Study of Rolling Bearing SVM Pattern Recognition Based on Correlation Dimension of IMF

Jiang, Qing; Li, Ting; Yao, Yan; Cai, Jun

doi:10.1109/isdea.2012.665

Cited by 3 publications

(1 citation statement)

References 4 publications

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“…In this paper, the results of the evaluation are verified by envelope spectrum analysis. Firstly, the IMF component of the intrinsic mode function of the data is extracted by the EMD algorithm, and the IMF component with the correlation of the original signal greater than 0.5 is selected by the correlation coefficient criterion [44]. The IMF component selected in this paper is greater than 0.5, which is IMF1.…”

Section: Envelope Spectrum Analysismentioning

confidence: 99%

Evaluation of Rolling Bearing Performance Degradation Using Wavelet Packet Energy Entropy and RBF Neural Network

et al. 2019

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Rolling bearings are the most important parts in rotating machinery, and one of the most vulnerable parts to failure. The rolling bearing is a cyclic symmetrical structure that is stable under normal operating conditions. However, when the rolling bearing fails, its symmetry is destroyed, resulting in unstable performance and causing major accidents. If the performance of rolling bearings can be monitored and evaluated in real time, maintenance strategies can be implemented promptly. In this paper, by using wavelet packet energy entropy (WPEE), the early fault-free features of bearing and the failure samples of similar bearings are decomposed firstly, and the energy value is extracted as the original feature, simultaneously. Secondly, a radial basis function (RBF) neural network model is established by using early fault-free features and similar bearing failure characteristics. The bearing full-life data characteristics of the extracted features are added into the RBF model in an iterative manner to obtain performance degradation Indicator. Boxplot was introduced as an adaptive threshold method to determine the failure threshold. Finally, the results are verified by empirical mode decomposition and Hilbert envelope demodulation. A bearing accelerated life experiment is performed to validate the feasibility and validity of the proposed method. The experimental results show that the method can diagnose early fault points in time and evaluate the degree of bearing degradation, which is of great significance for industrial practical applications.

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Section: Envelope Spectrum Analysismentioning

confidence: 99%