首页> ISA transactions> A bimodal framework for nonstationary process monitoring via collaborative contrastive and adversarial unsupervised learning.

A bimodal framework for nonstationary process monitoring via collaborative contrastive and adversarial unsupervised learning.

导出 LinkOut

翻译打印收藏纠错

第一作者： Jian,Huang

第一单位： College of Intelligent Robotics and Advanced Manufacturing, Fudan University, Shanghai, 201203, China. Electronic address: jianhuang23@m.fudan.edu.cn.

作者： Jian,Huang ^[1] ; Hang,Ruan ^[2] ; Jianbo,Yu ^[3] ; Qingchao,Jiang ^[4] ; Xiaofeng,Yang ^[5]

作者单位： College of Intelligent Robotics and Advanced Manufacturing, Fudan University, Shanghai, 201203, China. Electronic address: jianhuang23@m.fudan.edu.cn. ^[1] College of Intelligent Robotics and Advanced Manufacturing, Fudan University, Shanghai, 201203, China. Electronic address: 23110860012@m.fudan.edu.cn. ^[2] School of Microelectronics, Fudan University, Shanghai, 201203, China. Electronic address: jb_yu@fudan.edu.cn. ^[3] Key Laboratory of Smart Manufacturing in Energy Chemical Process of Ministry of Education, East China University of Science and Technology, Shanghai, 200237, China. Electronic address: qchjiang@ecust.edu.cn. ^[4] School of Microelectronics, Fudan University, Shanghai, 201203, China. Electronic address: xf_yang@fudan.edu.cn. ^[5]

关键词 Bimodal framework Nonstationary process monitoring Pseudo-supervised contrastive learning Self-adversarial distribution constraint

DOI 10.1016/j.isatra.2025.12.006

PMID 41372074

发布时间 2025-12-10

翻译满意度评价：

准确一般字义偏差语意偏离译文作用小提交