[1]郑亚平,苏 震.一种基于ResNet的车钩状态识别方法及其应用[J].控制与信息技术,2021,(02):37-40.[doi:10.13889/j.issn.2096-5427.2021.02.005]
 ZHENG Yaping,SU Zhen.A Method of Coupler State Recognition Based on ResNet and Its Application[J].High Power Converter Technology,2021,(02):37-40.[doi:10.13889/j.issn.2096-5427.2021.02.005]
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一种基于ResNet的车钩状态识别方法及其应用()
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《控制与信息技术》[ISSN:2095-3631/CN:43-1486/U]

卷:
期数:
2021年02期
页码:
37-40
栏目:
控制理论与应用
出版日期:
2021-04-05

文章信息/Info

Title:
A Method of Coupler State Recognition Based on ResNet and Its Application
文章编号:
2096-5427(2021)02-0030-07
作者:
郑亚平1苏 震2
(1.国家能源集团包神铁路集团神朔铁路分公司,陕西 神木 719300;2. 株洲中车时代电气股份有限公司, 湖南 株洲 412001)
Author(s):
ZHENG Yaping1 SU Zhen2
( 1. Shenshuo Railway Branch Company, CHN ENERGY Baoshen Railway Group Co., Ltd., Shenmu, Shaanxi 719300, China; 2. Zhuzhou CRRC Times Electric Co., Ltd., Zhuzhou, Hunan 412001, China )
关键词:
状态识别深度学习边缘计算计算机视觉ResNetTensorRT自动驾驶机车
Keywords:
state identification deep learning edge computing computer vision ResNet TensorRT automatic operation locomotive
分类号:
TP391.41
DOI:
10.13889/j.issn.2096-5427.2021.02.005
文献标志码:
A
摘要:
针对传统视觉方法在车钩状态识别方面存在的应用场景单一、实时性差、准确率低的问题,文章提出一种基于ResNet的车钩状态识别方法,其通过在原图上增加高斯噪声和修改曝光率、饱和度、角度等图像参数的方法进行数据增强,使车钩状态识别准确率在测试集上达到97%;利用开源加速库TensorRT 6.0将ResNet50模型部署到边缘计算平台,所测得的图片推理时间可满足机车自动驾驶中对车钩状态实时监控的要求。
Abstract:
Aiming at the problem of single scene, poor real-time performance and low accuracy of traditional vision in coupler state recognition, this paper proposes a coupler state recognition method based on ResNet. By adding Gaussian noise to original image and modifying image parameters such as exposure, saturation and angle, the data is enhanced, the coupler state recognition is realized, and the accuracy of coupler state recognition reaches 97% in the test set. A ResNet50 model is deployed to an edge calculation platform by using the open source acceleration library TensorRT 6.0, and its reasoning time can meet the real-time monitoring requirement of coupler state recognition in locomotive automatic driving.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2020-11-18
作者简介:郑亚平(1970—),男,高级工程师,主要从事铁路运输管理和智能运维工作。
更新日期/Last Update: 2021-05-06