The Condition Moniting And Failure Diagnosis System Based On LabVIEW

Rolling bearing is the most important part of rotating machinery and plays a key role in the production. So, Whether it is normal for running are often directly affect the performance of the entire machine. According to statistics, damage of rotating machinery caused by Rolling bearing fault accounted for about 30 percent. Therefore Rolling fault monitoring technology and methods on machinery and equipment in recent years has been an important area of fault diagnosis issues.For the reasons above, this thesis takes a systemic investigation of rolling-bearing monitoring and failure diagnosis. Firstly, on the sides of libration theory and sympathetic vibration, this thesis takes a technical analysis for rolling bearing. Secondly, on the basis of overall solution and using a virtual instrument software(LabVTEW),I have had a program development and built up the experimental device and environment for fault diagnosis.Status monitoring module can monitor the online functioning of bearing and it will give an alarm for the abnormal functioning of rolling bearing. Frequency-domain module takes the typical Eilbert transform to demodulate the bearing vibration signal. Combining pattern recognition techniques and signal analysis techniques to realize intelligent fault diagnosis, to directly achieve the bearing vibration signals contained in the frequency of fault and automatically judge the type of rolling bearings.In this thesis, the study results show that the rolling bearing online monitoring and fault diagnosis system which are based on modular and humanistic design idea has the following advantages: short development cycle, easy to build up, low cost, reliable, friendly interface, easy to extend. It not only used on the Rolling online and offline monitoring and fault diagnosis but also achieved on the remote-monitoring of fault vibration signal.