提出了一种融合投影寻踪的自回归分析方法实现设备的预知维护。该预知维护方法是从设备关键部件处提取振动信号，经分析和计算得出24种特征指标用以描述设备运行状态；对24种特征指标分别提取一个时间序列并各自进行自回归分析，得到各自对应的预测因子；利用投影寻踪将前述预测因子投影到二维空间，然后分别建立预测因子投影值与相对应的特征指标值的拟合函数，进而推算出24种特征指标的未来值；再通过对24种特征指标的未来值在最佳投影方向矩阵下进行投影，根据投影值的分布情况判断设备未来运行状态是否存在异常，从而实现设备的预知维护。最后利用美国西储大学轴承数据中心网站公开发布的轴承探伤测试数据集中的内圈故障数据和山西省某洗煤厂主井皮带机的减速器故障数据进行了验证。%Equipment maintenance is passive when using traditional threshold alarm ,so early detection of fault and prescient maintenance are badly in need .A method of regression analysis combined with projection pursuit method for equipments is put forward .The first step of this method is analyzing the vibration signal and calculating 24 characteristic indexes to describe the equipment running status .By extracting a time series respectively of these 24 characteristic indexes and regression analysis , predictors for each characteristic index are obtained .Predictors are respectively projected to two‐dimensional space using pro‐jection pursuit method ,and then fitting functions between projection values of predictors and characteristic index are estab‐lished ,hereunder future values of 24 characteristic indexes are inferred .Then projecting these 24 future values under the best projection direction matrix and observation of distribution of projection values ,whether the future status of the equipment ab‐normal could be judged and prescient maintenance of coal mine equipment could be realized .At last ,the method proposed in this paper is verified by inner ring fault test data publicly released by the Case Western Reserve University Bearing Data Center website and failure data when gear reducer served to belt convey at main shaft of coal washery of one mining group in Shanxi Province was broken .
展开▼
