基于废气排放和工况参数信息融合的内燃机失火故障诊断

I.C. Engine misfire faults diagnosis based on information fusion for exhaust emission and work parameters

提出一种利用内燃机排气中HC,CO2,O2浓度和内燃机工况参数信息融合的内燃机失火故障诊断方法,并提出描述内燃机失火程度的模糊评价指标,进行内燃机有失火故障和无故障排气成分检测对比实验,通过RBF神经网络建立失火程度评价指标与排气中HC,CO2,O2浓度以及内燃机工况参数之间关系的诊断模型.仿真分析结果表明,此模型能正确诊断内燃机失火故障.

An information fusion method for misfire faults diagnosis of internal combustion engine with exhaust density of HC, CO2, O2 and an engine＇s operation parameters are presented in this paper. And fuzzy describing the misfire degree is also introduced. The engine＇s exhaust emission with misfire fault and without fault is tested. A diagnosis model which describing the relationship between the misfire degree, the exhaust emission and some operation parameters is established based on Radial Basis Function （RBF） neural network. Simulation results show that the diagnosis model can be used to diagnose internal combustion engine misfire faults.