公开(公告)号：US08509985B2

公开(公告)日：2013-08-13

申请号：US13115216

申请日：2011-05-25

Applicant: Halasya Siva Subramania ,  Satnam Singh ,  Clifton L. Pinion

Inventor： Halasya Siva Subramania ,  Satnam Singh ,  Clifton L. Pinion

IPC: G06F17/00

CPC classification number: G05B23/0278

Abstract: A method is provided for identifying a root cause of a fault in a serviced vehicle based on analytical symptoms. Parameter identification data associated with identified DTCs is retrieved. Parameter identification data from a plurality of vehicles experiencing the DTCs is collected. A first set of diagnostic rules is generated that identify vehicle operating parameters for executing a DTC algorithm or for triggering a DTC. A second set of diagnostic rules is generated that identify vehicle operating parameters used for selecting field failure data obtained when the DTC is triggered. Statistically significant rules are extracted from the second set of diagnostic rules. The first set of rules and the statistically significant rules are cooperatively applied to the parameter identification data for identifying a subset of the parameter identification data that represents anomalies. A subject matter expert analyzes the anomalies for identifying a root cause of the fault.

Abstract translation: 提供了一种基于分析症状来识别服务车辆中的故障的根本原因的方法。 检索与识别的DTC相关联的参数识别数据。 收集来自经历DTC的多个车辆的参数识别数据。 生成第一组诊断规则，识别用于执行DTC算法或触发DTC的车辆操作参数。 产生第二组诊断规则，其识别用于选择触发DTC时获得的现场故障数据的车辆操作参数。 从第二组诊断规则中提取统计学上重要的规则。 协调地将第一组规则和统计上有意义的规则应用于参数识别数据，以识别代表异常的参数识别数据的子集。 主题专家分析了确定故障根本原因的异常情况。

公开(公告)号：US20120303205A1

公开(公告)日：2012-11-29

申请号：US13115216

申请日：2011-05-25

Applicant: Halasya Siva Subramania ,  Satnam Singh ,  Clifton L. Pinion

Inventor： Halasya Siva Subramania ,  Satnam Singh ,  Clifton L. Pinion

IPC: G06F17/00

CPC classification number: G05B23/0278

Abstract: A method is provided for identifying a root cause of a fault in a serviced vehicle based on analytical symptoms. Parameter identification data associated with identified DTCs is retrieved. Parameter identification data from a plurality of vehicles experiencing the DTCs is collected. A first set of diagnostic rules is generated that identify vehicle operating parameters for executing a DTC algorithm or for triggering a DTC. A second set of diagnostic rules is generated that identify vehicle operating parameters used for selecting field failure data obtained when the DTC is triggered. Statistically significant rules are extracted from the second set of diagnostic rules. The first set of rules and the statistically significant rules are cooperatively applied to the parameter identification data for identifying a subset of the parameter identification data that represents anomalies. A subject matter expert analyzes the anomalies for identifying a root cause of the fault.

Abstract translation: 提供了一种基于分析症状来识别服务车辆中的故障的根本原因的方法。 检索与识别的DTC相关联的参数识别数据。 收集来自经历DTC的多个车辆的参数识别数据。 生成第一组诊断规则，识别用于执行DTC算法或触发DTC的车辆操作参数。 产生第二组诊断规则，其识别用于选择触发DTC时获得的现场故障数据的车辆操作参数。 从第二组诊断规则中提取统计学上重要的规则。 协调地将第一组规则和统计上有意义的规则应用于参数识别数据，以识别代表异常的参数识别数据的子集。 主题专家分析了确定故障根本原因的异常情况。

公开(公告)号：US20110144853A1

公开(公告)日：2011-06-16

申请号：US12638592

申请日：2009-12-15

Applicant: Halasya Siva Subramania ,  Satnam Singh ,  Steven W. Holland ,  Jason T. Davis ,  Tim Felke ,  Ravindra Patankar ,  Aru Narla

Inventor： Halasya Siva Subramania ,  Satnam Singh ,  Steven W. Holland ,  Jason T. Davis ,  Tim Felke ,  Ravindra Patankar ,  Aru Narla

IPC: G06F7/00 ,  G01M17/00 ,  G06F17/30

CPC classification number: G06F11/0751 ,  G06F11/0739

Abstract: A system and method for reducing or eliminating built-in tests and diagnostic trouble codes that are set as a result of improper parameter values. The method includes collecting field failure data that identifies diagnostic trouble codes and parameters of the system that are used to set diagnostic trouble codes. The method transforms the collected data into a format more appropriate for human analysis and pre-processes the transferred data to identify and remove information that could bias the human analysis. The method includes plotting linear and nonlinear combinations of operation parameters, performing data mining and analysis for detecting inappropriate settings of fault codes in the pre-processed data and providing the mined data to a subject matter expert for review to determine whether a diagnostic trouble code has been issued because of improper parameters.

Abstract translation: 用于减少或消除由于不正确的参数值而设置的内置测试和诊断故障代码的系统和方法。 该方法包括收集现场故障数据，识别用于设置诊断故障代码的系统的诊断故障代码和参数。 该方法将收集的数据转换为更适合人类分析的格式，并预处理传输的数据，以识别和删除可能偏向人类分析的信息。 该方法包括绘制操作参数的线性和非线性组合，执行数据挖掘和分析，以检测预处理数据中的故障代码的不适当设置，并将开采的数据提供给主题专家以进行审查，以确定诊断故障代码是否具有 由于参数不当而被发布。

公开(公告)号：US08212527B2

公开(公告)日：2012-07-03

申请号：US12181683

申请日：2008-07-29

Applicant: Yilu Zhang ,  Mutasim A. Salman ,  Ryan M. Edwards ,  John J. Correia ,  Mark J. Rychlinski ,  Gary W Gantt, Jr. ,  Halasya Siva Subramania ,  Kyle L Lobes

Inventor： Yilu Zhang ,  Mutasim A. Salman ,  Ryan M. Edwards ,  John J. Correia ,  Mark J. Rychlinski ,  Gary W Gantt, Jr. ,  Halasya Siva Subramania ,  Kyle L Lobes

IPC: H02J7/00 ,  H02J7/14 ,  H02J7/16

CPC classification number: G01R31/3693 ,  G01R31/3689 ,  G08C17/00

Abstract: A system and method for determining the status of a vehicle battery to determine whether the battery may not have enough charge to start the vehicle. The method includes collecting data relating to the battery on the vehicle and collecting data relating to the battery at a remote back-office. Both the vehicle and the remote data center determine battery characteristics based on the collected data and the likelihood of a vehicle no-start condition, where the algorithm used at the remote back-office may be more sophisticated. The data collected at the remote back-office may include vehicle battery information transmitted wirelessly from the vehicle, and other information, such as temperature, battery reliability, miles that the vehicle has driven per day, ambient temperature, high content vehicle, etc. Both the vehicle and the remote back-office may determine the battery open circuit voltage.

Abstract translation: 一种用于确定车辆电池的状态以确定电池是否可能没有足够的充电以启动车辆的系统和方法。 该方法包括在车辆上收集与电池相关的数据，并在远程后台收集与电池相关的数据。 车辆和远程数据中心都基于收集的数据和车辆无启动条件的可能性确定电池特性，其中在远程后台使用的算法可能更复杂。 在远程后台收集的数据可以包括从车辆无线传输的车辆电池信息，以及诸如温度，电池可靠性，车辆每天驾驶的里程，环境温度，高内容车辆等的其他信息。两者 车辆和远程后台可以确定电池的开路电压。

公开(公告)号：US20100026306A1

公开(公告)日：2010-02-04

申请号：US12181683

申请日：2008-07-29

Applicant: Yilu Zhang ,  Mutasim A. Salman ,  Ryan M. Edwards ,  John J. Correia ,  Mark J. Rychlinski ,  Gary W. Gantt, JR. ,  Halasya Siva Subramania ,  Kyle L. Lobes

Inventor： Yilu Zhang ,  Mutasim A. Salman ,  Ryan M. Edwards ,  John J. Correia ,  Mark J. Rychlinski ,  Gary W. Gantt, JR. ,  Halasya Siva Subramania ,  Kyle L. Lobes

IPC: G01R31/36

CPC classification number: G01R31/3693 ,  G01R31/3689 ,  G08C17/00

Abstract: A system and method for determining the status of a vehicle battery to determine whether the battery may not have enough charge to start the vehicle. The method includes collecting data relating to the battery on the vehicle and collecting data relating to the battery at a remote back-office. Both the vehicle and the remote data center determine battery characteristics based on the collected data and the likelihood of a vehicle no-start condition, where the algorithm used at the remote back-office may be more sophisticated. The data collected at the remote back-office may include vehicle battery information transmitted wirelessly from the vehicle, and other information, such as temperature, battery reliability, miles that the vehicle has driven per day, ambient temperature, high content vehicle, etc. Both the vehicle and the remote back-office may determine the battery open circuit voltage.

Abstract translation: 一种用于确定车辆电池的状态以确定电池是否可能没有足够的充电以启动车辆的系统和方法。 该方法包括在车辆上收集与电池相关的数据，并在远程后台收集与电池相关的数据。 车辆和远程数据中心都基于收集的数据和车辆无启动条件的可能性确定电池特性，其中在远程后台使用的算法可能更复杂。 在远程后台收集的数据可以包括从车辆无线传输的车辆电池信息，以及诸如温度，电池可靠性，车辆每天驾驶的里程，环境温度，高内容车辆等的其他信息。两者 车辆和远程后台可以确定电池的开路电压。