高铁接触网U型抱箍螺母故障检测算法

针对高速铁路接触网平腕臂结构中U型抱箍螺母故障的问题，提出结合抱箍螺母检测算法（HND-Net）与Mask_RCNN实例分割的故障检测方法. 提出HND-Net目标检测算法，实现对平腕臂U型抱箍所在区域的初定位，对于定位得到的U型抱箍区域图像进行像素级别的Mask_RCNN实例分割，快速得到平腕臂U型抱箍4颗螺母的精确定位及分类信息. 利用得到的定位信息，提出分割算法实现对U型抱箍螺母的可靠故障诊断. 经实验验证可知，利用该方法能够在复杂的悬挂图像中准确地定位检测U型抱箍的螺母故障，对于拍摄角度、拍摄距离有良好的适应性和较高的检测效率.

High-speed rail contact network U-holding nut fault detection algorithm

The fault detection method combining the hoop nuts detector-net (HND-Net) and Mask_RCNN instance segmentation was proposed aiming at the problem of U-shaped hoop nut fault in the flat arm structure of high-speed railroad contact network. The proposed HND-Net target detection algorithm achieved the initial localization of the area where the U-shaped hoop of the flat wrist arm was located, and performed the pixel-level Mask_RCNN instance segmentation of the localized U-shaped hoop area in order to quickly obtain the precise localization and classification information of the four nuts of the U-shaped hoop of the flat wrist arm. The proposed segmentation algorithm achieved reliable fault diagnosis of U-shaped hoop nuts by using the obtained localization information. The experimental verification shows that the nut fault of U-type clamping hoop can be accurately located and detected in complex suspension images with good adaptability and high detection efficiency for shooting angle and shooting distance.