关于机车走行部监测装置数据综合分析利用标准的研究
Research on comprehensive analysis and utilization standard of locomotive running gear monitoring device data
PHM+车轮系统(车轮故障预测及健康管理系统)综合了机车车载走行部监测装置、TPDS及轮对在线检测系统的预报警数据以对机车车轮进行故障预测及健康管理,此次研究以概率为世界观、以统计为方法论,统计分析了TPDS监测的机务段配属HXD2型机车车轮预报警数据及车轮镟修前不落轮车床检测的多边形数据并深度挖潜,提出了PHM+车轮系统对TPDS多边形报警数据的利用建议,以提高PHM+车轮系统运维机车轮对的水平。
The PHM + Wheel System (Wheel Fault Prediction and Health Management System) integrates pre-alarm data from locomotive axle monitoring devices, TPDS, and wheelset online detection systems to predict wheel failures and manage maintenance. This study adopts a probabilistic framework and statistical methodology to analyze pre-alarm data from HXD2 locomotives in railway depots monitored by TPDS, along with polygonal data from non-landing lathe inspections before wheel overhauls. Through deep data mining, we propose practical applications of TPDS polygonal alarm data in the PHM + Wheel System to enhance maintenance efficiency.
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