Research And Application For Bearing Fault Diagnosis On Wavelet Transform

With the continuous development of science and technology, machinery and equipment become increasingly complex, increasingly high level of automation, equipment in the modern industrial production, the role and impact are increasing, and the cost of the equipment is getting higher and higher. The machine operation for any fault or failure will not only lead to serious consequences, resulting in huge economic losses, and even may lead to catastrophic loss of life and adverse social impact. It can clearly be seen, equipment fault diagnosis, monitoring technology in the modern industrial production plays a very important role.Rolling bearing is one of the most commonly components in rotating machinery equipment.So the fault diagnosis and detection of rolling bearing are very important with practical significance and economic significance.The key to fault diagnosis of rolling bearing is the analysis and processing of vibration signals,and extract fault features of rolling bearing. Analysis of rolling bearing vibration signal is through installing the vibration sensor in the box on the bearing to monitor the bearing vibration signal,through analysis and processing of rolling bearing vibration signal to extract the signal containing the fault characteristics and then to master the work of the state of rolling bearings, processing of various fault in timely.Due to the fact that most fault vibration signals of the rolling bearing present non-stationary properties,it is essential to choose appropriate signal analysis and processing methods that are suitable for non-stationary signals to extract fault feature.The time-frequency analysis method is widely applied to rolling bearing fault diagnosis due to it can simultaneously provide time and frequency domain information of a signal. In this paper,because wavelet transform has the characteristics of multi-resolution analysis and the capacity of local features in the time domain and frequency domain,we use wavelet analysis in the experiment.Through the analysis of experimental data,it verify that the two methods of failure diagnosis based on wavelet analysis and wavelet packet analysis are effectiveness.The all kinds of fault signals types and the damage degrees are compared and analyzed,the studying reault make the general rule used in rolling bearing fault diagnosis clearer further.In addition,through analysising the different wavelet basis functions and wavelet decomposition level,the analysis method of rolling bearing fault diagnosis results are proposed,and on this basis I hope that a practical model of rolling bearing fault diagnosis will be established.