2018 ◽  
Vol 211 ◽  
pp. 06006 ◽  
Author(s):  
Anthimos Georgiadis ◽  
Xiaoyun Gong ◽  
Nicolas Meier

Vibration signal analysis is a common tool to detect bearing condition. Effective methods of vibration signal analysis should extract useful information for bearing condition monitoring and fault diagnosis. Spectral kurtosis (SK) represents one valuable tool for these purposes. The aim of this paper is to study the relationship between bearing clearance and bearing vibration frequencies based on SK method. It also reveals the effect of the bearing clearance on the bearing vibration characteristic frequencies This enables adjustment of bearing clearance in situ, which could significantly affect the performance of the bearings. Furthermore, the application of the proposed method using SK on the measured data offers useful information for predicting bearing clearance change. Bearing vibration data recorded at various clearance settings on a floating and a fixed bearing mounted on a shaft are the basis of this study


2020 ◽  
Vol 106 (7-8) ◽  
pp. 3409-3435 ◽  
Author(s):  
Issam Attoui ◽  
Brahim Oudjani ◽  
Nadir Boutasseta ◽  
Nadir Fergani ◽  
Mohammed-Salah Bouakkaz ◽  
...  

2014 ◽  
Vol 556-562 ◽  
pp. 1286-1289 ◽  
Author(s):  
Jie Shi ◽  
Xing Wu ◽  
Nan Pan ◽  
Sen Wang ◽  
Jun Zhou

In order to monitor the operation state and implement fault diagnosis of rolling bearing in rotating machinery, this paper presents a method of fault diagnosis of rolling bearing, which is based on EMD and resonance demodulation. Using EMD to decompose the signal, which comes from QPZZ-II experimental station, the components of intrinsic mode function (IMF) will be obtained. Then, calculating the correlation coefficient of each IMF component, the highest correlation coefficient of IMF component will be analyzed by resonance demodulation. Finally, the experimental results show that the method can accurately identify and diagnose the running state and bearing fault type.


Author(s):  
Shumin Hou ◽  
Ming Liang ◽  
Yi Zhang ◽  
Chuan Li

The resonance demodulation technique has been widely employed in vibration signal analysis. In order to construct a proper bandpass filter, the prior knowledge, i.e. the resonance frequency band of the mechanical system is required in the traditional demodulation method. However, as the collected vibration signal is often tainted by the background noise and interferences often with unknown frequency contents, it is difficult to identify the center frequency and the bandwidth of the filter. This paper introduces a clustering-based segmentation method to determine these parameters automatically. Envelope analysis is then applied to demodulating the vibration data. According to the simulated cases, the proposed approach is robust to Gaussian noise and interferences. Its effectiveness is further validated by applying it to detect rolling bearing faults based on experimental data.


2011 ◽  
Vol 418-420 ◽  
pp. 1843-1846
Author(s):  
Zheng Cai Yang ◽  
Zhao Wen Deng

A set of Vibration Measurement and Analysis System was Researched. It is the PC as a hardware platform and the labview as a software platform that Completed the whole system. The system contains the necessary sensors, signal conditioning ,data acquisition card and so on.It has data collection, processing,analysis,and results show functions. The Users can carry on the vibration signal analysis by Modules. Software functions Consists mainly of Signal acquisition, historical data access, data filtering, signal analysis and so on. The system is stable, full-featured, easy to operate and has good scalability and low cost high performance.


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