Abstract: A method to predict remaining life of a target is disclosed. The method includes receiving information regarding a behavior of the target, and identifying from a database at least one piece of equipment having similarities to the target. The method further includes retrieving from the database data prior to an end of the equipment useful life, the data having a relationship to the behavior, evaluating a similarity of the relationship, predicting the remaining life of the target based upon the similarity, and generating a signal corresponding to the predicted remaining equipment life.

Abstract: Monitoring dynamic units that operate in complex, dynamic environments, is provided in order to classify and track unit behavior over time. When domain knowledge is available, feature-based models may be used to capture the essential state information of the units. When domain knowledge is not available, raw data is relied upon to perform this task. By analyzing logs of event messages (without having access to their data dictionary), embodiments allow the identification of anomalies (novelties). Specifically, a Normalized Compression Distance (such as one based on Kolmogorov Complexity) may be applied to logs of event messages. By analyzing the similarity and differences of the event message logs, units are identified that did not experience any abnormality (and locate regions of normal operations) and units that departed from such regions. Of particular interest is the detection and identification of units' epidemics, which is defined as sustained/increasing numbers of anomalies over time.

Abstract: A method and system for creating healthy operating envelope from only data samples obtained during normal operation/behavior of dynamic systems is provided. This method determines healthy operating envelope by clustering a stream of discrete event code sequences from the underlying system under normal operation condition only. The method is unsupervised, that is, requiring no prior knowledge of event code patterns corresponding to different operation conditions. Such created envelope can be used for fault detection and health monitoring of dynamic systems.

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 system of forecasting reliability of an asset is provided. The method includes identifying peer units of the asset by using selected criteria, performing a search for the peer units based upon the selected criteria, and constructing local predictive models using the peer units. The method also includes estimating the future behavior of the asset based upon the local predictive models and dynamically updating the local predictive models to reflect at least one change in the criteria.

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: 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: 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: 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: The present invention discloses a system and computer-implemented method for analyzing a fault log from a malfunctioning machine. The method includes receiving, from the malfunctioning machine, at least one of at least one fault code and at least one data code, at least one fault code and at least one anomaly code, and at least one data code and at least one anomaly code, and determining at least one of a cause of and a repair for the malfunctioning machine based on the at least one of the at least one fault code and the at least one data code, the at least one fault code and the at least one anomaly code, and the at least one data code and the at least one anomaly code. The method desirably includes receiving a fault log comprising at least one fault code and at least one data pack, parsing the at least one data pack, and generating at least one data pack code for a portion of the at least one parsed data pack.

Abstract: A system for at least a partial underwriting of insurance policies is described. based on the similarity to previous insurance applications, a decision on the current request for underwriting may be made this decision-making process represents an analogical approach to the placement of an insurance application to an underwriting category, whereby a given insurance application request is compared to previous requests.

Abstract: A process for at least a partial underwriting of insurance policies is described. Based on the similarity to previous insurance applications, a decision on the current request for underwriting may be made. This decision-making process represents an analogical approach to the placement of an insurance application to an underwriting category, whereby a given insurance application request is compared to previous requests.

Abstract: An algorithm for improving the probability of identifying the repair that will correct a fault aboard a machine, such as a locomotive. The invention utilizes historical fault log and repair data and further calculates the number of times a particular fault occurs in a given number of days and also the number of times a particular fault occurs on each day. Averages are calculated for these results and when the number of fault occurrences exceed some or more of those averages, then these faults are deemed statistically significant for subsequent processing.

Abstract: The present invention is directed to a method for processing records to extract relevant, reusable diagnostic information and make the information available in a form capable of being used by field engineers to speed the diagnosis and repair or adjustment of equipment.

Abstract: The present invention discloses a system and method for processing repair data and fault log data from one or more machines to facilitate analysis of a malfunctioning machine. The system includes a repair data storage unit comprising a plurality of repairs and a fault log data storage unit comprising a plurality of faults. A processor generates a plurality of cases from the repair data and the fault log data. Each case comprises a repair and a plurality of distinct faults. The processor further generates, for each of the plurality of cases, at least one repair and distinct fault cluster combination, and assigns, to each of the repair and distinct fault cluster combinations, a weight, whereby weighted repair and distinct fault cluster combinations facilitate prediction of at least one repair for the malfunctioning machine.

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.