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Vehicle error diagnosis - and vehicle error prediction system and method for fault diagnosis and error prediction

机译:车辆错误诊断以及用于故障诊断和错误预测的车辆错误预测系统和方法

摘要

Vehicle error diagnosis - and vehicle error prediction system (10), which includes:a computing platform (14), the inside of a vehicle (12) is arranged, characterized in that the computing platform (14) is configured to an error classifier periodically from a remote server (18) to receive data, wherein the computing platform (14) in concrete terms, contains computer-executable instructions for:Evaluation of the current data sequences, the expensive network of a vehicle are received and grafted block diagnosis error codes, time stamped diagnosis error codes and vehicle parameters; andApplying the classifier to the data sequences, wherein the classifier is configured to determine whether the data sequences define a pattern, which is associated with a special error,Outputting a warning message, if it is found that the data sequences define a pattern, which is associated with a special error,the classifier is trained on the basis of a comparison of data sequences, which consists of a first population of vehicles with repair data, which consists of a second population of vehicles are obtained, reference being made to the data sequences from the first population of vehicles are obtained, a time data used to obtain applicationn="12" the identifying of frequent data sequences comprises;the data sequences from the first population of vehicles are obtained, with the repair data composed of the second population of vehicles are obtained, are compared with each other, in order to identify patterns in the data sequences with a specific cause failure mode in relation to one another, wherein each identified pattern is a backup cluster - and measure of confidence is assigned in the form of a probability.
机译:车辆错误诊断和车辆错误预测系统(10),包括:计算平台(14),布置有车辆(12)内部,其特征在于,计算平台(14)定期配置为错误分类器从远程服务器(18)接收数据,其中计算平台(14)具体包含用于以下方面的计算机可执行指令:评估当前数据序列,接收昂贵的车辆网络并嫁接块诊断错误代码,带有时间戳的诊断错误代码和车辆参数;将分类器应用于数据序列,其中,如果发现数据序列定义了模式,则分类器用于确定数据序列是否定义了与特殊错误相关的模式,并输出警告消息。与特殊错误相关的分类器在比较数据序列的基础上进行训练,该数据序列包括第一组车辆和维修数据,第二组车辆由维修数据组成,参考数据序列从第一批车辆中获得的时间数据用于获取应用n =“ 12”,其中包括对频繁数据序列的识别;从第一批车辆中获取数据序列,其中维修数据由第二批车辆中的维修数据组成。获得车辆,将它们相互比较,以便识别数据序列中与一个原因相关的特定故障模式的模式另一个,其中每个识别出的模式是备用群集-并以概率的形式分配置信度。

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