Abstract: A system and method for inferring vehicle health are disclosed. The computer-implemented method comprises identifying a plurality of candidate vehicles for consideration for use for a task, and receiving corresponding event data for at least one of the plurality of candidate vehicles. The event data may correspond to at least one occurrence of at least one suspected problem for the corresponding candidate vehicle. A corresponding health score can be generated for each one of the plurality of candidate vehicles. The corresponding health score for the at least one of the plurality of candidate vehicles can be generated based on the corresponding event data for the at least one of the plurality of candidate vehicles. The generated health scores can indicate a likelihood of failure for their corresponding candidate vehicles.

Abstract: A vehicle control system includes a transceiver and a control unit. The transceiver is configured to communicate with plural vehicles, to receive operational parameter values from the plural vehicles. The operational parameter values are generated by sensors on board the vehicles and relate to operation of the vehicles during movement of the vehicles along one or more routes. The control unit is configured to generate respective vehicle operational assessments of the vehicles based on the received operational parameter values. The vehicle operational assessments are representative of respective states of operational readiness of the vehicles. The control unit is further configured to generate control signals, relating to control of the vehicles for operation along the one or more designated routes, based on the operational assessments. The control signals are configured to control at least one device, either on board or off board the vehicles.

Abstract: A system includes provision of a first set of instructions associated with a product to a user of the product, the user having one or more associated characteristics, reception of a revision to the first set of instructions from the user, determination of whether to modify the first set of instructions based the revision and on the characteristics, and modification, if a determination is made to modify the first set of instructions, of the first set of instructions based at least in part on the revision to generate a second set of instructions.

Abstract: A method for diagnosing machine faults, includes obtaining sensory data from a machine and obtaining a plurality of measured structural features based on the sensory data. The method also includes obtaining a plurality of reference cases corresponding to the sensory data, from a database. The plurality of reference cases include a plurality of reference structural features and a plurality of fault identifiers. The method further includes computing a statistical parameter based on the plurality of reference cases and obtaining a first subset of reference structural features from the plurality of reference structural features based on the computed statistical parameter. The method also includes computing a plurality of similarity values based on the obtained first subset of reference structural features and the plurality of measured structural features.

Abstract: A system and method are provided that can identify instructive fault identifiers to assist in the diagnosis of machine faults. The system and method can obtain fault identifiers indicative of potential faults of machines. Frequencies of occurrences of the fault identifiers among the reference cases and determining coverage indices of the fault identifiers can be determined. The coverage indices may indicate how many of the reference cases associated with a selected repair recommendation include one or more of the fault identifiers. The system and method also can determine confusion probabilities that the fault identifiers are indicative of a repair recommendation other than the selected repair recommendation and identify at least one of the fault identifiers as instructive fault identifiers for the selected repair recommendation based on the frequencies of occurrences, the coverage indices, and/or the one or more confusion probabilities.

Abstract: Systems and methods for diagnosing or prognosing mobile and/or fixed client assets in a logical and interactive manner. Embodiments of the present invention provide a data analyzer with one or more asset diagnostic models. An asset diagnostic model is configured to logically and systematically interact with a client asset and analyze operational parameter data obtained from the client asset to diagnose a problem with the client asset and/or to predict or forecast future problems or conditions of the client asset.

Abstract: Systems and methods for scoring, ranking, and allocating mobile and/or fixed client assets. Embodiments of the present invention relate to the characterization or assessment of client assets with respect to the health of the client assets, the ranking of the client assets according to the characterization or assessment, and the allocating of the client assets to tasks or missions based on the ranking and/or mission parameters.

Abstract: Method and system are provided for processing a new diagnostics case relative to historical case data for a machine undergoing diagnostics. The method allows providing a database storing historical case data for the machine undergoing diagnostics. The method further allows calculating a degree of similarity between the new case and respective cases stored in the database. A list of neighboring cases is determined relative to the new case based on the calculated degree of similarity between the new case and the respective cases stored in the database. The list of neighboring cases is processed to determine a ranking for possible corrective actions for the new case. A corrective action is selected for the new case based on the ranking of the possible corrective actions for the new case.

Abstract: A method and apparatus for determining the root cause of no trouble found events in a machine is disclosed. The actual faults occurring during a predetermined time interval prior to the no trouble found event are analyzed and correlated with the no trouble found events in an effort to identify those actual faults that have a high correlation with each no trouble found event. If a high correlation is not found, then the no trouble found event is analyzed off-line to determine the root cause.

Abstract: An analysis scheduler for scheduling the automatic processing of performance data through a plurality of analysis tools is disclosed. Performance data provided to some of the tools by the analysis scheduler may be specified to be within a predetermined (but variable) look-back period. The analysis tools identify faults and anomalous conditions and also create repair recommendations, and automatically create problem cases when conditions warrant, or update existing problem cases with additional data, all under control of the analysis scheduler. The problem cases are reviewed by a human user and then forwarded to the railroad for implementation.

Abstract: A method and apparatus for determining when to close a problem case associated with a machine that includes identifying at least one failure condition associated with the problem case, determining whether the failure condition is repeated after a recommended fix instruction is executed and closing the problem case if the failure condition does not repeat within a predetermined amount of time after the fix instruction has been executed. The machine may be a remote machine such as a locomotive and electronic data indicative of the failure condition may be transmitted from the remote machine to a control center over a telecommunications medium such as the Internet. The control center may include a processor for managing the electronic data that may be transmitted from a plurality of remote machines.

Abstract: The present invention discloses system and method for analyzing operational parameter data from a malfunctioning locomotive or other large land-based, self-powered transport equipment. The method allows for receiving new operational parameter data comprising a plurality of anomaly definitions from the malfunctioning equipment. The method further allows for selecting a plurality of distinct anomaly definitions from the new operational parameter data. Respective generating steps allow for generating at least one distinct anomaly definition cluster from the plurality of distinct anomaly definitions and for generating a plurality of weighted repair and distinct anomaly definition cluster combinations. An identifying step allows for identifying at least one repair for the at least one distinct anomaly definition cluster using the plurality of weighted repair and distinct anomaly definition cluster combinations.

Abstract: A system (830) and method (800) for diagnosing a malfunctioning machine. A fault event is selected (806) together with sequential operating parameter data (808) from a selectively focused time interval about the fault event for evaluation of a machine (810). The selectively focused time interval may include data occurring just before, just after, or spanning the fault event. Characterizing information such as slope, rate of change, and absolute sign of the data may be derived (809) from the operating parameter data over the selectively focused time interval and used in the diagnosis. The fault event and operating parameter data may be compared to existing cases in a case database (834). A set of rules (817) or candidate anomalies (841) may be executed over the operating parameter data to further improve the accuracy of the diagnosis.

Abstract: Method and system are provided for processing a new diagnostics case relative to historical case data for a machine undergoing diagnostics. The method allows providing a database storing historical case data for the machine undergoing diagnostics. The method further allows calculating a degree of similarity between the new case and respective cases stored in the database. A list of neighboring cases is determined relative to the new case based on the calculated degree of similarity between the new case and the respective cases stored in the database. The list of neighboring cases is processed to determine a ranking for possible corrective actions for the new case. A corrective action is selected for the new case based on the ranking of the possible corrective actions for the new case.

Abstract: An analysis scheduler for scheduling the automatic processing of performance data through a plurality of analysis tools is disclosed. Performance data provided to some of the tools by the analysis scheduler may be specified to be within a predetermined (but variable) look-back period. The analysis tools identify faults and anomalous conditions and also create repair recommendations, and automatically create problem cases when conditions warrant, or update existing problem cases with additional data, all under control of the analysis scheduler. The problem cases are reviewed by a human user and then forwarded to the railroad for implementation.

Abstract: The present invention discloses system and method for analyzing operational parameter data from a malfunctioning locomotive or other large land-based, self-powered transport equipment. The method allows for receiving new operational parameter data comprising a plurality of anomaly definitions from the malfunctioning equipment. The method further allows for selecting a plurality of distinct anomaly definitions from the new operational parameter data. Respective generating steps allow for generating at least one distinct anomaly definition cluster from the plurality of distinct anomaly definitions and for generating a plurality of weighted repair and distinct anomaly definition cluster combinations. An identifying step allows for identifying at least one repair for the at least one distinct anomaly definition cluster using the plurality of weighted repair and distinct anomaly definition cluster combinations.

Abstract: A system and method are disclosed for aiding a field engineer in the field such as at a remote service facility in analyzing a fault log of a malfunctioning machine such as a locomotive. The method includes obtaining data associated with operation of the malfunctioning machine from a user at a second computing unit coupled via a communications network such as the Internet to a first computing unit such as a centrally located server operable to provide data associated with analysis of the malfunctioning machine, and providing at the second computing unit at least one of a diagnosis of and a repair for the malfunctioning machine based on the data associated with the operation of the malfunctioning machine and the data associated with analysis of the malfunctioning machine.

Abstract: A method and apparatus for determining the root cause of no trouble found events in a machine is disclosed. The actual faults occurring during a predetermined time interval prior to the no trouble found event are analyzed and correlated with the no trouble found events in an effort to identify those actual faults that have a high correlation with each no trouble found event. If a high correlation is not found, then the no trouble found event is analyzed off-line to determine the root cause.

Abstract: A method for analyzing fault data specific to a machine comprising a plurality of subsystems, said method comprising collecting fault data from a machine experiencing a malfunction, filtering said fault data with a noise-reduction filter to produce noise-reduced fault data, establishing fault rules specific to a subsystem of said machine, applying fault rules specific to said subsystem to noise-reduced fault data, and predicting at least one repair specific to said subsystem based on said fault rules and said noise-reduced fault data.

Abstract: A method and apparatus for determining when to close a problem case associated with a machine that includes identifying at least one failure condition associated with the problem case, determining whether the failure condition is repeated after a recommended fix instruction is executed and closing the problem case if the failure condition does not repeat within a predetermined amount of time after the fix instruction has been executed. The machine may be a remote machine such as a locomotive and electronic data indicative of the failure condition may be transmitted from the remote machine to a control center over a telecommunications medium such as the Internet. The control center may include a processor for managing the electronic data that may be transmitted from a plurality of remote machines.