Abstract:
Systems and methods for capturing and analyzing significant parameter data from vehicle systems whenever a diagnostic trouble code (DTC) is triggered. A multi-dimensional matrix is constructed, with vehicles, DTCs, and parameter data comprising three dimensions of the matrix. The data matrix is populated with DTC and parameter data from many different vehicles, either when vehicles are taken to a dealer for service, or via wireless data download. Time can be added as a fourth dimension of the matrix, providing an indication of whether a particular system or component is temporally degrading. When sufficient data is accumulated, the data matrix is pre-processed, features are extracted from the data, and the features are classified, using a variety of mathematical techniques. Trained classifiers are then used to diagnose the root cause of any particular fault signal, and also to provide a prognosis of system health and remaining useful life.
Abstract:
Systems and methods for capturing and analyzing significant parameter data from vehicle systems whenever a diagnostic trouble code (DTC) is triggered. A multi-dimensional matrix is constructed, with vehicles, DTCs, and parameter data comprising three dimensions of the matrix. The data matrix is populated with DTC and parameter data from many different vehicles, either when vehicles are taken to a dealer for service, or via wireless data download. Time can be added as a fourth dimension of the matrix, providing an indication of whether a particular system or component is temporally degrading. When sufficient data is accumulated, the data matrix is pre-processed, features are extracted from the data, and the features are classified, using a variety of mathematical techniques. Trained classifiers are then used to diagnose the root cause of any particular fault signal, and also to provide a prognosis of system health and remaining useful life.
Abstract:
A method is provided for enhancing service diagnostics utilizing service repair data of previously serviced vehicles. Service repair data of previously serviced vehicles is obtained from a memory storage device. The service data is compiled into a service diagnostic code dataset and a service labor code dataset. The service diagnostic code dataset and service labor code dataset are categorized into an electronic data table. Respective combinations are formed in the electronic data table. An aggregate count is determined for each respective combination in the electronic data table. Either of a respective diagnostic code or a respective service labor code is identified having a correlation with more than one of either service diagnostic codes or service labor codes. At least one of a service repair procedure used to repair the vehicle or a respective service diagnostic code used to identify the fault is modified in response to analyzing the respective combinations.
Abstract:
An integrated diagnosis and prognosis system that collects vehicle information over the life of a vehicle and its development. The system provides the collected vehicle information to supplier management, product development management, service/dealership management, customer relations departments and production facilities, which use the information to take certain action for existing vehicles, fleets of vehicles or future vehicles to improve vehicle reliability and quality.
Abstract:
A method is provided for enhancing service diagnostics utilizing service repair data of previously serviced vehicles. Service repair data of previously serviced vehicles is obtained from a memory storage device. The service data is compiled into a service diagnostic code dataset and a service labor code dataset. The service diagnostic code dataset and service labor code dataset are categorized into an electronic data table. Respective combinations are formed in the electronic data table. An aggregate count is determined for each respective combination in the electronic data table. Either of a respective diagnostic code or a respective service labor code is identified having a correlation with more than one of either service diagnostic codes or service labor codes. At least one of a service repair procedure used to repair the vehicle or a respective service diagnostic code used to identify the fault is modified in response to analyzing the respective combinations.
Abstract:
An integrated diagnosis and prognosis system that collects vehicle information over the life of a vehicle and its development. The system provides the collected vehicle information to supplier management, product development management, service/dealership management, customer relations departments and production facilities, which use the information to take certain action for existing vehicles, fleets of vehicles or future vehicles to improve vehicle reliability and quality.
Abstract:
A system and method for converting text related to vehicle service to symptom codes. The method includes typing into work orders and service reports statements that describe the various symptoms and problems of a vehicle that is being serviced. The work orders and service reports are then transmitted to a database facility where they are analyzed. Prior to the reports being analyzed, the text in the work order and service reports is read by a machine reader that converts the text to symptom codes that describe particular vehicle conditions and symptoms. A processor analyzes the codes for patterns and other relationships, and can provide a display of such patterns. Further, the codes and reports are stored in a memory.
Abstract:
A system and method for fault diagnosis includes receiving information defining a relationship between failure modes and diagnostic trouble codes and extracting diagnostic trouble code data, including set times, frequency data and diagnostic trouble code sequence information for a plurality of diagnostic trouble codes relating to a plurality of failure modes. The system and method further include constructing a Markov chain using the diagnostic trouble code data for each of the plurality of failure modes, training the Markov chain to learn a set of state parameters using the diagnostic trouble code data, and computing a likelihood of a diagnostic trouble code sequence for each of the plurality of failure modes using the trained Markov chains.
Abstract:
A system and method for fault diagnosis includes receiving information defining a relationship between failure modes and diagnostic trouble codes and extracting diagnostic trouble code data, including set times, frequency data and diagnostic trouble code sequence information for a plurality of diagnostic trouble codes relating to a plurality of failure modes. The system and method further include constructing a Markov chain using the diagnostic trouble code data for each of the plurality of failure modes, training the Markov chain to learn a set of state parameters using the diagnostic trouble code data, and computing a likelihood of a diagnostic trouble code sequence for each of the plurality of failure modes using the trained Markov chains.
Abstract:
A document may be received at a processing module. One or more tags may be applied to the document, each tag applied to a term, each tag representing a part of speech. One or more terms may be extracted from the document based on the tag. A weighting assignment parameter may be determined for each of the one or more extracted terms. Based on the weighting assignment parameter associated with each of the extracted terms, it may be determined whether the domain ontology includes the one or more extracted terms. If the domain ontology does not include the one or more extracted terms, the domain ontology may be augmented such that the domain ontology comprises the one or more extracted terms.