Study Of Diesel Engine Fault Diagnosis Technique Based On Genetic Neural Network

Based on the analysis of domestic and foreign research about intelligent diagnosis technology and fault diagnosis methods of diesel engine,a method of diesel engine fault diagnosis based on genetic neural network is given in this paper.The fault diagnosis of fuel system is deeply studied.Firstly,the research status of fault diagnosis technology and contents of the topic have been discussed briefly in this paper;several popular methods of diesel engine fault diagnosis are introduced;the shortcoming of neural network in fault diagnosis is analysized.Secondly,for shortcomings of slow convergence rate and falling into local minimum easily of BP neural network,genetic algorithm and neural network are combined.Using the global search ability of genetic algorithm,initial weights and thresholds of neural network are optimized and the two inherent shortcomings of network are solved,which has enhanced the accuracy and rapidity of neural network in fault diagnosis.Lastly,simulation test is carried on by the MATLAB,the network is constructed and trained using typical fault data of fuel system as genetic neural network training samples and simulation fault is diagnosed and analysized.The simulation results show that the fault diagnosis result based on genetic neural network is well consistent with measured values.As long as we choose enough typical initial fault samples to train genetic neural network,the stability of network is better.The method of fault pattern recognition based on genetic neural network can fully use information characteristics, achieve mapping relation between input and output and get accurate result.