天津科技大学学报2023，Vol.38Issue(6)：62-68,7.DOI:10.13364/j.issn.1672-6510.20230003
基于EMD和改进TCN的滚动轴承剩余寿命预测方法
Prediction Method of Remaining Life of Rolling Bearing Based on EMD and Improved TCN
胡勇 1李孝忠1
作者信息
- 1. 天津科技大学人工智能学院,天津 300457
- 折叠
摘要
Abstract
Considering that in the current field of predicting the remaining useful life of rolling bearings,it is difficult to extract effective features from bearing vibration data,the data dimension is small and difficult to meet the demand,and the prediction model tends to become complex,resulting in high computational costs.Therefore,in this article we propose a feature extraction method based on empirical mode decomposition(EMD)and a residual life prediction method based on improved temporal convolutional network(TCN),and also validate it on the PHM 2012 bearing dataset.The experimental results showed that the improved temporal convolution network reduced the mean squared error(MSE)index by 46.43%compared with other temporal convolution networks,and increased the score function index by 4.06%compared with other temporal convolution networks.Moreover,the improved temporal convolutional network in our study reduced the MSE by 84.74%compared to the other four model methods.Compared to its four model methods,the score index increased by 163%.The experimental result fully verifies the effectiveness of improving the TCN model in the article.关键词
剩余使用寿命预测/滚动轴承/时间卷积网络/经验模态分解Key words
remaining useful life prediction/rolling bearing/temporal convolutional network/empirical mode decom-position分类
信息技术与安全科学引用本文复制引用
胡勇,李孝忠..基于EMD和改进TCN的滚动轴承剩余寿命预测方法[J].天津科技大学学报,2023,38(6):62-68,7.
