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基于时频域信号优化器的Mi-MkTCN轴承寿命预测模型

刘毅 高雪莲 李一弘 王永琦 孔玲丽 康立军

现代制造工程Issue(2):117-128,12.
现代制造工程Issue(2):117-128,12.DOI:10.16731/j.cnki.1671-3133.2026.02.015

基于时频域信号优化器的Mi-MkTCN轴承寿命预测模型

Mi-MkTCN bearing remaining useful life prediction model based on time frequency domain signal ratio optimizer

刘毅 1高雪莲 1李一弘 1王永琦 1孔玲丽 2康立军2

作者信息

  • 1. 华北电力大学电气与电子工程学院,北京 102206
  • 2. 北京博纳电气股份有限公司,北京 102206
  • 折叠

摘要

Abstract

Rolling bearings were recognized as common key components in mechanical equipment.Accurate prediction of their re-maining service life was considered crucial for safe and stable operation.A Multi inflated Multi kernel Time Convolutional Net-work(Mi-MkTCN)model was proposed to address current challenges in bearing life prediction.The model was based on a Time-Frequency domain signal Ratio Optimizer(TFRO).Three main problems were targeted:unclear bearing degradation characteris-tics,poor model generalization ability,and difficulty in capturing long-term data dependencies.The TFRO optimizer was designed to accurately retain important information.At each time node,past and current information were reassembled.Important time-fre-quency domain features from past information were proportionally allocated.Multiple dilation methods were employed in Mi-MkTCN to prevent loss of important features.A multi-kernel temporal convolutional network was then used to extract features at different scales.The effectiveness of the proposed model improvement method was demonstrated through ablation experiments.Al-gorithm comparison studies were conducted to verify the superiority of the TFRO-based Mi-MkTCN model.Performance metrics were recorded as follows:MAE(0.001 45),MSE(0.050 69),and RMSE(0.120 45).The experimental results showed that the proposed method significantly improved the prediction accuracy of the remaining service life of bearings,providing a high-precision and highly robust solution for predicting the remaining service life of bearings.

关键词

时频域信号比例优化器/精准记忆TPA/多重膨胀/多核时间卷积网络/轴承剩余使用寿命预测

Key words

Time-Frequency domain signal Ratio Optimizer(TFRO)/precision memory TPA/multi inflated/Multi inflated Multi kernel Time Convolutional Network(Mi-MkTCN)/prediction of remaining useful life of bearings

分类

机械制造

引用本文复制引用

刘毅,高雪莲,李一弘,王永琦,孔玲丽,康立军..基于时频域信号优化器的Mi-MkTCN轴承寿命预测模型[J].现代制造工程,2026,(2):117-128,12.

基金项目

国家自然科学基金青年基金项目(62401205) (62401205)

现代制造工程

1671-3133

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