Abstract: A system may include a processor to receive vehicle data from a vehicle system at a first location and communicate the data to a second location. The processor may integrate the data into a database of diagnostic data at the second location and identify a diagnostic code that indicates an expected operation of the vehicle system or an unexpected operation. The processor may determine a maintenance operation based on the diagnostic code. A method may include receiving vehicle data from a vehicle system at a first location and communicating the vehicle data to a second location. The method may include integrating the vehicle data into a database of first diagnostic data and identifying a diagnostic code that indicates whether the vehicle data represents an expected operation of the vehicle system or an unexpected operation of the vehicle system. The method may include determining a maintenance operation based on the code.

Abstract: Systems and methods described herein relate to indicating a repair to perform on an asset based on historic data related to a repair on the asset and/or sensor data associated with the asset. An evaluate component aggregates information related an asset such as a repair performed or data from a sensor. A repair evaluation component indicates a repair to perform on the asset based on at least one of the data from the sensor or the information related to the asset. By utilizing asset-specific information and historical data, repair schedules for assets can be more accurate and thereby reducing untimely repairs.

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: 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 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: 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 continuous parameter data from a malfunctioning locomotive or other large land-based, self-powered transport equipment. The method allows for receiving new continuous 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 continuous 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 process and system for populating a database of repair codes used by respective diagnostic tools to identify repairs of respective machines is provided. The process allows for collecting a list of available repair codes. The process further allows for executing expert analysis upon the collected list so as to determine compatibility of the respective repair codes with the diagnostic tools. A customizing step allows for customizing the list of repair codes based upon the executed expert analysis, and a storing step allows for storing the customized list of repair codes in the database of repair codes.

Abstract: Computerized method and system for identification and evaluation of a repair likely to prevent a failure of a mobile asset is provided. The method allows collecting data indicative of an incipient malfunction in the mobile asset (e.g., 1006). The method further allows collecting usage data indicative of usage of the mobile asset (e.g., 1002). The usage data is processed relative to historical data collected from a fleet of corresponding mobile assets to generate a usage profile for that asset (e.g., 1004). The data indicative of incipient malfunctions is processed to generate a prediction of a failure in the mobile asset and at least one repair likely to prevent the failure of the mobile asset (e.g., 1010). A repair weight indicative of a probability that the repair will prevent the predicted failure is determined (e.g., 466). The repair weight is adjusted based on the usage profile of the asset (e.g.

Abstract: The present invention discloses a system and method for analyzing fault log data from a malfunctioning machine. The system comprises a processor for receiving new fault log data comprising a plurality of faults from the malfunctioning machine and selecting a plurality of distinct faults from the new fault log data. The processor generates at least one distinct fault cluster from the selected plurality of distinct faults. Thereafter, the processor predicts at least one repair for at least one distinct fault cluster using a plurality of predetermined weighted repair and distinct fault cluster combinations.

Abstract: A method for analyzing fault log data and snapshot operational parameter data from a machine undergoing diagnostics is provided. A receiving step allows for receiving fault log data comprising a plurality of faults from the machine. Respective executing steps allow for executing a set of noise-reduction filters upon the received fault log data to generate noise-reduced fault log data, and for executing a set of candidate snapshot anomalies upon the noise-reduced data to generate data predictive of malfunctions of the machine.