电子测量与仪器学报

吴家腾,李威,方志超,童成彪,徐新明.基于物理模型驱动优化 WPD 的弧齿锥齿轮故障诊断方法研究[J].电子测量与仪器学报,2023,37(8):214-222

基于物理模型驱动优化 WPD 的弧齿锥齿轮故障诊断方法研究

Fault diagnosis method of spiral bevel gear based on physical model driven optimal WPD

DOI：

英文关键词:spiral bevel gear fault diagnosis dynamic modeling wavelet packet decomposition

基金项目:湖南省教育厅科研优秀青年(22B0199)、湖南省自然科学基金(2021JJ30347)、湖南省重点研发计划(2022NK2028)项目资助

作者	单位
吴家腾	1.湖南农业大学机电工程学院
李威	1.湖南农业大学机电工程学院
方志超	1.湖南农业大学机电工程学院
童成彪	1.湖南农业大学机电工程学院
徐新明	1.湖南农业大学机电工程学院

Author	Institution
Wu Jiateng	1.College of Mechanical and Electrical Engineering, Hunan Agricultural University
Li Wei	1.College of Mechanical and Electrical Engineering, Hunan Agricultural University
Fang Zhichao	1.College of Mechanical and Electrical Engineering, Hunan Agricultural University
Tong Chengbiao	1.College of Mechanical and Electrical Engineering, Hunan Agricultural University
Xu Xinming	1.College of Mechanical and Electrical Engineering, Hunan Agricultural University

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中文摘要:

弧齿锥齿轮作为收获机主动力输出的关键零部件,其故障表现通常为激励脉冲,为实现农业收获机主传动齿轮箱故障及时有效地监测诊断,本文提出基于物理模型驱动优化的小波包分解方法(wavelet packet decomposition, WPD)。针对齿轮损伤的多分量调制现象,该方法根据小波基函数特定时频窗口分析信号的特点,通过建立齿轮损伤集中参数模型,辅助筛选适应齿轮损伤特性的小波包分解系数,以此优化分解信号所选用的小波基函数,使之具有更好的提取齿轮故障特征信息的能力。通过对实验信号和藠头收获机齿轮故障信号的包络谱分析,验证了该方法能够有效地应用于收获机齿轮故障诊断。

英文摘要:

As a key component of the main power output of harvester, the fault performance of the spiral bevel gear is usually the excitation impulse. To monitor and diagnose the faults of the main transmission gearbox of agricultural harvester timely and effectively, an improved wavelet packet decomposition ( WPD) method based on dynamic model driven optimization is proposed in this paper. Aiming at the multi-component modulation phenomenon of gear damage and the characteristics of wavelet basis function specific timefrequency window to analyze the signal, the proposed method establishes the physical model of gear dynamic damage to assist in screening of wavelet packet decomposition coefficients that adapt to the gear damage characteristics. Thus, the wavelet basis function selected for the decomposed signal is optimized, so that it has a better ability to extract feature information of gear fault. Through the envelope spectrum analysis of the experimental signal and fault signal of the Chinese onion harvester gear, it is verified that the proposed method can be effectively applied to the fault diagnosis of the harvester gear.

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