| Rotating machinery is a key equipment in the automation industrial field and widely used in petroleum, electric power, aviation and so on. In engineering application, the normal operation of the rotating machine is vital for the whole production process, however, the design of the mechanical and operation will cause some failure which will affect the operation of a whole system. Rolling bearing is the most widely used in all kinds of rotating machine. It is a general part of a machine. The normal operation of the bearings directly affects the operation condition of the rotating machinery. So the bearing fault monitoring has the practical significance. In this paper, based on the Lab VIEW and EEMD,a bearing fault monitoring system is designed. The analysis of bearing vibration data can detect the bearing fault which is used to repair or replacement.Vibration signal analysis mainly includes analysis in the time domain, frequency domain analysis and time-frequency. The time-frequency analysis method has experienced from Fourier transform to wavelet transform which this paper presented one by one. But actually most of the signal is nonlinear and non-stationary, so according to the characteristics of the signal, this paper adopted an adaptive time-frequency analysis method of empirical mode decomposition(EMD). the method is mainly according to the local characteristic time scale, dynamic signal will be decomposed into a series of signals to be analyzed the basic model of independent component(IMF), and then IMF is analyzed from the time and frequency domain.A fault diagnosis system is designed based on Compact RIO and Lab VIEW of NI company. The main function of the system is to collect signals by using Compact RIO system, and then analyze signal in time domain, frequency domain, the EEMD time-frequency fields by using the Lab VIEW software and Matlab software, getting the bearing fault results. |
