铁路计算机应用2024,Vol.33Issue(1) :28-32.DOI:10.3969/j.issn.1005-8451.2024.01.04

牵引变电所墙壁渗水检测方法研究与实现

Method for detecting water seepage on walls of traction substation

刘立超
铁路计算机应用2024,Vol.33Issue(1) :28-32.DOI:10.3969/j.issn.1005-8451.2024.01.04

牵引变电所墙壁渗水检测方法研究与实现

Method for detecting water seepage on walls of traction substation

刘立超1
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作者信息

  • 1. 中国铁路呼和浩特局集团有限公司 供电部,呼和浩特 010050
  • 折叠

摘要

针对牵引变电所墙壁渗水易影响列车的正常运营,且人工检查效率较低的问题,研究墙壁渗水检测方法.该方法基于改进的MobileNetV2网络和DeeplabV3网络相结合的模型进行设计,采用边缘计算和 5G移动通信技术进行边缘化部署,实现了对牵引变电所墙壁渗水区域的精确分割,降低了模型的参数量,提升了模型的精确度,PA(Pixel Accuracy)和MIoU(Mean Intersection over Union)指标分别达到98.82%和95.32%;部署方案便捷,适用范围广,在2T算力下,单帧执行时间仅为40 ms.

Abstract

This paper focused on the problem of water seepage on the walls of traction substations,which could easily affect the normal operation of trains,and the low efficiency of manual inspection,studied a method for detecting water seepage on the walls.This method was designed based on the improved model combining MobileNetV2 network and DeeplabV3 network,used edge computing and 5G mobile communication technology for edge deployment.It was implemented accurate segmentation of the water seepage area on the wall of the traction substation,reduced the parameters of the model,and improved the accuracy of the model.PA(Pixel Accuracy)and MIoU(Mean Intersection over Union)indicators reach 98.82%and 95.32%respectively.The deployment plan is convenient and widely applicable,with a single frame execution time of only 40 ms under 2 T of computing power.

关键词

墙壁渗水/MobileNetV2/DeeplabV3/牵引变电所/目标检测

Key words

wall seepage/MobileNetV2/DeeplabV3/traction substation/object detection

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出版年

2024
铁路计算机应用
中国铁道科学研究, 中国铁道学会计算机委员会

铁路计算机应用

影响因子:0.267
ISSN:1005-8451
参考文献量2
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