基于FNN-GA融合算法的喷油器在线诊断

On-Line Diagnosis of the Injector Based on FNN-GA

依据喷油器开启信号波形的变化规律,探讨了柴油机喷油器故障的产生机理,提出了波形幅度、上升沿宽度和波形宽度等诊断指标。基于模糊推理逻辑和喷油器的工作机理,建立了模糊神经网络(fuzzy neural network,简称FNN)与遗传算法(genetic arithmetic,简称GA)相结合的柴油机喷油器故障诊断模型。以喷油器开启信号的特征参数为基准,建立了故障隶属度和故障类型,制定了柴油机喷油器故障诊断的模糊推理逻辑。运用FNN-GA融合算法,依据不同故障的喷油器开启信号对喷油器故障进行了诊断,对故障模式进行了判别,提出了柴油机喷油器故障的在线诊断策略,并进行喷油器电磁阀驱动电流的故障试验。结果表明,所设计的柴油机喷油器故障诊断模型合理,验证了诊断策略具有较好的分辨率,可用于喷油器故障在线诊断。

The fault process of the injector has been discussed according to the variation laws of its start signal wave,the diagnostic parameters are put forward,such as waveform amplitude,the width of rising edge and breadth of waveform.The diesel engine injector fault diagnosis model,which containes fuzzy neural network(FNN) and the genetic arithmetic(GA),is established based on fuzzy logic reasoning and working mechanical of the injector.The fault type is also established according to characteristic parameters of the injector start signal,and the fuzzy logic reasoning of diesel engine injector fault diagnosis is put forward.Based on different fault injector start signals and FNN-GA fusion algorithm,the injector fault model is diagnosed and identified,the on-line diagnostic strategy of diesel engine injector fault is put forward and the fault tests on drive current of the injector are carried out.The results show that the diesel engine injector fault diagnosis model is reasonable;the RBF-GA diagnostic strategy has the good resolving power and can be fitted for the on-line diagnosis of the injector fault.