摘要
针对单一源域信息有限、域自适应对齐粒度不足导致滚动轴承剩余寿命(remain useful life,RUL)预测精度低的问题,提出了一种多源域子域自适应(multi-source subdomain adaption network,MS_SAN)的滚动轴承剩余寿命预测方法。首先,将采集的原始振动信号进行快速傅里叶变换得到频域信号作为模型的输入。其次,利用一维卷积将多个源域与目标域数据映射到一个公共的特征空间,采用局部最大均值差异将每个源域与目标域的退化阶段在独立的特征空间进行领域自适应,缩小多个源域与目标域之间的分布差异。最后,通过综合各领域RUL预测模块的输出得到最终轴承剩余寿命预测结果。在PHM2012数据集上的测试结果表明该方法的预测准确率高于对比方法,能够对滚动轴承剩余寿命进行有效的预测。
To address the problem that low accuracy of rolling bearing remain useful life(RUL)prediction caused by the limited information of single source domain and the insufficient granularity of domain,a new method of RUL for rolling bearing based on multi-source subdomain adaption network is proposed.Firstly,fast fourier transform is applied to the collected raw vibration signals to obtain the frequency-domain signals and it takes the frequency-domain signals as the input of the model.Secondly,to reduce the distribution difference between multiple source domains and target domains,all domains are mapped to a common feature space by one-dimensional convolution,and the local maximum mean discrepancy is used to align the degradation stage of each source domain and target domain in an independent feature space.Finally,the RUL of rolling bearing is obtained by comprehensive output of the module in different domains.The results on PHM2012 data set show that the prediction accuracy of proposed method is higher than the comparison method,and can effectively predict the RUL of rolling bearing.
作者
黄庆卿
胡欣堪
韩延
林志超
张焱
Huang Qingqing;Hu Xinkan;Han Yan;Lin Zhichao;Zhang Yan(Automation College,Chongqing University of Posts and Telecommunications,Chongqing 400065,China;Institute of Industrial Internet,Chongqing University of Posts and Telecommunications,Chongqing 401120,China)
出处
《电子测量与仪器学报》
CSCD
北大核心
2022年第10期100-107,共8页
Journal of Electronic Measurement and Instrumentation
基金
国家自然科学基金(51605065)
重庆市博士后科学基金(cstc2021jcyj-bshX0094)
重庆市教委科学技术研究(KJQN202100612,KJQN202000611)项目资助
