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:2019,28(9):110-117
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基于EMD-ARIMA模型的地铁门传动系统早期故障预测
(1.兰州理工大学 能源与动力工程学院, 兰州 730050;2.兰州轨道交通有限公司 机电设备处, 兰州 730030)
Early Fault Prediction of Metro Door Transmission System Based on EMD-ARIMA Model
(1.School of Energy and Power Engineering, Lanzhou University of Technology, Lanzhou 730050, China;2.Department of Electromechanical Equipment, Lanzhou Rail Transit Co. Ltd., Lanzhou 730030, China)
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投稿时间:2019-03-09    修订日期:2019-04-04
中文摘要: 地铁门夹紧力峰值数据在一定程度上可以反映其传动系统的退化状态.基于此,本文运用研发的数据采集系统对新上线地铁门的夹紧力进行实时地采集、存储、显示和查询.分别采用ARIMA模型与EMD-ARIMA模型对夹紧力峰值的均值和标准差随累积运行时间的变化趋势进行预测,依据预测结果确定地铁门传动系统发生早期故障的概率.通过两种模型预测对比结果表明,EMD-ARIMA模型可以较好地预测地铁门夹紧力峰值的变化趋势,这种改进的预测方法可以对处于调试期车门退化状态的预测提供新思路.
Abstract:The peak of clamping force data of Metro doors can reflect the degradation of the transmission system to a certain extent. Based on this, this study uses the developed data acquisition system to collect, store, display, and query the clamping force of the new on-line metro door in real time. ARIMA model and EMD-ARIMA model are used to predict the trend of mean and standard deviation of peak clamping force with cumulative running time, and the probability of early failure of door transmission system is determined based on the prediction results. The comparison of the two models shows that EMD-ARIMA model can predict the change trend of peak clamping force of metro doors, and the improved prediction method can provide a new idea for predicting the deterioration of metro doors in debugging period.
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基金项目:国家自然科学基金(71561016)
引用文本:
李勃旭,南西康,郑向东,高文科.基于EMD-ARIMA模型的地铁门传动系统早期故障预测.计算机系统应用,2019,28(9):110-117
LI Bo-Xu,NAN Xi-Kang,ZHENG Xiang-Dong,GAO Wen-Ke.Early Fault Prediction of Metro Door Transmission System Based on EMD-ARIMA Model.COMPUTER SYSTEMS APPLICATIONS,2019,28(9):110-117

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