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基于PCA和希尔伯特谱的柔性薄壁轴承故障诊断研究
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国家高技术研究发展计划(863计划)(2015AA043005);国家自然科学基金项目(51875205;51875216);广东省自然科学基金项目(2018A030310017;2019A1515011780);广东省重点领域研发计划项目(2019B090918003);广东省教育厅项目(2018KQNCX191);广州市科技计划(201904010133)


Research on Fault Diagnosis of Flexible Thinwall Bearings Based on PCA and Hilbert Spectrum
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    摘要:

    针对柔性薄壁轴承在发生故障时产生的非平稳、非线性信号,采用希尔伯特-黄变换方法对其进行分析,同时针对噪声信号会污染整个希尔伯特谱的问题,提出基于SVR谱的PCA降噪算法。通过仿真分析和柔性薄壁轴承故障实验,从轴承内、外圈故障仿真信号和实际信号的希尔伯特谱中,均能够得出外圈故障信号频率的变化率为轴承转频的两倍、而内圈故障信号频率的变化率与轴承转频一致的结论。该结论可为工程实际应用提供理论指导。

    Abstract:

    For the nonstationary and nonlinear signals generated by the flexible thinwalled bearings in the event of failure,the Hilbert-Huang transform (HHT) method is used to analyze them.For the problem that the noise signal will pollute the entire Hilbert spectrum,a PCA noise reduction algorithm based on SVR spectrumis proposed.Through simulation analysis and flexible thinwall bearing failure experiments,from the Hilbert spectrum of the bearing inner and outer ring fault simulation signals and actual signals,it can be concluded that the change rate of the outer ring fault signal frequency is twice that of the bearing frequency,the change rate of the inner ring fault signal frequency is consistent with the bearing frequency.This conclusion can provide theoretical guidance for the practical application of the project.

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李伟光,刘振宇,林鑫,赵学智,林守金,李国臣.基于PCA和希尔伯特谱的柔性薄壁轴承故障诊断研究[J].机床与液压,2020,48(16):169-175.
LI Weiguang, LIU Zhenyu, LIN Xin, ZHAO Xuezhi, LIN Shoujin, LI Guochen. Research on Fault Diagnosis of Flexible Thinwall Bearings Based on PCA and Hilbert Spectrum[J]. Machine Tool & Hydraulics,2020,48(16):169-175

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  • 在线发布日期: 2020-09-08
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