| 杜 望,王衍学.基于协整和向量误差修正的轴承剩余寿命预测[J].电子测量与仪器学报,2020,34(9):32-39 |
| 基于协整和向量误差修正的轴承剩余寿命预测 |
| RUL prediction method for rolling bearing based on cointegration system and vector error correction |
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| DOI： |
| 中文关键词: 滚动轴承 协整理论 向量误差修正模型 剩余寿命预测 |
| 英文关键词:roller bearing cointegration system vector error correction model remaining useful life prediction |
| 基金项目:国家自然科学基金(面上)项目(51875032)、桂林电子科技大学研究生教育创新计划项目(2020YCXS014)资助 |
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| 中文摘要: |
| 针对传统机器学习出现“伪回归”问题,忽视非平稳序列间的长期依赖关系,提出协整理论和向量误差修正模型预测滚
动轴承的性能退化趋势,进而预测其剩余使用寿命(RUL)。 首先从振动信号中提取峭度值、峰峰值和均方根值,并分析其平稳
性。 然后检验 3 种时域特征的协整关系,根据检验结果来建立向量误差修正模型,并对模型进行残差分析,分析结果接近于高
斯白噪声分布,表明模型良好。 最后利用该模型预测轴承性能退化趋势和 RUL,并使用均方根误差(RMSE)、平均百分比误差
(MPE)、平均绝对百分比误差(MAPE)和 Theil 不等系数来定量评估预测结果。 实验结果表明,提出的向量误差修正模型相比
于差分平均移动自回归-卡尔曼滤波模型,具有更高的预测精度,并简化了建模过程。 |
| 英文摘要: |
| Aiming at the problem of “ pseudo regression” in traditional machine learning, ignoring the long-term dependence between
non-stationary sequences, the cointegration theory and vector error correction model were proposed to predict the performance degradation
trend of rolling bearings, and then predicted the remaining useful life (RIL). Firstly, extracted the kurtosis value, peak-to-peak value
and root mean square value from the vibration signal, and analyzed its stability. Then, tested the cointegration relationship of the time
domain features and established vector error correction models based on the test results, and performed the residual analysis. The
analysis results were close to the Gaussian white noise distribution, indicating that the models were good. Finally, used the models to
predict the bearing performance degradation trend and applied RUL, and RMSE, MPE, MAPE and the unequal coefficients of Theil to
quantitatively evaluate the prediction results. Experimental results show that the proposed vector error correction model has higher
prediction accuracy than the differential average moving autoregressive-Kalman filter model, and simplifies the modeling process. |
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