动车组受电弓碳滑板厚度检测算法研究

Research on Thickness Detection Algorithm for Carbon Sliding Plates of High-Speed Train Pantographs

弓网系统对电气化铁路的提速和安全运行至关重要,传统的人工测量碳滑板厚度存在工作效率低、检修周期长问题。首先,对现场采集的碳滑板图片进行灰度处理、透视校正、图像滤波、图像增强;其次,提出一种基于canny算子的边缘检测算法对碳滑板边缘提取和定位;最终,得到碳滑板厚度曲线。实验结果表明,通过图像检测算法测量得到的碳滑板厚度值误差在合理范围内,准确度高,具有实际的工程应用价值。

The bow net system is crucial for the acceleration and safe operation of electrified railways.Traditional manual measurement of the thickness of carbon skateboards has some problems such as low work efficiency and long maintenance cycles.Firstly,the carbon skateboard images collected on site are subjected to grayscale processing,perspective correction,image filtering and image enhancement.An edge detection algorithm based on the Canny operator is proposed to extract and locate the edges of the carbon skateboard,ultimately obtaining the thickness curve of the carbon skateboard.The experimental results show that the thickness value error of the carbon skateboard measured by the image detection algorithm is within a reasonable range,with high accuracy and practical engineering application value.