基于图像差分运算的电刷表面摩擦面积测量

    Measurement of Surface Friction Area on Brush Based on Machine Vision

    • 摘要: 针对汇流环电刷经跑合工艺后表面磨损面积难以准确测量的问题。本研究提出一种基于多通道图像差分运算与自适应阈值分割的摩擦区域面积检测方法。该方法通过分解RGB图像后进行差分运算,结合自适应全局阈值分割提取摩擦区域后,通过连通域分析、形态学运算及面积筛选获取摩擦区域面积。试验结果表明:本方法最大相对测量误差为4.2%,满足测量误差在±5%内的工艺精度要求;且重复性测量的标准差平均值为0.84 mm2,具有较好的测量稳定性,为后续分析汇流环工艺的影响因素提供可靠数据支持。

       

      Abstract: Aiming to address the challenge of accurately measuring the wear area on the surface of collector ring brushes after the running-in process, this study proposes a method for detecting the friction area based on multi-channel image difference operations and adaptive threshold segmentation. The method involves decomposing RGB images, performing difference operations, and combining adaptive global threshold segmentation to extract the target region. Furthermore, it utilizes connected component analysis, morphological operations, and area filtering to obtain the pixel count of the target region. Experimental results demonstrate that the maximum relative measurement error of this method is 4.2%, meeting the precision requirement of a ±5% error margin. Additionally, the average standard deviation of repeated measurements is 0.84 mm², indicating high measurement stability. This approach provides reliable data support for subsequent analyses of the influencing factors of the slip ring.

       

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