Research Of Fault Signal Analysis Method For Rolling Bearing Based On Acoustics

In this paper, the acoustic detection and signal analysis technology for rolling bearings is studied. The main research contents include the Acoustic rolling bearing fault detection experiments, the acoustic signal propagation characteristics, the wavelet analysis research of acoustic signal and neural network technology for the fault pattern recognition of rolling bearings, and other areas were studied.Based on the non-contacting and contacting acoustics method, some experiments are studied on rolling bearings with three different types of contrived failure. In the experiments, a number of acoustic emission signals are achieved, which proves that it will produce acoustic emission source when the fault appears, and also provides experimental basis for leading Acoustic methods into the fault detection.In this paper, the acoustic signal propagation characteristics in the air are studied. The results show that: due to the impact of air absorption, the low-frequency acoustic in the air can spread very far distance, and high-frequency acoustic attenuates off quickly. So the acoustic signals from non-contacting experiments mainly concentrate in the low frequency band. By use of analysis of parameter, judge the fault of the bearing, combining characteristic frequency, study the periodic Characteristics of the signals and then identify the location of the fault effectively.According to the characteristics of AE signals, the selection rules of wavelet basis are identified. The energy coefficient is extracted as a feature vector. Combining the analysis of waveforms, the acoustic signals are denoised, and by use of power spectrum the characteristic of frequency is analysed.By use of neural network technology, the five characteristic parameters are extracted as a eigenvector which includes rise time, ringing count, energy, duration and amplitude and the type and severity of the fault are recognized effectively.In the paper, the no-contacting acoustic detection and signal analysis technology for rolling bearings are systemic studied. The achievements can be helpful to the introduction of acoustic method into the on-line inspection and evaluation for the rotating equipments and mobile equipments, which is also significant to the research and development of the fault diagnosis technology for rolling bearings in practice.