柴油车尾气智能检测诊断系统设计

黄万友，邹于建，谭世威，郭雅晶，褚瑞霞，刘冬影

山东交通学院汽车工程学院，山东 济南  250357

摘要：为提高柴油车排放超标故障诊断的准确率，基于改进的GA-BP神经网络模型，以加载减速法和自由加速法获取的实车检测尾气数据作为诊断依据，设计一种柴油车尾气智能检测诊断系统，并进行实车试验，测试诊断准确率。结果表明：设计的柴油车智能诊断系统柴油车排放超标故障诊断准确率为95%，更新学习时间约为10 min。该智能诊断系统大幅提高了柴油车排放超标故障诊断准确率，实现智慧诊断。

关键词：柴油车尾气检测；柴油车故障诊断；GA-BP神经网络

Design of intelligent detection and diagnosis system fordiesel vehicle exhaust

HUANG Wanyou, ZOU Yujian, TAN Shiwei, GUO Yajing, CHU Ruixia, LIU Dongying

School of Automotive Engineering, Shandong Jiaotong University, Jinan 250357, China

Abstract：In order to improve the accuracy of fault diagnosis of diesel vehicle emissions, based on the improved GA-BP neural network model, a diesel vehicle exhaust detection and diagnosis system is designed based on the real vehicle detection exhaust data obtained by loading deceleration method and free acceleration method, and the real vehicle experiment is carried out to test the diagnostic accuracy. The results show that the designed intelligent diagnosis system for diesel vehicles has high accuracy of 95%, and short system update time of 10 minutes. It has greatly improved the accuracy of fault diagnosis of diesel vehicle emissions exceeding standards, realized intelligent diagnosis.

Keywords:diesel vehicle exhaust gas detection; diesel vehicle fault diagnosis; GA-BP neural network