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Research on Identification and Localization of Rotor–Stator Rubbing Faults Based on AF-VMD-KNN

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Abstract

In considering that variational modal decomposition (VMD) can fulfill the self-adaptive separation of complex signals, the paper has applied VMD to the identification of rotor–stator rubbing fault and position in aero-engine. The paper has proposed a method combing autocorrelation function (AF), variational modal decomposition (VMD) and k-nearest neighbor (KNN) classification algorithm. To reduce noise and reinforce the characteristics of faults, the method firstly calculates the autocorrelation function of vibration acceleration signals from casing. Secondly, the autocorrelation function is decomposed by VMD algorithm to obtain the intrinsic modal functions of different frequency bands. Thirdly, calculates the normalized energy of intrinsic modal components and carry out cluster analysis on the normalized energy set by k-means clustering. Finally, the normalized energy obtained are inputted into KNN classifier as characteristic vectors to identify rotor–stator rubbing fault and rubbing positions. The result indicates that the proposed AF-VMD-KNN method has the recognition rate of rubbing faults as high as over 94% in terms of different dates, rotation speeds and rubbing severity with training and testing samples randomly divided.

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Acknowledgements

This work was supported by National Natural Science Foundation of China [Grant number: 51605309], Natural Science Foundation of Liaoning Province [Grant number: 2019-ZD-0219] , Aeronautical Science Foundation of China [Grant number: 201933054002] and Department of Education of Liaoning Province [Grant number: JYT19042].

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  1. Shenyang Aerospace University, Shenyang, China

    Wangying Chen, Mingyue Yu & Minghe Fang

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  1. Wangying Chen
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  2. Mingyue Yu
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  3. Minghe Fang
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Correspondence to Mingyue Yu.

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Chen, W., Yu, M. & Fang, M. Research on Identification and Localization of Rotor–Stator Rubbing Faults Based on AF-VMD-KNN. J. Vib. Eng. Technol. 9, 2213–2228 (2021). https://doi.org/10.1007/s42417-021-00357-z

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