CN102069781B - 允许远程信息处理的聚合的车辆诊断和预报 - Google Patents
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Abstract
本发明涉及允许远程信息处理的聚合的车辆诊断和预报,具体而言提供一种利用远程信息处理技术采集行驶车辆诊断数据的系统和方法。在一个实施例中,该方法包括从维修车间、行驶车辆和保修记录中采集车辆诊断数据,聚合所采集的数据和从聚合的数据中提取知识。提取的知识可用于增强车载的或者在维修中心使用的算法,以更好的识别车辆故障并提供增强的诊断和预报。然后,增强的算法可用于提供预测性保养建议,提供故障解决辅助或者提供车辆设计改进。
Description
技术领域
本发明总体涉及一种用于采集行驶车辆的数据的系统和方法,尤其涉及一种系统和方法,其用于采集行驶车辆的数据,提供从采集的数据进行的数据聚合和知识提取,以及根据提取的知识提供增强的故障隔离和预测性的保养维修。
背景技术
现代车辆典型地包括设计成提高车辆安全,增加驾驶者舒适度,提高驾驶者便利性等的几种系统。随着车辆上加入了越来越多这样的系统,车辆的电子设备、设备和电气系统正变得更加复杂。伴随着车辆系统的许多与电电气、控制和软件相关的故障断续地发生或者也可能仅在某种条件下发生。因此,当把车辆运到维修站时,车辆驾驶者在行驶中经历的故障可能不能再现。这导致对车辆系统、子系统和部件的诊断和预报变得更加困难。因为维修技师或许不能再现故障,所以在这些情况下故障基本上不可能被解决。而且,由于在这些车辆系统中应用的部件和设备的数量,所以定义这些部件和设备可能存在的所有故障情况通常是一个艰巨的任务。结果,大量的维修报告都说未发现故障(NTF)或客户关心的问题没有再出现。
发明内容
依照本发明的教导,公开了一种用于通过远程信息处理技术采集行驶车辆诊断数据的系统和方法。在一个实施例中,该方法包括从维修车间、行驶车辆和保修记录中采集车辆诊断数据,聚合所采集的数据并从中提取知识。提取的知识可用于增强车载的或者在维修中心使用的算法,以更好的识别车辆故障并提供增强的诊断和预报。然后,增强的算法可用于提供预测性保养建议,提供故障解决辅助或者提供车辆设计改进措施。
本发明的附加特征可以从以下描述和所附权利要求并结合附图中清楚得到。
附图说明
图1是根据本发明实施例的包括车辆的网络的平面图,该车辆具有在车辆行驶时用于传输车辆运行数据的无线通信系统;和
图2是根据本发明实施例的流程图,其显示了获取和使用利用远程信息处理技术从车辆采集的数据的方法。
具体实施方式
对针对在车辆行驶时通过远程信息处理技术获取车辆数据的系统和方法的本发明的实施方式的如下讨论实质上仅是示例性的,并不旨在限定本发明或其应用或使用。
本发明提出了一种用于在车辆行驶时采集车辆数据,并使用该数据来提供故障检测和预防保养的方法。该方法涉及三个主要步骤,包括:从行驶车辆远程采集数据,通过对上述数据的挖掘识别共享的故障症状和共同的故障预兆,和提供增强的故障隔离和预测性保养维修。采集数据包括从行驶车辆中连续上传数据,包括参数化数据和抽象化数据,例如故障或诊断代码。采集数据也可以包括从维修车间,例如经销商,签约的修车厂等上传车辆修理信息。而且,可以从维修车问能够最好的故障解决手段。为了提取知识,在合适的位置挖掘所述数据以识别共享的故障症状和共同的预兆以用于相同或相似的修理情况。能够用于数据挖掘的各种技术包括,但不局限于,关联规则学习,决策树以及其他数据挖掘和模式识别方法。这些数据能够转换成通过推理机或维修程序表示的知识。可以使用任何合适的基于案例的推理过程,例如贝叶斯网络。提供维修可包括向技师和维修车间提供故障解决辅助。维修程序可以通过出版物更新。推理机可在原始设备生产商(OEM)技师支持中心使用以回答电话呼叫。而且,维修可以向车辆所有者、个人、车队管理者等提供预测性保养建议。维修特色也可以包括向OEM提供设计改进建议。
图1是包括具有无线通信系统14的车辆12的通信网络10的平面图。车辆控制器16从车辆系统、子系统和部件接收各种信号,并从这些识别车辆12运行的系统和设备采集诊断代码和其他信号。这些数据被提供给无线通信系统14,无线通信系统14向符合此处讨论的适当设施18播送该数据。与车辆诊断和预报相关的信息和其他数据也可从其他设施20,例如维修车间、保修记录设施等输送到设施18。输送到设施18的涉及车辆诊断和预报的信息并不局限于特定的设施、特定的车辆数量、特定的车辆类型等,而是按照本文所讨论地仅由期望接收的信息的数量和类型所限定。
图2是显示根据本发明实施例的用于采集车辆数据和分析这些数据的方法的流程图30。在方框32,当车辆进行修理或在进行其他维修时,从维修车间,例如维修车间20采集车辆数据。这些数据可以包括各种事项,例如车辆识别码(VIN)、参数化或抽象化的车辆数据、根本原因数据、问题解决信息、保养记录等。而且,在方框34,也从行驶车辆,例如车辆12,中采集数据。如上所述,可以连续地在车辆12上采集数据,并连续地传输到数据设施18,或者可以在感知到问题时采集数据,其中可以恰好在该问题前和该问题期间传送数据。从行驶车辆上采集的数据可以包括VIN、参数化或抽象化的车辆数据、时间戳等。而且,在单元36,可以从保修记录中采集数据,例如车辆何时去修理车间进行保修或其他可获得的保修信息。这些数据可包括VIN、参数化或抽象化的车辆数据、根本原因数据、工作代码等。
然后将从这三个指定位置采集的数据传输或输送到特定设施,例如设施18,其中在方框38自动聚合数据并从中提取知识。从不同来源采集的数据的此自动聚合和知识的提取能够通过任何合适的方式执行以识别共享的症状和公同的预兆以用于相似修理。可以使用各种方法和算法,例如关联规则学习、支持向量机操作,和其他数据挖掘和模式识别技术。因此,如果症状在以前已经被发现并记录,且被充分地修正过,那么对带有同样问题的新车辆可以再次使用相同的维修程序。
当技师在带有老问题的新车辆上工作时,他可以通过任何合适的方式进入数据库来查找该问题以确定该车辆的正确修理方法。在方框40,已采集并通过上述的各种学习算法提取的数据可以利用用于识别车辆问题的增强诊断和预报算法以车载或非车载的方式被使用。例如,可以车载用于查看诊断代码和车辆信息以确定问题是否存在的这些算法,能够利用从其它车辆采集的可以从相同症状识别该相同问题的信息来升级。而且,在特许经销商或其他维修站点所使用的算法也能被增强,在这些地方可以向数据库输入车辆的症状以识别特定的车辆问题从而允许技师更轻松更容易地修正该问题。上述所提取的知识可以为推理机或其他使用了例如基于案例的推理、贝叶斯网络、规则数据库技术或其他推理机的维修程序所使用。
既然已经对算法进行升级以随车或者在维修设施处提供更好的车辆维修,那么增强的算法可以通过各种方式使用。例如,在方框42,上述算法可以用于向车辆所有者提供预测性保养建议。特别地,如果车辆发现了在过去已知会在特定问题前发生的一系列信号,那么可以提供合适的警告灯或其他提醒设备以让车辆所有者知道应当在实际问题发生前进行维修。在这种情况下,维修中心的技师将可以查看车辆控制器以了解可能发生的具体的潜在问题是什么。另外,在方框44,当车辆所有者把车辆送到维修中心时,上述算法也能向试图解决问题的技师提供故障解决辅助。这可以通过不同方式实现,例如通过网络出版物,分配多个推理机,通过软件更新或其他,通过工具,例如技术-2设备(tech-2devices)更新维修程序,和利用推理机和OEM技师支持中心以回答电话呼叫。而且,在方框46,来自增强算法的与潜在车辆问题相关的信息可以为OEM所用以提供设计改进。
可以给出多个示例以显示如上所述的本发明的一些优点。一个示例包括当大量场地车辆经历各种问题(例如ECU性能DTC代码,遗失通信DTC代码和弱点火)同时发生时的故障隔离。如果车辆上出现ECU运行DTC和遗失通信DTC的组合,维修车间可以使用这个信息首先检查电池状态。而且,也可以进行上面已经讨论过的故障预测,例如大量场地车辆对非起动情形在在两个月内经历DTC代码的某种组合或电池电流/电压的某些时序模式。如果这些故障发生,故障预测软件能警告车辆所有者进行电池检查。对于设计的改进,如果特定的车辆生产线对于通常/常见的行驶模式(例如工作日行驶10-40英里且周末行驶少于10英里)经历充电恶化的电池状态,那么算法可以建议该车辆生产线修改发电机尺寸或电池尺寸。
上述讨论揭示并描述的仅是本发明的示例性实施例。本领域技术人员将容易地从这样的讨论和附图及权利要求认识到在不超出所附权利要求所定义的本发明的范围和精神的情况下可以进行各种改变、改进和变化。
Claims (14)
1.一种用于采集和分析车辆数据的方法,所述方法包括:
从维修车间采集数据;
使用无线通信从行驶车辆采集数据;
采集保修记录数据;
自动聚合所采集的数据并使用知识提取以从聚合的数据提取信息;
利用所提取的信息提供车载和非车载的诊断和预报算法增强,其中提供算法增强包括使用基于案例的推理、贝叶斯网络、规则数据库、或推理机;并使用从其他行驶车辆采集的能够从相同症状识别相同问题的信息升级每个车辆的算法;和
使用增强的算法以提供各种车辆维修。
2.根据权利要求1所述的方法,其中使用增强的算法包括向车辆所有者提供预测性保养建议。
3.根据权利要求1所述的方法,其中使用增强的算法包括向技师提供故障解决辅助。
4.根据权利要求1所述的方法,其中使用增强的算法包括提供设计改进建议。
5.根据权利要求1所述的方法,其中从维修车间采集数据包括采集车辆识别码、参数化或抽象化的车辆数据、根本原因数据、问题解决数据和保养数据。
6.根据权利要求1所述的方法,其中从行驶车辆采集数据包括采集车辆识别码、参数化或抽象化的车辆数据和时间戳数据。
7.根据权利要求1所述的方法,其中采集保修数据包括采集车辆识别码、参数化或抽象化的车辆数据、根本原因数据和工作代码。
8.根据权利要求1所述的方法,其中自动数据聚合和知识提取包括使用从由关联规则学习和支持向量机学习组成的组中选择的算法。
9.根据权利要求1所述的方法,其中从行驶车辆采集数据包括从行驶车辆连续地采集数据或仅当在车辆上识别出潜在问题时采集数据。
10.一种用于采集和分析车辆数据的方法,所述方法包括:
从维修车间采集数据,包括车辆识别码、参数化或抽象化的车辆数据、根本原因数据、问题解决数据和保养数据;
使用无线通信从行驶车辆采集数据;
采集保修记录数据;
聚合所采集的数据和使用知识提取以从聚合的数据提取信息;和
使用所提取的信息提供车载和非车载的车辆诊断和预报以及故障预测,其中每个车辆的车载的诊断和预报以及故障预测使用从其他行驶车辆采集的能够从相同症状识别相同问题的信息来升级。
11.根据权利要求10所述的方法,进一步包括使用所提取的信息向车辆所有者提供预测性保养建议。
12.根据权利要求10所述的方法,进一步包括使用所提取的信息向技师提供故障解决辅助。
13.根据权利要求10所述的方法,进一步包括使用所提取的信息提供设计改进建议。
14.根据权利要求10所述的方法,其中数据聚合和知识提取包括使用从由关联规则学习和支持向量机学习组成的组中选择的算法。
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