A novel multi-channel CNN-LSTM and transformer-based network for diesel engine misfire diagnosis under different noise conditions

作     者：LI Ou LEI JunBo QIN ChengJin ZHANG ZhiNan TAO JianFeng LIU ChengLiang 

作者机构：State Key Laboratory of Mechanical System and VibrationSchool of Mechanical EngineeringShanghai Jiao Tong UniversityShanghai 200240China 

出 版 物：《Science China(Technological Sciences)》 (中国科学（技术科学英文版）)

年 卷 期：2024年第67卷第9期

页      面：2965-2967页

核心收录：

学科分类：080703[工学-动力机械及工程] 08[工学] 0807[工学-动力工程及工程热物理] 

基　　金：supported by the National Key R&D Program of China(Grant No.2023YFB3408502) Shanghai Municipal Science and Technology Major Project(Grant No.2021SHZDZX0102) 

主　　题：Diesel diagnosis network 

摘      要：Misfire fault, as a major fault of diesel engines, usually occurs because of low fuel quality, insufficient compression, ignition system failure, *** engines may experience issues such as reduced power, increased fuel consumption, and increased noise when misfire happens. Therefore, timely detection and diagnosis of diesel engine misfire faults are of great significance in the industry [1].