基于案例信息检索的汽车故障诊断系统的构建

Construction of Vehicle Fault Diagnosis System Based on Case Information Retrieval

传统车辆维修养护诊断模式依赖于人工经验和配套设备,已经适应不了汽车更新换代的速度,迫切需要更高效更智能的定位故障、快速检修技术来提升车辆安全性和可靠性,从而诞生了车辆故障诊断技术这个综合性学科。文章通过基于人工智能设计思想,采用大量的维修实例可以作为系统的训练样本,应用最新信息技术完成汽车故障认知诊断系统的设计与实现,为用户提供一个高效简便的故障诊断平台,为专业维修人员解决汽车故障、对汽车维修提供依据,经实验测试,系统大大降低故障诊断难度,节约故障诊断时间,带来良好的经济效益。

The traditional vehicle maintenance and diagnosis mode depends on manual experience and supporting equipment,which can not adapt to the speed of vehicle replacement.There is an urgent need for more efficient and intelligent fault location and rapid maintenance technology to improve vehicle safety and reliability,thus giving birth to the comprehensive discipline of vehicle fault diagnosis technology.Based on the design idea of artificial intelligence,this paper adopts a large number of maintenance examples as the training samples of the system,applies the latest information technology to complete the design and implementation of automobile fault cognitive diagnosis system,provides users with an efficient and simple fault diagnosis platform,and provides the basis for professional maintenance personnel to solve automobile faults and automobile maintenance.Through experimental test,the system greatly reduces the difficulty of fault diagnosis and saves the time of fault diagnosis,and brings good economic benefits.