Research On Intelligent Detection And Diagnosis System Of Diesel Vehicle Exhaust

With the continuous development of society,the number of motor vehicles in China is increasing year by year.Traditional fuel vehicles still dominate the market,are the main contributor to automotive pollutant emissions,especially the diesel vehicles with substandard emission.At present,the "I/M" system has entered the stage of comprehensive and systematic construction,but most maintenance stations have excessive maintenance during the inspection and maintenance process,which does not meet the requirements of the "I/M" system.It is difficult to form a "inspectionmaintenance-recheck" closed-loop control for vehicles with unqualified emissions,and unable to guarantee the qualified emission of vehicles running on the road.In view of the above problems,this paper develops an intelligent detection and diagnosis system for diesel vehicle exhaust,proposes to use GA-BP neural network algorithm to intelligently diagnose diesel vehicle faults,and finally designs a diagnostic system,which verifies the stability and accuracy of the system through real vehicle testing,and the specific research work is as follows:Experiments and simulations study the sensitivity of exhaust gases to different influencing factors.The loading deceleration method and the free acceleration method were used to obtain emission parameters.The simulation method simulates the diesel engine fault,establishes the diesel engine combustion simulation model,uses the model to simulate the failure that is difficult to achieve in the experiment,verifies the fault model,and analyzes the sensitivity of diesel vehicle exhaust to different influencing factors according to the experimental and simulation data.A diesel vehicle fault diagnosis model based on GA-BP neural network was established.A traditional BP neural network diagnosis model and a GA-BP neural network diagnosis model were established respectively,and the diagnostic performance of the two neural networks was compared.It was concluded that GA-BP neural network had better diagnostic performance and was more suitable for application in diesel vehicle fault diagnosis.An intelligent diesel vehicle exhaust gas detection and diagnosis system was developed,and experiments were designed to verify the stability and accuracy of the diagnosis system.It was proved that the system can operate stably and diagnose diesel vehicle faults in real time using the detection data.This paper provides a new scheme for intelligent diagnosis of diesel vehicles using exhaust gas data.First of all,the system can reduce the workload of maintenance and diagnosis personnel.Secondly,based on GA-BP neural network algorithm diagnosis,the system can gradually improve the accuracy of diagnosis and realize intelligent diagnosis by continuously obtaining the sample library.At the same time,the system can also provide technical support for the vehicle emission performance maintenance station,enhance its maintenance function,promote the implementation of the "I/M" system,and help the country to achieve the goal of "carbon peak,carbon neutral" as soon as possible.