基于相关分析和Lempel-Ziv指标的轴承损伤程度识别
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TH17

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(国家自然科学基金资助项目(10772061)


Damage Degree Recognition of Bearing Based on Correlation Analysis and Lempel-Ziv Index
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    摘要:

    针对单一故障模式下轴承内、外圈损伤程度的区分问题,提出了一种基于相关分析的Lempel-Ziv指标评估方法。通过相关分析在保留信号中频率成分的基础上来降低信号中噪声对Lempel-Ziv指标的影响。首先,该方法对原始信号进行自相关分析,将信号进行降噪;其次,对降噪处理后的信号进行0-1编码,得到信号的编码序列;最后,对编码后的序列计算Lempel-Ziv指标,得到信号的复杂度。通过仿真和轴承故障实验数据验证了所提方法的有效性。与传统的Lempel-Ziv指标及滤波后的Lempel-Ziv指标相比,在噪声环境下,所提方法能较好地识别噪声中轴承故障信号的复杂程度,能够有效的区分单一故障模式下轴承内、外圈的损伤严重程度。

    Abstract:

    For the damage degree recognition of bearing inner and outer ring under the single failure mode, an evaluation method based on the Lempel-Ziv index and correlation analysis is proposed. The influence of noise on Lempel-Ziv index is reduced by correlation analysis on the basis of retaining frequency components in the signal. Firstly, the autocorrelation analysis of the original signal is used to reduce the noise component of the signal. Secondly, the coding sequence of the original signal is obtained by 0-1 encoding of the noise reduction signal. Finally the sequence after coding is used to calculate the Lempel-Ziv index to get the signal complexity. The effectiveness of the proposed method is verified by simulation and experimental data. Compared with the traditional Lempel-Ziv complexity and the Lempel-Ziv complexity after filtering, the proposed method can identify the bearing fault signal complexity in the noise environment, whic

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  • 在线发布日期: 2019-05-13
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