基于异构知识蒸馏网络的滚动轴承剩余寿命预测  

Remaining Useful Life Prediction of Rolling Bearings Based on Heterogeneous Knowledge Distillation Network

作　　者：徐超[1,2] 汪永超 李世昌[1,2] 李翰儒 XU Chao;WANG Yongchao;LI Shichang;LI Hanru(School of Mechanical Engineering,Sichuan University,Chengdu 610065,China;Yibin Industrial Technology Research Institute,Sichuan University,Yibin 610064,China)

机构地区：[1]四川大学机械工程学院,成都610065 [2]宜宾四川大学产业技术研究院,宜宾610064

出　　处：《组合机床与自动化加工技术》2024年第8期154-157,162,共5页Modular Machine Tool & Automatic Manufacturing Technique

基　　金：国家自然科学基金资助项目(51875370)。

摘　　要：针对滚动轴承寿命预测中预测精度低和边缘设备资源有限等问题,提出了一种异构知识蒸馏网络来预测滚动轴承的剩余使用寿命。网络使用教师—学生知识蒸馏架构,首先引入自注意力机制与长短时记忆网络融合构建了一个预测精度较高的教师模型;其次,在卷积神经网络的基础上引入变分自动编码器构建了一个特征提取能力较强、参数量较少、复杂度较低的学生模型;然后,设计了一个复合损失函数,用于训练学生模型对教师模型知识的吸收能力和对训练数据的适应能力;最后,在XJTU-SY轴承数据集上进行寿命预测实验。结果表明,与其他预测方法相比,所提方法能有效降低模型的参数量和复杂度并且预测精度更高。Aiming at the problems of low prediction accuracy and limited resources of edge equipment in rolling bearing life prediction,a heterogeneous knowledge distillation network is proposed to predict the remaining useful life of rolling bearings.The network uses a teacher student knowledge distillation architecture.Firstly,the network introduces the self-attention mechanism and the long-term short-term memory network to construct a teacher model with high prediction accuracy.Secondly,on the basis of convolutional neural network,a variational auto-encoder is introduced to construct a student model with strong feature extraction ability,less parameter quantity and lower complexity.Then,a composite loss function is designed to train the absorption ability of the student model to the knowledge of the teacher model and the adaptability to the training data.Finally,the life prediction experiment is carried out on the XJTU-SY bearing dataset.The results show that compared with other prediction methods,the proposed method can effectively reduce the number and complexity of model parameters and have higher prediction accuracy.

关 键 词：滚动轴承 剩余使用寿命 知识蒸馏 自注意力机制 变分自动编码器 

分 类 号：TH133.3[机械工程—机械制造及自动化] TG66[金属学及工艺—金属切削加工及机床]