基于主成分分析的车用发动机振动状态综合评价

Comprehensive Evaluation of Vehicle's Engine Vibration Based on PCA

针对车用发动机振动状态大样本数据分析困难问题,提出用主成分分析(PCA)方法对大样本数据进行特征信息提取,将高维相关特征参数转化为低维互不相关的特征参数,从而建立了某型车用发动机振动状态综合评价函数。应用该方法对某型车用发动机振动状态进行分析,结果表明,该方法可以在信息量损失较小的前提下,定量评价车用发动机振动状态。

Large sample data analysis for vehicle＇s engine vibration is a difficult issue.An approach of extracting the characteristic information from the large sample data is proposed using the principal component analysis（PCA） method.In this method,the mutually related high-dimensional characteristic parameters are reduced to several independent low-dimensional characteristic parameters,so as to constitute a model for comprehensive evaluation of a vehicle＇s engine vibration.Using this method,the vibration state of the vehicle＇s engine is analyzed.The result shows that using this method,the vibration state of vehicle＇s engine can be quantitatively evaluated with a smaller information loss.