Research On Fault Diagnosis And Monitoring Assessment System Of EFI Automotive Based On Intelligent Learning

Automobiles have become an indispensable tool for people to travel on a daily basis.In the course of the operation of the on-board equipment,once the equipment failure occurs,if it cannot be timely and effectively repaired,it will seriously affect people's travel safety.It is a vital problem to be able to quickly diagnose faults in onboard equipment and ensure the normal operation of onboard equipment.In addition,with the development of wireless communication technology and network technology,real-time understanding of the current working state of the vehicle,the full use of sensor technology to detect on-board equipment,through accurate and effective reasoning analysis based on advanced models and improved methods,rapid and accurate fault diagnosis,prediction,decision analysis and status assessment of on-board equipment are realized.This has important practical significance for improving the safety,reliability,and added value of social benefits of the entire vehicle.This paper studies the fault diagnosis and decision-making assessment techniques for remote monitoring of automobiles.A light-duty petrol vehicle of the domestic brand is taken as the research object,and the corresponding design tasks for remote monitoring,fault diagnosis and decision-making evaluation of the vehicle are completed.From the aspects of theoretical knowledge,hardware,network design,modeling and simulation,experimental research and system implementation,the technology of remote monitoring fault diagnosis and decision evaluation system was systematically analyzed and studied.With regard to the implementation of comprehensive projects,this system provides new means for vehicle detection technology,and has certain theoretical and practical significance and reference value.The main research results obtained are:(1)Based on the OSI network model of intelligent vehicle remote monitoring and diagnosis and decision-making evaluation system design of the overall program and hardware modules,designed and developed device based on the CAN bus universal vehicle diagnostic communication interface,designed the various hardware modules.System communication is designed,a protocol stack based on CAN open protocol is established,and these fault signals are transmitted to the diagnostic system master chip in an orderly and timely manner through a dynamic priority scheduling algorithm.Analysis and study of the remote monitoring data transmission control strategy and server monitoring model,in order to realize the vehicle state information data exchange between the vehicle network and the remote server,established the data foundation for follow-up research.(2)A fault diagnosis method based on machine learning is proposed.Combine the idea of integration of informatization and industrialization to store fault information collected on the server after fault diagnosis.And the fault information collection and features are extracted.An improved reasoning fault diagnosis method model based on BNs classifier and a diagnostic analysis method model based on group decision tree optimization are proposed.The multi-model fusion was used to make a decision evaluation,and a method model based on group support was proposed.(3)Taking the electronically controlled gasoline engine as the research object,a general research on the automotive fault diagnosis technology is conducted.The gasoline engine sensor failure simulation test bench was completed,and a typical fault simulation platform device was designed and developed.Through experimental research,the main data under sensor failure mode was monitored and analyzed,and combined with the automotive fault diagnosis fusion model for scientific verification.The impact of typical faults on the economic performance and emission performance of the vehicle was analyzed,and get accurate and highly reliable fault classification assessment result data and diagnosis decisions.(4)Designed and developed a remote fault diagnosis and monitoring and evaluation system,designed the functional structure of the system,improved the system architecture through an object-oriented design method.Established a diagnostic evaluation system method,and designed a scheme based on knowledge base and inference engine to analyze and evaluate expert knowledge and experience.Designed and developed a system database,use related data for testing,and verified the stability and rapid accuracy of the equipment alarm node and system communication delay.