AI-Enabled Monitoring, Diagnosis & Prognosis

作     者：Ruqiang Yan Xuefeng Chen Weihua Li Robert X.Gao Ruqiang Yan;Xuefeng Chen;Weihua Li;Robert X.Gao

作者机构：School of Mechanical EngineeringXi’an Jiaotong UniversityXi’an 710049China SHIEN-MING WU School of Intelligent EngineeringSouth China University of TechnologyGuangzhou 510641China Department of Mechanical and Aerospace EngineeringCase Western Reserve UniversityClevelandOhio 44106-7222USA 

出 版 物：《Chinese Journal of Mechanical Engineering》 (中国机械工程学报（英文版）)

年 卷 期：2021年第34卷第3期

页      面：1-2页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0802[工学-机械工程] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：diagnosis prognosis bringing 

摘      要：The emerging and development of Artificial Intelligence(AI),especially deep learning,has stimulated its application in various engineering ***,diagnosis and prognosis,as the key elements of intelligence maintenance of manufacturing systems in the era of Industry 4.0,has also benefited from the advancement of AI *** main objective of this special issue aims at bringing scholars to show their research findings in the field of monitoring,diagnosis and prognosis driven by AI,and promote its application in intelligent maintenance of manufacturing system in *** papers have been selected in this special issue after rigorous review and they represent the latest research outcomes in this active area.