基于自回归滑动平均模型的道岔动作电流故障曲线预测方法
黄世泽1张肇鑫2张帆3杨玲玉1
Prediction Method of ARMA-based Turnout Operation Current Fault Curve
HUANG ShizeZHANG ZhaoxinZHANG FanYANG Lingyu
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作者信息:1.1. 上海市轨道交通结构耐久与系统安全重点实验室， 201804， 上海；
2.2. 同济大学道路与交通工程教育部重点实验室， 201804， 上海；
3.3. 中国中铁二院工程集团有限责任公司， 610031， 成都
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Affiliation:Shanghai Key Laboratory of Rail Infrastructure Durability and System Safety, 201804, Shanghai, China
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关键词:
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Key words:
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DOI:10.16037/j.1007-869x.2022.12.009
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中图分类号/CLCN:U216.42+5
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栏目/Col:研究报告
摘要:
针对道岔故障预测无法精确到类别的问题，提出了一种基于ARMA(自回归滑动平均模型)的道岔动作电流故障曲线预测算法。结合道岔电流曲线的形成与道岔故障之间的联系，从微机监测系统中提取道岔动作电流曲线数据，建立基于ARMA模型的道岔动作电流曲线预测方法。根据实际案例，计算出道岔动作电流预测曲线，并根据多项指标进行比较验证。试验验证结果表明，该方法能直接预测曲线形状，进而判断故障类别，具有较好的预测效果。
Abstracts:
Aiming at the problem that the turnout fault category can′t be accurately predicted,an ARMA-based(autoregressive moving average) turnout operation current fault curve prediction algorithm is proposed. Considering the connection between the formation of turnout current curve and turnout fault, the turnout operation current curve data is extracted from the microcomputer monitoring system, and a method for predicting turnout operation current curve based on ARMA model is established. According to actual case, the turnout operation current prediction curve is calculated, then compared and verified based on several indicators. The experimental validation results show that the method can directly predict the curve shape and then determine the fault category, demonstrating well-performed prediction results.
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