Abstract: A method for fault detection includes selecting a measured parameter from a subsurface electrical device and obtaining a plurality of samples for the measured parameter. The method also includes removing at least one invalid sample from the plurality of samples to generate a remaining number of samples. The method further includes computing a diagnostic parameter based on the remaining number of samples, if the remaining number of samples is greater than a predefined threshold number and terminating the method otherwise. The method also includes obtaining a rule from a plurality of rules stored in a database, based on the diagnostic parameter. The rule is indicative of a standard operating condition of the subsurface electrical device. The method further includes evaluating whether the determined diagnostic parameter satisfies the obtained rule, to generate an output and determining a measured operating condition of the subsurface electrical device based on the output.

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 method for fault detection includes selecting a measured parameter from a subsurface electrical device and obtaining a plurality of samples for the measured parameter. The method also includes removing at least one invalid sample from the plurality of samples to generate a remaining number of samples. The method further includes computing a diagnostic parameter based on the remaining number of samples, if the remaining number of samples is greater than a predefined threshold number and terminating the method otherwise. The method also includes obtaining a rule from a plurality of rules stored in a database, based on the diagnostic parameter. The rule is indicative of a standard operating condition of the subsurface electrical device. The method further includes evaluating whether the determined diagnostic parameter satisfies the obtained rule, to generate an output and determining a measured operating condition of the subsurface electrical device based on the output.

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 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: 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 for determining anomaly conditions within a fleet of physical assets includes a central system having at least one computing device, the computing device including a processor and a memory device coupled to the processor and a database associated with the central system. The system includes a plurality of databases and a plurality of client devices associated with the fleet of physical assets. The system is configured to receive a first set of fleet data. The system is further configured to generate one or more computer-executable steps for detection of predicted anomalies. The system is configured to receive a first set of fleet asset data. The system is configured to detect at least one physical asset from the fleet of physical assets predicted to have at least one anomaly using the one or more computer-executable steps for detection of predicted anomalies and the first set of fleet asset data.

Abstract: A computer-implemented method for detecting a change in state of a physical asset is performed by a computer device. The computer device includes a processor and a memory device. The method includes receiving at least one input signal associated with the physical asset in a time period. The time period includes a first period and a second period. The method further includes receiving at least one output signal associated with the physical asset in the time period. The method also includes generating a predicted estimate and estimate residuals based upon the at least one input signal. The method additionally includes determining estimation errors. The method also includes detecting a probability of change in state of the physical asset. The method further includes transmitting the probability of change in state of the physical asset to a servicer of the physical asset.