基于增强自适应盲解卷积方法的齿轮故障诊断

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摘要针对最小熵解卷积（Minimum Entropy Deconvolution, MED）在故障诊断中倾向于恢复少量伪主导冲击以及依赖经验选取滤波器长度的问题，提出了一种增强自适应盲解卷积方法。该方法设计一种非线性变换以增强滤波信号中的故障冲击特征，并将其融入滤波器系数的迭代求解中，从而解决MED因少量伪主导冲击造成峭度过大而无法有效恢复周期性故障冲击的问题。同时，所提方法提供一种可根据待分析信号自适应获得合适滤波参数的策略，进而克服传统依赖经验取值的不足。仿真信号与齿轮植入故障信号分析结果验证方法对于增强故障冲击及自适应选取滤波参数的有效性，实现周期性故障冲击的准确恢复。在列车齿轮故障诊断的工程实际案例中，所提方法准确诊断出齿轮传动系统中大齿轮的早期裂纹故障。与MED的对比研究，进一步表明所提方法在故障冲击增强与自适应恢复方面的优势。

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	吴磊1
	张新1
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	王家序1
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	赵艺珂1
	刘治汶3
	王磊4

关键词 ：齿轮故障诊断, 自适应盲解卷积, 非线性变换, 故障特征增强

Abstract：Aiming at addressing the problems that minimum entropy deconvolution (MED) tends to restore a few pseudo-dominant impulses and determines the filter length empirically in fault diagnosis, an enhanced and adaptive blind deconvolution method is proposed in this paper. A nonlinear transformation is designed to process the filtered signal so as to enhance the fault impulses, and then the filter coefficients are estimated by maximizing the kurtosis of the processed signal. In this context, it can avoid attaining unsuitable filter coefficients due to excessively large kurtosis caused by a few pseudo-dominant impulses. Meanwhile, this method provides a strategy for adaptively obtaining the filter parameters according to the signal to be analyzed, and overcomes the drawback that depends on experience. The analysis results of simulated signals and gear seeded-fault signal verified the effectiveness of the method. In engineering applications, the method successfully diagnosed the incipient gear crack damage in a train transmission system, and showed great superiority over the traditional MED in enhancing and adaptively restoring the periodic fault impulses.

Key words： gear fault diagnosis adaptive bind deconvolution nonlinear transformation fault impulse enhancement

收稿日期: 2022-01-10 出版日期: 2023-04-15

引用本文:

吴磊1,张新1,2,王家序1,2,赵艺珂1,刘治汶3,王磊4. 基于增强自适应盲解卷积方法的齿轮故障诊断[J]. 振动与冲击, 2023, 42(7): 123-132.
WU Lei1, ZHANG Xin1,2, WANG Jiaxu1,2, ZHAO Yike1, LIU Zhiwen3, WANG Lei4. Gear fault diagnosis based on enhanced and adaptive blind deconvolution method. JOURNAL OF VIBRATION AND SHOCK, 2023, 42(7): 123-132.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2023/V42/I7/123

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