Research on Fault Behavior Analysis and Feature Extraction Methods of CNC Machine Tools Based on Sensor Data
This paper deeply studies the fault behavior analysis and feature extraction methods of CNC machine tools based on sensor data.First,an overview of the CNC machine is given,including its definition,fault data sources and pre-processing.Then,the cluster analysis of fault data and a variety of fault behavior diagnosis methods,such as time-domain,frequency-domain,time-frequency,time-varying and multi-scale feature analysis,are discussed in detail.In the feature selection part,this paper expounds the process,method and results of feature selection,and successfully identifies a series of representative fault characteristic values.These research results provide a solid basis for the fault prediction and diagnosis of CNC machine tool equipment,which helps to improve the operation efficiency and stability of the equipment and reduce the maintenance cost.In the future,more effective fault detection and diagnosis methods should be explored to promote the development of modern industrial manufacturing.
万方数据
维普
