基于PCA-MSET的主通风机健康评估方法

Health Assessment Method of Main Ventilator Based on PCA-MSET

为了保证煤矿生产中通风机的健康运行,提出了一种基于PCA-MSET的健康评估方法。以山西某煤矿2#主通风机为研究对象,利用主成分分析法(PCA)对通风机的13个监测变量进行线性降维处理;以主通风机主电机的主成分参数为特征参数,建立基于多元状态估计技术(MSET)的主风机健康状态评估模型,利用滑动窗口统计法设置观测向量和估计向量的残差阈值,最后人为模拟故障数据进行模型的验证,结果表明主风机健康状态评估模型能够有效实现预期功能。

Taking No.2 main fan of a coal mine in Shanxi Province as the research object,the linear dimension reduction of 13 monitoring variables of the ventilator was carried out by PCA.Taking the main component parameters of the main motor of the main ventilator as the characteristic parameters,the health state assessment model of the main ventilator based on the MSET is established,and the residual threshold of the observation vector and the estimation vector is set by using the sliding window statistical method.Finally,the model is verified by simulating the fault data.The results show that the health state assessment model of the main ventilator can effectively achieve the expected function.