Design And Implementation Of Rolling Bearing Vibration Signal Analysis And Data Processing System

In the mechanical equipment system that rotates at high speed unde r complex working conditions,the rolling bearing plays a pivotal role.Therefore,the status detection of the rolling bearing is an indispensable link.By processing and analyzing the vibration signal of the rolling bearing,the fault condition of the bearing can be effectively judged and the efficiency of the fault detection of the rolling bearing can be improved;on the other hand,the scientific management of vibration signal data is convenient for the subsequent fault reproduction of the bearing.Therefore,design and implementation of a system for rolling bearing vibration signal analysis and data processing is of great significance for the quality inspection of the rolling bearing.In view of the problem of rolling bearing vibration signals under continuous high sampling conditions,the amount of data is large and the storage resource is occupied too large,this paper uses a compressed sensing algorithm to achieve dimensionality reduction of the signal.First,this paper conducts theoretical research on the compression sensing algorithm used for rolling bearing vibration signals.Then by conducting simulation signal compression test,this paper compares the reconstruction effects of three different reconstruction algorithms.Finally,the SWOMP reconstruction algorithm is selected to reconstruct the signal and applied to the subsequent vibration signal of the rolling bearing.And the bearing vibration signal compression test further demonstrates that the compression sensing algorithm has certain feasibility and effectiveness for the compression of rolling bearing vibration signals.In view of the problem that the vibration signal of the roll ing bearing contains complex interference noise components,which makes it difficult to extract the vibration characteristics of the bearing,this paper int roduces the fault theory of the rolling bearing and then studies the feature extraction algorithm ba sed on CEEMDAN and wavelet packet.The extraction of IMF components that can reflect the vibration characteristics of be arings in IMFs that achieve CEEMDAN decomposition through cross-correlation coefficients and variance contribution rates.For the wavelet packet decomposition,the frequency band characteristics of the wavelet packet decomposition are selected by the percen tage of the energy of the sub-band in the total band energy.Finally,the above two algorithms are used to extract the feature of the b earing vibration signal.The results show that the wavelet packet feature extraction algorithm can effectively extract the characteristics of the rolling bearing vibration signal.A software system that based on Labview is developed.This system includes user login and management module,bearing information management module,data acquisition and compression module,data analysis module,data stora ge module and data callback module.This system mainly realizes real-time compression of the continuously collect ed vibration signals,and stores the file name of the stored data in the My SQL database.At the same time,the bearing operating status is monitored in the time domain and the frequency domain to effectively extract the bearing vibration characteristics.In addition,the data files stored in the database can be recalled according to the test sequence and time to realize the recurrence of the running state of the bearing.By conducting rolling bearing vibration test,the function of each module of the developed software system is verified.The test results show that the system developed by this subject has good performance and has certain practical application significance.