| 改进的正弦辅助多元经验模式分解及其在滚动轴承故障诊断中的应用 |
| |
| 引用本文： | 吴利锋,吕勇,袁锐,朱熹,游俊.改进的正弦辅助多元经验模式分解及其在滚动轴承故障诊断中的应用[J].中国机械工程,2022,33(11):1336-1344. |
| |
| 作者姓名： | 吴利锋 吕勇 袁锐 朱熹 游俊 |
| |
| 作者单位： | 1.武汉科技大学冶金装备及其控制教育部重点试验室，武汉,430081
2.武汉科技大学机械传动与制造工程湖北省重点试验室，武汉,430081 |
| |
| 基金项目： | 国家自然科学基金（51875416）；湖北省自然科学基金创新群体项目（2020CFA033）；中国博士后科学基金（2020M682492） |
| |
| 摘 要： | 正弦辅助多元经验模式分解算法（SA-MEMD）通过在额外的通道中加入正弦辅助信号来减少模式混合，但该算法对噪声敏感，辅助信号的主频率比需要根据经验确定，为此，提出了一种改进的正弦辅助多元经验模式分解算法。首先使用非局部均值降噪对原始信号进行预处理，减少噪声对算法的干扰，其次使用短时傅里叶变换确定信号频谱范围，然后以最小集成EMD能量熵准则选择最优主频率比，最后根据正弦辅助多元经验模式分解算法的步骤进行信号处理。模拟信号和实际信号的对比分析结果证明，改进的方法可以减少传统的多元经验模式分解方法存在的模式混合现象。
|
| 关 键 词： | 故障诊断 正弦辅助多元经验模式分解 模式混合 短时傅里叶变换 能量熵 |
Improved SA-MEMD with Applications to Fault Diagnosis of Rolling Bearings |
| |
| WU Lifeng,LYU Yong,YUAN Rui,ZHU Xi,YOU Jun.Improved SA-MEMD with Applications to Fault Diagnosis of Rolling Bearings[J].China Mechanical Engineering,2022,33(11):1336-1344. |
| |
| Authors: | WU Lifeng LYU Yong YUAN Rui ZHU Xi YOU Jun |
| |
| Affiliation: | 1.The Key Laboratory of Metallurgical Equipment and Control of Education Ministry,Wuhan University of Science and Technology,Wuhan,430081
2.Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering,Wuhan University of Science and Technology,Wuhan,430081 |
| |
| Abstract: | The SA-MEMD algorithm reduced mode mixing by adding a sine assisted signal to an additional channel, but the algorithm was sensitive to noises, and the main frequency ratio of the auxiliary signals needed to be determined empirically. For this reason, an improved SA-MEMD was proposed. First, The non-local mean noise reduction was used to preprocess the original signals to reduce noise interference for the algorithm, then the short-time Fourier transform was used to determine the signal spectrum range, thus the optimal main frequency ratio was selected based on the minimum ensemble EMD energy entropy criterion. The steps of the SA-MEMD algorithm were used to complete signal processing. The analysis of simulation signals and actual signals proves that the improved method may alleviate the mode mixing phenomenon that exists in the traditional multivariate empirical mode decomposition methods. |
| |
| Keywords: | fault diagnosis sine-assisted multivariate empirical mode decomposition(SA-MEMD) modal aliasing short-time Fourier transform energy entropy |
|
| 点击此处可从《中国机械工程》浏览原始摘要信息 |
|
点击此处可从《中国机械工程》下载全文 |
