Fault Diagnosis Of Journal Bearings Based On Acoustic Emission Technique

Journal bearings are widely used in rotating machinery as an important support component, while journal bearing is easy to be damaged as one of the key components because of poor environment, whether journal bearings working safely and stably is related to the security and stability of the entire mechanical system. Monitoring working state of journal bearings in time is benefit to the healthy and stable operation of machinery and the personal safety of the operators. Acoustic emission technology is a new method of dynamic testing, acoustic emission technology compared with the widely used vibration method on anti-noise ability have advantages for early identification of weak faults and other advantages toward journal bearing condition monitoring and fault diagnosis.This paper based on acoustic emission technology carry out journal bearing fault diagnosis of theoretical and experimental research, the research work mainly covers the following aspects:1. Set up a journal bearing acoustic emission detective system, designed the journal bearing typical fault simulation program and carry out the typical acoustic emission test, analyses the characteristics of the acoustic emission signal and the typical failure mechanism of acoustic emission.2. Carry out research of journal bearing contact friction fault diagnosis and AE signal's feature extraction research based on wavelet packet method, the key research is to use analytical methods to take a sliding bearings contact with the launching signals , carry out contrast research of the traditional method based on parameters of acoustic emission signals fault feature extraction methods.3. Carry out research of journal bearings oil whirl fault diagnosis and make the AE signal's feature extraction research based on time-frequency analysis method and carry out comparative research with the traditional method based on parameters of acoustic emission signals fault feature extraction method and vibration method.