Research On Fault Diagnosis Of Rolling Bearing Based On Vibration Signal Analysis

As one of the most important parts in modern machinery and equipment,rolling bearings will affect the performance of the entire equipment in the event of a failure,and even the safety of the entire production line where the equipment is located.At present,the existing fault diagnosis technology of rolling bearings in China can not meet the needs of modern industry development for high efficiency and high accuracy.In view of the above problems,this paper proposes a Matlab-based fault diagnosis method for rolling bearings based on the vibration characteristics of rolling bearings during operation,combined with the advantages of rapid computer learning and intelligent diagnosis.Taking rolling bearings as the research object,this paper analyzes the basic structure and fault types of rolling bearings.Diagnosis method of feature value extraction and computer intelligent classification of vibration signals.Based on Matlab,the multi-fractal detrending fluctuation analysis(MFDFA method)computer analysis is used to analyze the vibration signals of different states,and the two multi-fractal spectrum parameters with the best sensitivity and stability are selected as the fault eigenvalues and input into the Matlab classifier for computer Learning and classification diagnosis have verified the effectiveness of the method? Furthermore,the five-dimensional eigenvalue analysis method composed of complementary information eigenvalues was used to optimize the diagnosis method,and the simulation test and verification were carried out,which effectively solved the error problem of the existing fault diagnosis technology.The innovation of the content studied in this article is that only the vibration signal fragments can be used to complete the entire process from the analysis to the diagnosis of the rolling bearing fault type.The inspection tool is easy to obtain and use,without the need to add equipment or develop new systems,and save costs to the greatest extent.And,the diagnostic method has a high universality,a wide range of application,and can be directly applied to actual industrial production..