轻型汽油车远程监测及故障诊断技术研究
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摘要
随着汽车排放法规的日趋严格和用户对汽车性能要求的不断提高,现代汽车企业不断增加电子控制技术的在汽车中应用来满足上述要求,这使得汽车电控系统的结构越来越复杂,诊断故障发生原因及发现故障的部位也相应的变得越来越困难。因此,本文通过对当前汽车远程监测技术和智能诊断技术的研究,提出构建汽车远程监测及故障诊断系统,并对其核心技术进行了研究。
首先,针对各种车型诊断协议不兼容的问题,设计了基于车载自诊断系统扩展协议ISO14230和ISO15765的通用型汽车诊断通信接口装置。为了解决传统监测和诊断方法受地理位置限制的影响,进一步提出了基于Internet3G的汽车远程状态监测方法,通过归纳总结各类型数据在远程传输过程中的要求特征,设计了相关的传输控制策略和服务器监测模型,为后续研究奠定了数据基础。
其次,研究了基于多信息融合技术的汽车故障诊断方法,构建了汽车故障融合诊断模型。该模型根据不同数据层次,分别设计了基于RBF神经网络的数据层融合诊断、基于支持向量机和主成分分析的特征层融合诊断、基于D-S证据理论的决策层融合诊断。在以冷却液温度传感器、氧传感器和进气歧管绝对压力传感器的老化失效和通断故障模拟的研究基础上,通过数据采集平台获取了车辆实时状态数据,并由汽车故障融合诊断模型进行了各层次融合诊断,验证了该诊断模型的有效性。
最后,设计和构建了汽车远程监测及故障诊断系统,该系统以汽车远程监测及故障诊断中心为核心,并结合车辆诊断通信接口装置、PC和智能手机客户端共同构成。结合实际功能需求,本文对汽车远程监测及故障诊断系统的分层模式和UML架构模型进行了研究,并实现了基于多智能体的汽车远程故障融合诊断模型。同时,使用可复用思想设计了跨平台的PC和智能手机客户端程序,有效改善了当前手持式诊断方法的处理性能不高和功能不全的问题,便于实现随时随地的汽车故障诊断,并形成了一定规模的产业化应用。
In order to meet increasing emission standard requirements and further improve automobile performance, automotive enterprises now apply electronic control technology in the automobiles increasingly, thus making the structure of automobile electronic control system more and more complicated. It becomes more and more difficult to judge the causes of faults and determine the locations of faults. Based on the study of vehicle remote monitoring and intelligent diagnosis technology, this thesis establishes an vehicle remote monitoring and intelligent diagnosis system, and its core technology is studied.
First of all, according to extended protocol of vehicle fault diagnosis ISO14230and ISO15765, a universal data collection platform based on K line and CAN bus is designed and developed. In order to solve the traditional monitoring and diagnosis method is restricted by geographical position, a method for remote diagnosis data acquisition is proposed, which is based on Internet and3G. According to data transmission process and network transmission characteristics, the data transmission strategy and server monitoring model are designed to achieve remote monitoring data acquisition.
And then, this paper design a intelligent diagnostic model, which is divided into three parts:data level fusion diagnosis based on RBF neural network; characteristic level fusion diagnosis based on support vector machine and principal component analysis; decision level fusion diagnosis based on D-S evidence theory. Output signal failures and on-off faults of coolant temperature sensor, oxygen sensor, manifold absolutely pressure sensor are simulated, real-time status data of the vehicle are acquired by data collection platform. By comparing and analyzing automobile intelligent diagnostic model that is based on multi-information fusion at data level, characteristic level and decision level, the effectiveness of diagnostic model is validated, a variety of combinations in practical application are proposed.
Finally, a vehicle remote monitoring and fault diagnosis system is also designed and built, combining diagnostic communication interface, PC and smart phone client, vehicle remote monitoring and fault diagnosis center. Combined with the actual functional requirements, this paper does research on architecture models of the system. Combined with the multiple information fusion diagnosis models, and design the intelligent diagnosis method based on multi-agent. At the same time, improve the processing performance of the current handheld diagnosis method by the use of PC and smart phones with automobile fault diagnosis is implemented for the client, realizing the auto fault diagnosis anytime and anywhere.
首先,针对各种车型诊断协议不兼容的问题,设计了基于车载自诊断系统扩展协议ISO14230和ISO15765的通用型汽车诊断通信接口装置。为了解决传统监测和诊断方法受地理位置限制的影响,进一步提出了基于Internet3G的汽车远程状态监测方法,通过归纳总结各类型数据在远程传输过程中的要求特征,设计了相关的传输控制策略和服务器监测模型,为后续研究奠定了数据基础。
其次,研究了基于多信息融合技术的汽车故障诊断方法,构建了汽车故障融合诊断模型。该模型根据不同数据层次,分别设计了基于RBF神经网络的数据层融合诊断、基于支持向量机和主成分分析的特征层融合诊断、基于D-S证据理论的决策层融合诊断。在以冷却液温度传感器、氧传感器和进气歧管绝对压力传感器的老化失效和通断故障模拟的研究基础上,通过数据采集平台获取了车辆实时状态数据,并由汽车故障融合诊断模型进行了各层次融合诊断,验证了该诊断模型的有效性。
最后,设计和构建了汽车远程监测及故障诊断系统,该系统以汽车远程监测及故障诊断中心为核心,并结合车辆诊断通信接口装置、PC和智能手机客户端共同构成。结合实际功能需求,本文对汽车远程监测及故障诊断系统的分层模式和UML架构模型进行了研究,并实现了基于多智能体的汽车远程故障融合诊断模型。同时,使用可复用思想设计了跨平台的PC和智能手机客户端程序,有效改善了当前手持式诊断方法的处理性能不高和功能不全的问题,便于实现随时随地的汽车故障诊断,并形成了一定规模的产业化应用。
In order to meet increasing emission standard requirements and further improve automobile performance, automotive enterprises now apply electronic control technology in the automobiles increasingly, thus making the structure of automobile electronic control system more and more complicated. It becomes more and more difficult to judge the causes of faults and determine the locations of faults. Based on the study of vehicle remote monitoring and intelligent diagnosis technology, this thesis establishes an vehicle remote monitoring and intelligent diagnosis system, and its core technology is studied.
First of all, according to extended protocol of vehicle fault diagnosis ISO14230and ISO15765, a universal data collection platform based on K line and CAN bus is designed and developed. In order to solve the traditional monitoring and diagnosis method is restricted by geographical position, a method for remote diagnosis data acquisition is proposed, which is based on Internet and3G. According to data transmission process and network transmission characteristics, the data transmission strategy and server monitoring model are designed to achieve remote monitoring data acquisition.
And then, this paper design a intelligent diagnostic model, which is divided into three parts:data level fusion diagnosis based on RBF neural network; characteristic level fusion diagnosis based on support vector machine and principal component analysis; decision level fusion diagnosis based on D-S evidence theory. Output signal failures and on-off faults of coolant temperature sensor, oxygen sensor, manifold absolutely pressure sensor are simulated, real-time status data of the vehicle are acquired by data collection platform. By comparing and analyzing automobile intelligent diagnostic model that is based on multi-information fusion at data level, characteristic level and decision level, the effectiveness of diagnostic model is validated, a variety of combinations in practical application are proposed.
Finally, a vehicle remote monitoring and fault diagnosis system is also designed and built, combining diagnostic communication interface, PC and smart phone client, vehicle remote monitoring and fault diagnosis center. Combined with the actual functional requirements, this paper does research on architecture models of the system. Combined with the multiple information fusion diagnosis models, and design the intelligent diagnosis method based on multi-agent. At the same time, improve the processing performance of the current handheld diagnosis method by the use of PC and smart phones with automobile fault diagnosis is implemented for the client, realizing the auto fault diagnosis anytime and anywhere.
引文
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