Vibration Signal Analysis of Rolling Bearing Based on Permutation Entropy

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.

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Design and development of rolling bearing vibration signal analysis system

Proceedings of 2011 International Conference on Electronic & Mechanical Engineering and Information Technology ◽

10.1109/emeit.2011.6023648 ◽

2011 ◽

Cited By ~ 1

Author(s):

Wensheng Su ◽

Fengtao Wang

Keyword(s):

Signal Analysis ◽

Vibration Signal ◽

Rolling Bearing ◽

Design And Development ◽

Bearing Vibration ◽

Vibration Signal Analysis ◽

Analysis System

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Rolling Bearing Vibration Signal Analysis Based on Dual-Entropy, Holder Coefficient and Gray Relation Theory

2017 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C) ◽

10.1109/qrs-c.2017.37 ◽

2017 ◽

Cited By ~ 1

Author(s):

Yulong Ying ◽

Jingchao Li ◽

Zhimin Chen ◽

Jing Li

Keyword(s):

Signal Analysis ◽

Vibration Signal ◽

Rolling Bearing ◽

Relation Theory ◽

Bearing Vibration ◽

Vibration Signal Analysis

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Vibration signal demodulation and bearing fault detection: A clustering-based segmentation method

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science ◽

10.1177/0954406213514960 ◽

2013 ◽

Vol 228 (11) ◽

pp. 1888-1899 ◽

Cited By ~ 7

Author(s):

Shumin Hou ◽

Ming Liang ◽

Yi Zhang ◽

Chuan Li

Keyword(s):

Background Noise ◽

Signal Analysis ◽

Vibration Signal ◽

Rolling Bearing ◽

Center Frequency ◽

Segmentation Method ◽

Vibration Data ◽

Signal Demodulation ◽

Vibration Signal Analysis ◽

Demodulation Method

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.

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