Research On Rolling Bearing Fault Detection System Based On Wavelet Transform And HHT

With the great strides of China's Industry 4.0 and the coordinated management of industrial production and various businesses,the overall mechanical structure will be more complicated.The upgrading of Industrial 4.0 must be based on the automated mechanical structure.The rolling bearing has a wide range of applications in the mechanical structure.Achieving fault detection of finished product line of rolling bearing has a practical significance to the protection of mechanical safety and reduce the fault rate.The traditional fault detection methods of rolling bearing have some limitations,such as time domain analysis,frequency domain analysis and resonance demodulation analysis.It is impossible to detect the fault of the rolling bearing and the type of the fault that occurred accurately.In view of the above problems,a fault detection method of rolling bearing based on wavelet transform and HHT is proposed in this paper.The specific research contents are as follows:Firstly,the main failure modes of the rolling bearing are expounded.The fault characteristics of the rolling bearing are analyzed based on the failure mode and the fault frequency of different positions on the rolling bearing is calculated.At the same time,the common analysis methods for the fault diagnosis of rolling bearings are analyzed and studied.Secondly,according to the functional characteristics of the fault detection system on rolling bearing,the vibration signal acquisition system of rolling bearing based on FPGA is designed to meet the requirements of faster acquisition speed,data storage,multi-channel data acquisition and so on.Taking the A/D converter module,SDRAM storage control module and the Ethernet interface module into consideration,the design and analysis of hardware and software part are done.Thirdly,fault vibration signal of the rolling bearing belongs to a non-stationary signal,which contains abundant fault information.The method of wavelet transform is adopted to extract the fault features of the rolling bearing and analyze the limitations of traditional wavelet threshold denoising.The signal is preprocessed by wavelet denoising based on neighborhood correlation.The method of Hilbert-Huang transform is used to realize the analysis of non-stationary signals and extract the frequency composition of the signals.Finally,a fault detection method of rolling bearing based on wavelet transform and HHT is proposed.Applying this method to detect,the fault occurring on outer ring of rolling bearing has been verified,with simulation model of rolling bearing established.In order to verify the effectiveness of the method much further,fault detections are used for inner and outer ring of SKF6205-2RS rolling bearing respectively.The results of detection show that the method can extract fault characteristic information of the rolling bearing and detect fault of the rolling bearing.