| 基于多源数据分析的TEDS故障识别技术研究 |
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| 引用本文： | 杨凯,刘彬,崔中伟,谢斌. 基于多源数据分析的TEDS故障识别技术研究[J]. 铁路计算机应用, 2019, 28(4): 14-17 |
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| 作者姓名： | 杨凯 刘彬 崔中伟 谢斌 |
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| 作者单位： | 1. 中国铁道科学研究院集团有限公司 电子计算技术研究所, 北京, 100081; |
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| 基金项目： | 中国铁路总公司科技研究开发计划课题（2017J003-D）；中国铁道科学研究院电子计算技术研究所科研项目（1752DZ0901） |
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| 摘 要： | 单点运行的动车组运行故障动态图像检测系统(TEDS)故障自动识别功能存在识别准确率不足,误判率高的问题。为此,提出了一种基于多源数据的动车组故障图像识别方法,以联网运行的TEDS数据为基础,结合传统的差异检测法,对不同空间与时间TEDS采集的同一列车图像进行多源数据融合与权重差异计算,实现了动车组车体异常部位的检测。试验表明,该方法建立了更为准确的对比参考源,减少了环境对成像内容的影响,能够提高动车组运行故障自动识别率,降低误报率。
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| 关 键 词： | TEDS 故障识别 图像处理 |
| 收稿时间： | 2018-11-13 |
TEDS fault recognition technology based on multi-source data analysis |
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| YANG Kai,LIU Bin,CUI Zhongwei,XIE Bin. TEDS fault recognition technology based on multi-source data analysis[J]. Railway Computer Application, 2019, 28(4): 14-17 |
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| Authors: | YANG Kai LIU Bin CUI Zhongwei XIE Bin |
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| Affiliation: | 1. Institute of Computing Technologies, China Academy of Railway Sciences Corporation Limited, Beijing 100081, China;2. Department of Locomotive and Vehicle, China Railway, Beijing 100844, China;3. Beijing Jingwei Information Technology Co. Ltd., Beijing 100081, China |
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| Abstract: | The automatic fault recognition function for TEDS (Trouble of moving EMU Detection System) of singlepoint operation has the problems of insufficient recognition accuracy and high misjudgment rate. This paper proposeda fault image recognition method for EMU based on multi-source data. Based on TEDS data of network operationand combined with traditional difference detection method, the paper carried out the multi-source data fusion andweight difference calculation for the same train image collected by TEDS in different space and time, and implementedabnormal parts detection of EMU car body. Experiments show that the proposed method establishes a more accuratecomparative reference source, reduces the impact of the environment on the image content, improves the automaticrecognition rate of EMU operation fault, and reduces the false alarm rate. |
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| Keywords: | TEDS(Trouble of moving EMU Detection System) fault recognition image processing |
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