|
|||||
|
|
| 基于VMD及广义分形维数矩阵的滚动轴承故障诊断 | |
| 引用本文： | 张淑清,邢婷婷,何红梅,董玉兰,张立国. 基于VMD及广义分形维数矩阵的滚动轴承故障诊断[J]. 计量学报, 2017, 38(4): 439-443. DOI: 10.3969/j.issn.1000-1158.2017.04.12 |
| 作者姓名： | 张淑清 邢婷婷 何红梅 董玉兰 张立国 |
| 作者单位： | 1.燕山大学 电气工程学院 河北省测试计量技术及仪器重点实验室, 河北 秦皇岛 066004 2.唐山工业职业技术学院, 河北 唐山 063000 3.河北省计量监督检测院, 河北 石家庄 0500515. 燕山大学电气工程学院 |
| 基金项目： | 国家自然科学基金（51475405,61077071）; 河北省自然科学基金(F2015203413, F2015203392) |
| 摘 要： | 提出基于变分模态分解及广义分形维数矩阵的滚动轴承故障诊断方法。对信号进行变分模态分解得到若干模态函数,根据不同权重因子计算得到每个模态函数的广义分形维数序列,排列构成广义分形维数矩阵,最后通过分析待测信号和各样本信号的广义分形维数矩阵的相关系数判断故障状态。实验结果表明该方法能精确、稳定提取故障特征,区分不同状态的信号。 |
| 关 键 词： | 计量学 轴承故障诊断 变分模态分解 广义分形维数 相关分析 |
| 收稿时间： | 2016-02-22 |
Bearing Fault Diagnosis Method Based on VMD and Generalized Fractal Dimension Matrix |
|
| ZHANG Shu-qing,XING Ting-ting,HE Hong-mei,DONG Yu-lan,ZHANG Li-guo,JIANG Wan-lu. Bearing Fault Diagnosis Method Based on VMD and Generalized Fractal Dimension Matrix[J]. Acta Metrologica Sinica, 2017, 38(4): 439-443. DOI: 10.3969/j.issn.1000-1158.2017.04.12 | |
| Authors: | ZHANG Shu-qing XING Ting-ting HE Hong-mei DONG Yu-lan ZHANG Li-guo JIANG Wan-lu |
| Affiliation: | 1. Key Lab of Measurement Technology and Instrumentation of Hebei Province, Institute of Electrical Engineering, Yanshan University, Qinhuangdao, Hebei 066004, China 2. Tangshan Polytechnic College, Tangshan, Hebei 063000, China 3. Hebei Institute of Metrological Supervision and Measurement, Shijiazhuang, Hebei 050051, China |
| Abstract: | A method of bearing fault diagnosis based on variational mode decomposition (VMD) and generalized fractal dimension was proposed. A number of mode functions were obtained through the decomposition to the signal by VMD method. Then the generalized fractal dimension of each mode functions were calculated according to the different weighting factors, and arranged to construct the generalized fractal dimension matrix. Finally, according to the correlation coefficient of the signals generalized fractal dimension matrix and the sample signals, the fault status could be diagnosed. The experiment results showed that the method could extract fault feature accurately and stably, and distinguish signals of different status and identify the faults with close frequency. |
| Keywords: | metrology bearing fault diagnosis variational mode decomposition generalized fractal dimension matrix correlation analysis |
| 本文献已被 CNKI 等数据库收录！ | |
| 点击此处可从《计量学报》浏览原始摘要信息 | |
| 点击此处可从《计量学报》下载全文 | |