说明：  为实现旋转机械故障诊断方法的自动化高精度及通用性，提出基于线性局部切空间排列( ， ) 维数化简的故障诊断模型 首先结合经验模式分解( ，) 和自回归( ，) 模型系数构造全面表征不同故障特性的混合域特征集，再利用 将高维混合域特征集化简为故障区分度更好的低维特征矢量，并输入到最近邻分类器( ， ) 中进行故 障模式识别
(For rotating machinery fault diagnosis method of automated high-precision and versatility, the proposed arrangement based on the linear local tangent space (,) dimension fault diagnosis model simplification first combined empirical mode decomposition (,) and autoregressive model coefficients (,) The feature set of the mixed-domain structure to fully characterize the different failure characteristics, and then take advantage of the high-dimensional mixed-domain feature set simplified to better distinguish between degrees of failure low-dimensional feature vector, and input to the nearest neighbor classifier (,) fault pattern recognition)