| 陈 剑,夏 康,黄凯旋,刘幸福.基于 VMD 相对能量熵和自适应 ARMA模型的轴承性能退化趋势动态预警[J].电子测量与仪器学报,2020,34(8):116-123 |
| 基于 VMD 相对能量熵和自适应 ARMA模型的轴承性能退化趋势动态预警 |
| Dynamic prediction of bearing performance degradation trend based on VMD relative energy entropy and adaptive ARMA model |
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| DOI： |
| 中文关键词: 变分模态分解 相对能量熵 ARMA 模型 滚动轴承 性能退化 |
| 英文关键词:variational mode decomposition relative energy entropy ARMA model rolling bearing performance degradation |
| 基金项目:国家自然科学基金青年基金(11604070)、安徽省科技重大专项(17030901049)资助 |
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| 中文摘要: |
| 为了有效监测滚动轴承性能退化趋势及其指标异常波动,提出了一种基于变分模态分解(VMD)的相对能量熵和自回
归滑动平均(ARMA)模型的滚动轴承性能退化趋势动态预警方法。 方法利用 VMD 对滚动轴承寿命数据进行分解,得到有限带
宽固有模态函数(BLIMFs);对该 BLIMFs 分量的能量进行相对熵分析,提取滚动轴承性能退化特征,得到 VMD 相对能量熵的轴
承性能退化评估指标;该相对能量熵值作为输入供 ARMA 模型进行动态回归预测。 试验结果表明,该方法能有效监测滚动轴
承性能退化趋势、指标的异常波动,验证了所提方法的有效性。 |
| 英文摘要: |
| In order to effectively monitor the rolling bearing performance degradation trend and its abnormal fluctuations, a dynamic early
warning method of rolling bearing performance degradation trend based on the relative energy entropy of variational mode decomposition
(VMD) and the adaptive ARMA model is proposed. Methods VMD was used to decompose the life data of rolling bearing to obtain bandlimited intrinsic mode functions (BLIMFs). The energy of the BLIMFs component is analyzed by relative entropy, and the characteristics
of rolling bearing performance degradation are extracted to obtain the bearing performance degradation evaluation index of VMD relative
energy entropy. The energy entropy value extracted by VMD decomposition is used as an input for ARMA model for dynamic regression
prediction. The test results show that this method can effectively monitor the degradation trend of rolling bearing performance and the
abnormal fluctuation of indexes, and verify the effectiveness of the proposed method. |
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