Fault Diagnosis Based on Acoustic Emission Signal for Low Speed Rolling Element Bearing

2011 ◽  
Vol 199-200 ◽  
pp. 1020-1023 ◽  
Author(s):  
Hua Qing Wang ◽  
Yong Wei Guo ◽  
Jian Feng Yang ◽  
Liu Yang Song ◽  
Jia Pan ◽  
...  

The fault of a bearing may cause the breakdown of a rotating machine, leading to serious consequences. A rolling element bearing is an important part of, and is widely used in rotating machinery. Therefore, fault diagnosis of rolling bearings is important for guaranteeing production efficiency and plant safety. Although many studies have been carried out with the goal of achieving fault diagnosis of a bearing, most of these works were studied for rotating machinery with a high rotating speed rather than with a low rotating speed. Fault diagnosis for bearings under a low rotating speed, is more difficult than under a high rotating speed. Because bearing faults signal is very weak under a low rotating speed. This work acquires vibration and acoustic emission signals from the rolling bearing under low speed respectively, and analyzes the both kinds of signals in time domain and frequency domain for diagnosing the typical bearing faults contrastively. This paper also discussed the advantages using the acoustic emission signal for fault diagnosis of rolling speed bearing. From the results of analysis and experiment we can find the effectiveness of acoustic emission signal is better than vibration signal for fault diagnosis of a bearing under the low speed.

Author(s):  
Fazhong Li ◽  
Zengshui He ◽  
Lin Zhang ◽  
Anbo Ming ◽  
Yongsheng Yang

The accurate description of acoustic emission signals produced by the localized fault of a rolling element bearing plays an important role in its feature extraction and analysis. This paper analyzes the excitation mechanisms and develops the analytical model of acoustic emission signals produced when the rolling element bearing passes across the localized fault on the inner or outer race. Based on the analytical model, the spectral characteristics are discussed substantially. Simulations and experiments are carried out to validate the efficacy of the model developed in the paper. The experimental results show that the response signal thus produced has two parts. The first one is produced by the entry of the rolling element bearing, while the other is produced by the departure of the rolling element bearing. The energy of both parts is concentrated around the resonance frequency of the acoustic emission transducer. Generally, the interval of adjacent acoustic emission events is not equivalent to each other and the corresponding spectrum is continuous in the high frequency band.


2011 ◽  
Vol 199-200 ◽  
pp. 895-898
Author(s):  
Hong Fang Yuan ◽  
Peng Wang ◽  
Hua Qing Wang

Because AE (Acoustic Emission) signals in bearing fault monitoring unavoidably mixed various noise which lead to wide band characteristics, in this paper, the collected AE signals are pre-processed by EMD (Empirical Mode Decomposition) algorithm to extract useful information in the concerned frequency range, after that, power spectrum is used to locating analysis and pattern recognition. Experiment show that this method could improve the detection accuracy in rolling element bearing fault diagnosis.


2011 ◽  
Vol 291-294 ◽  
pp. 2006-2009
Author(s):  
Hua Qing Wang ◽  
Yong Wei Guo ◽  
Jin Ji Gao ◽  
Feng Wang

Bearing faults signal is very weak under a low rotating speed, and therefore fault diagnosis for bearings under a low rotating speed, is more difficult than under a high rotating speed. The wavelet analysis technique is adopted for fault diagnosis of rolling element bearing under low rotating speed. This work also acquired vibration signals and acoustic emission signals from the rolling bearing under low speed respectively, and analyzed the both kinds of signals for diagnosing the typical bearing faults contrastively.


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