Precision Component Alignment Detection and Contact-Wear Particulates Visual Inspection for Spacecraft Components

Conductive slip rings are critical components for signal transmission in spacecraft radar and navigation systems. During operation, sliding contact between the brush wires and slip ring grooves leads to material wear due to brush inclination and mechanical motion, which may degrade signal quality or even cause failure. Traditional visual inspection methods suffer from low accuracy and inefficiency. To address this, this study proposes a machine vision-based approach for brush wire alignment detection and evaluates wear severity through post-run-in debris characterization. A comprehensive motion microscopy imaging platform and image analysis system were developed. Initial region detection employs a YOLO-based object detection algorithm and a custom-designed adaptive box filtering method. To enhance debris segmentation, an improved snake model incorporating contour boundary attraction forces was introduced, combined with re-segmentation for overlapping debris particles based on watershed algorithm. Experimental results demonstrate that the proposed method effectively detects brush wire alignment and characterizes wear debris, significantly improving the efficiency of failure assessment for critical slip ring components.