@article{ZHANG2026, 
author = {Xiaolin ZHANG and Junjie LIU and Jianling SONG and Meibao WANG},
title = {Pin-retraction detection for aerospace electrical connectors based on binocular stereo vision},
year = {2026},
journal = {Journal of Measurement Science and Instrumentation},
volume = {17},
number = {1},
pages = {49-60},
keywords = {binocular stereo vision, pin-retraction detection, image processing, electrical connector, machine vision, 3D measurement},
url = {https://www.sciopen.com/article/10.62756/jmsi.1674-8042.2026004},
doi = {10.62756/jmsi.1674-8042.2026004},
abstract = {Electrical connectors are core functional components in aerospace electrical systems. Pin retraction may lead to signal transmission interruption and even system failure, directly affecting the reliability of electrical equipment and causing incalculable consequences. We propose a high-precision pin-retraction detection method that integrates binocular stereo vision with a multi-constrained optimization matching algorithm, aiming to achieve universal recognition of pins across different connector models and robust detection of pin retraction in complex scenarios. In this study, the Delaunay triangulation algorithm is employed to eliminate the misidentified pins from the template matching algorithm. Furthermore, the pin recognition rate is enhanced to nearly 99.75%, and the accuracy of pin center positioning is significantly improved by integrating a contour fitting and positioning algorithm for pin points. Subsequently, the binocular matching of pins is achieved by combining probabilistic epipolar constraints with geometric constraints, thereby completing the three-dimensional reconstruction of pin points. The Euclidean distance from the three-dimensional pin points to the reference plane is calculated as the pin retraction amount, enabling the quantitative measurement of pin retraction amount. Through the design of multiple experiments for measuring the pin retraction of different-type electrical connectors and the analysis of the results using the Kullback-Leibler (K-L) divergence, it is demonstrated that the system’s measurement accuracy is superior to 0.05 mm, with an repeatability error of less than 0.035 mm. The effectiveness of the proposed pin-retraction detection method is thus verified, and the detection efficiency over manual operations is greatly enhanced to meet the actual industrial inspection requirements.}
}