various types of pin skew in connectors, with a detection accuracy better than 0.05 mm and a repeatability better than 0.03 mm. This method is suitable for automatic detection scenarios of connector pin skew.