Research On Intelligent Fault Diagnosis And Maintenance System Based On Digital Auto Fast Repair

The rapid development of the auto industry for the automotive service industry ushered in a huge space for development,in the entire automotive industry chain,the market share of the automotive service market is getting higher and higher.As the new auto technology is endless,traditional auto fault diagnosis and maintenance methods are difficult to solve the current system and structure of the increasingly complex auto failure,leading to the difficulty of auto maintenance is growing.In recent years,car fast repair chain as a new type of car service model,by virtue of its own convenient advantages in the country has been rapid development.However,the efficiency of fault diagnosis of auto fast repair enterprises in China is low and the quality of service is poor.Therefore,it is very important to apply effective tools and methods to eliminate auto failure and improve the quality of auto maintenance service in a timely manner.After summarizing the current research situation of intelligent fault diagnosis and maintenance technology,this paper analyzes and compares the advantages and disadvantages of each diagnostic method.Based on this,a case-based reasoning method based on qualitative and quantitative transformation of triangular fuzzy number is proposed,and a hybrid intelligent fault diagnosis and maintenance method for auto quick repair is combined with rule reasoning.For CBR,this paper focuses on the organizational structure of the case database and the case search strategy;the failure case library is divided into representative case database and sub-case library;Using the shortest distance clustering algorithm to optimize the fault case retrieval strategy to improve the retrieval efficiency and accuracy.Aiming at the quantization of the fuzzy attribute of the symptom of the fault case,the triangular fuzzy number is used to digitize it,and the attribute is normalized by the normalized utility function.For the case attribute with hierarchical relation,this paper uses semantic similarity method to calculate the similarity between attributes.Finally,the nearest neighbor algorithm is used to retrieve the historical case according to the set threshold,and its solution is used to solve the current auto fault.For the RBR,the rules of the representation and storage methods,collection,sorting out the rules of nearly a thousand,to complete the rule of reasoning strategy.And finally combines the Case-Based Reasoning and Rule-Based Reasoning two kinds of intelligent fault diagnosis and maintenance technology,so that it can give full play to the case of reasoning fast and efficient advantages,but also in the case of Case-Based Reasoning failure to continue to use the rule of reasoning method to exclude the auto malfunction.Based on the field investigation of auto repair enterprises,the requirements of the system were analyzed,based on the modularization of ideas,in the digital auto fast repair platform,combined with automotive marketing management subsystem,the use of Microsoft Visual Stdio 2010 development tools,MySQL database,C ++ for the programming language developed based on hybrid reasoning intelligent fault diagnosis and maintenance assistance system.Through the trial results show that the system can accurately and quickly diagnose the causes of the auto failure,shorten the time of auto fault diagnosis and maintenance,standardize the maintenance steps,provide the customers with reasonable and transparent maintenance price according to the information of the auto fault symptom,and combine with the digital auto fast Repair platform under the auto marketing subsystem,the overall increase in the quality of automotive after-sales service.