Data flow analysis in automotive engine underpower fault detection

Jianke Liu; Zhikun Ming; Tianxi Yu

doi:10.1117/12.2671697

28 April 2023 Data flow analysis in automotive engine underpower fault detection

Jianke Liu, Zhikun Ming, Tianxi Yu

Proceedings Volume 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022); 126100L (2023) https://doi.org/10.1117/12.2671697
Event: Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 2022, Wuhan, China

Abstract

Due to the relative maturity of Data Flow (DF) analysis and research technology as well as the increasing number and development of diagnostic instruments, the automotive engine fault detection and diagnosis system is developing in the direction of precision, intelligence and multi-module diagnosis. In this paper, the fault detection system is designed for the problem of insufficient power of automobile engine. The ECU of automobile engine has the function of collecting the engine DF under various conditions in real time, and then reading out the relevant data during the driving process with the automobile fault diagnostic instrument, and the maintenance personnel combine them according to different requirements to form different data sets. The fault detection system also has the function of fault identification and prediction, and the best result of PSO-ELM algorithm is found by comparing the prediction accuracy of different algorithms. Here, it is hoped that the research in this paper will provide a reliable basis for analyzing and researching automotive engine faults.

Citation Download Citation

Jianke Liu, Zhikun Ming, and Tianxi Yu "Data flow analysis in automotive engine underpower fault detection", Proc. SPIE 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 126100L (28 April 2023); https://doi.org/10.1117/12.2671697

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