摘要
为实现车辆故障的高精准识别和诊断,设计了一种基于数据分析的车辆故障系统。首先结合实际需求,采用3层的C/S架构搭建了系统的总体结构,基于大数据分析、挖掘技术支撑下的案例推理原理,给出了故障诊断的流程方法;而后,以多特征组合的方法建构故障案例库,给出案例库的结构组成、字段设计及功能模块,并基于案例相似度计算,匹配最优的解决方案,进行故障案例的重用及优化决策;通过不同分类函数的优化拟合,得出车辆典型故障发生概率分布图,以辅助运维人员快速定位故障。在Windows操作环境下,融合Access数据库,实现车辆故障系统开发。经测试,该系统可实现车辆故障的智能化、准确性诊断,提升车辆运行安全性。
In order to realize the high accuracy recognition and diagnosis of vehicle fault,designs a vehicle fault system based on data analysis.Firstly,combined with the actual needs,the system structure is built with three-tier C/S architecture.Based on the case-based reasoning principle supported by big data analysis and mining technology,the flow method of fault diagnosis is given.Then,the fault case base is constructed by the method of multi feature combination,and the structure,field design and function modules of the case base are given.Based on the case similarity calculation,the optimal solution is matched,and the reuse and optimization decision of fault cases are made.The probability distribution diagram of typical vehicle faults is obtained by the optimization fitting of different classification functions to assist the operation and maintenance personnel quickly locate the fault.Under the windows operating environment,the access database is integrated to realize the development of vehicle fault system.After testing,the fault diagnosis system can realize the intelligent and accurate diagnosis of vehicle faults,and improve the safety of vehicle operation.
作者
刘冬梅
Liu Dongmei(School of automotive engineer,Shaanxi College of Communication Technology,Xi’an 710019,China)
出处
《电子测量技术》
2020年第15期149-153,共5页
Electronic Measurement Technology
基金
陕西交通职业技术学院项目(YJ19001)资助
关键词
数据分析
车辆故障
案例库
预测
data analysis
vehicle failure
case base
prediction
作者简介
刘冬梅,硕士研究生,讲师,主要研究方向为车辆工程、汽车设计与制造。E-mail:fangyu_y@126.com
