采煤机齿轮箱故障诊断方法

发布时间：2018-05-06 18:38

本文选题：煤炭开采 + 采煤机　；参考：《工矿自动化》2017年12期

【摘要】：针对采煤机齿轮箱运行过程中很容易发生润滑不良或异常磨损等故障的问题,提出了一种基于偏最小二乘回归的采煤机齿轮箱故障诊断方法。选取采煤机齿轮箱内润滑油的铁元素含量、黏度、酸值和水分为检测指标,在对数据进行初值化及主成分提取处理后,建立了采煤机齿轮箱磨损状态的偏最小二乘回归模型。采用某煤矿采煤机齿轮箱的实际运行状态诊断对该偏最小二乘回归模型进行了检验,结果表明在齿轮箱正常磨损情况下,润滑油中铁元素含量实测值与预测值的误差较小,故障情况下二者误差较大,从而可准确判断出齿轮箱的磨损状态和故障情况。
[Abstract]:A fault diagnosis method of shearer gearbox based on partial least square regression is proposed to solve the problems of poor lubrication or abnormal wear during the operation of shearer gearbox. The content of iron element, viscosity, acid value and water of lubricating oil in shearer gear box are selected as testing indexes. After the initial value of data and principal component extraction are processed, the partial least square regression model of wear state of shearer gear box is established. The partial least square regression model is tested by using the actual operating state diagnosis of the gearbox of a coal mine shearer. The results show that under the normal wear condition of the gear box, the error between the measured value of iron element content in lubricating oil and the predicted value is small. Under the condition of fault, the error between them is great, so the wear state and fault condition of gearbox can be accurately judged.
【作者单位】：太原理工大学机械工程学院;煤矿综采装备山西省重点实验室;
【基金】：国家自然科学基金山西煤基低碳联合基金资助项目(U1510116) 山西省科技基础条件平台建设资助项目(201605D121032)
【分类号】：TD421.6

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