Aggregated information fusion for enhanced diagnostics, prognostics and maintenance practices of vehicles
First Claim
1. A method for providing vehicle diagnostics and prognostics evaluations, said method comprising:
- collecting data from multiple components, sub-systems and systems of a vehicle and from multiple vehicle sources including components, sub-systems and systems for different vehicles;
storing the collected data in one or more databases;
generating classes for different types of collected data, where the classes include working, impending failure and faulty;
fusing the collected data from the vehicle'"'"'s components, sub-systems and systems and the multiple vehicle sources; and
analyzing the fused data to identify fault conditions in the vehicle'"'"'s components, sub-systems and systems.
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Accused Products
Abstract
A system and method for enhancing vehicle diagnostic and prognostic algorithms and improving vehicle maintenance practices. The method includes collecting data from vehicle components, sub-systems and systems, and storing the collected data in a database. The collected and stored data can be from multiple sources for similar vehicles or similar components and can include various types of trouble codes and labor codes as well as other information, such as operational data and physics of failure data, which are fused together. The method generates classes for different vehicle components, sub-systems and systems, and builds feature extractors for each class using data mining techniques of the data stored in the database. The method also generates classifiers that classify the features for each class. The feature extractors and feature classifiers are used to determine when a fault condition has occurred for a vehicle component, sub-system or system.
51 Citations
20 Claims
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1. A method for providing vehicle diagnostics and prognostics evaluations, said method comprising:
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collecting data from multiple components, sub-systems and systems of a vehicle and from multiple vehicle sources including components, sub-systems and systems for different vehicles; storing the collected data in one or more databases; generating classes for different types of collected data, where the classes include working, impending failure and faulty; fusing the collected data from the vehicle'"'"'s components, sub-systems and systems and the multiple vehicle sources; and analyzing the fused data to identify fault conditions in the vehicle'"'"'s components, sub-systems and systems. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A method for providing vehicle diagnostics and prognostics evaluations, said method comprising:
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collecting data from vehicle components, sub-systems and systems on vehicles; storing the collected data in a database either onboard the vehicles or off-board the vehicles; telematically transmitting the collected data from the vehicles to a remote data center; generating classes for different types of the collected data at the remote data center, where the classes include working, impending failure and faulty; building feature extractors for each class using data mining techniques of the data stored in the database at the remote data center; generating feature classifiers that classify features for each class at the remote data center; using the feature extractors and the feature classifiers to determine when a fault condition has occurred for a vehicle component, sub-system or system; combining outputs for multiple feature classifiers to increase the robustness for determining when a fault condition occurs; and transmitting fault condition results back to the vehicles. - View Dependent Claims (12, 13, 14, 15, 16)
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17. A system for providing vehicle diagnostics and prognostics evaluations, said system comprising:
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means for collecting data from vehicle components, sub-systems and systems on a vehicle; means for storing the collected data in a database on the vehicle; means for transmitting the collected data telematically to a remote data center; means for generating classes for different types of collected data at the remote data center, where the classes include working, impending failure and faulty; means for building feature extractors for each class using data mining techniques of the data stored in a database on the remote data center; means for generating feature classifiers that classify the features for each class; and means for using the feature extractors and feature classifiers to determine when a fault condition has occurred for a vehicle component, sub-system or system. - View Dependent Claims (18, 19, 20)
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Specification