Fuel Cell Engine Fault Diagnosis Expert System based on Decision Tree
Liang Huang, Qi Yong Zeng, Ruiming Zhang · 2019 IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC) · 2019
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.