Fuel Cell Engine Fault Diagnosis Expert System based on Decision Tree

被引：0
|
作者：
Huang, Liang [1 ]
Zeng, Qi [1 ]
Zhang, Ruiming [2 ]
机构：
[1] Wuhan Univ Technol, Sch Automat, Wuhan, Hubei, Peoples R China
[2] Guangshun New Energy Power Technol Co Ltd Guangdo, Wuhan, Hubei, Peoples R China
来源：
PROCEEDINGS OF 2019 IEEE 3RD INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC 2019) | 2019年
关键词：
fuel cell engine; decision tree; fault diagnosis; expert system;
D O I：
10.1109/itnec.2019.8729556
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Under the general trend of industrial transformation, the development of fuel cell electric vehicles has gradually received attention. Aiming at the fault diagnosis of fuel cell engine, this paper proposes a diagnostic method combining C4.5-based decision tree with fault diagnosis expert system. After data preprocessing and feature selection, the training set is imported and the rules are stored in the knowledge base, and the faults are classified.
引用
收藏
页码：282 / 286
页数：5
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