Study on Fault Feature Extraction for Rotating Equipment
Rotating equipment,including rolling bearings and other equipment,is one of the core equipment in industrial production.It operates under heavy loads,high temperatures,and other harsh environments for extended periods of time,making it a type of equipment with a high failure rate.Any slight malfunction may have a negative impact on the equipment's reliable operation and safe production.Therefore,research on the fault diagnosis of rotating equipment is crucial.Analyzing and processing the vibration signals of the rotating equipment to extract fault features is currently an important method for fault diagnosis.Firstly,the methods for extracting fault features are divided into time domain,frequency domain,time-frequency domain analysis,and artificial intelligence.This article elaborates on the fault feature extraction methods for rotating machinery in China and abroad and analyzes the basic theories and advantages and disadvantages.Finally,the article summarizes the advantages and limitations of various fault feature extraction methods and prospects for future development trend in the field of fault feature extraction.The aim is to bring new inspiration to researchers.
NETL
NSTL
万方数据
