Asset failure prediction with location uncertainty
First Claim
1. A method, comprising:
- logically dividing a railroad network into segments each of a specified length, the railroad network comprising a railroad network infrastructure that includes a plurality of data sources, the plurality of data sources comprising sensors configured to monitor operational aspects of components of the railroad network;
collecting data from the plurality of data sources with respect to monitored operational aspects of the components;
identifying, via a computer processor that is communicatively coupled to the plurality of data sources, geo-defects and approximated locations of the geo-defects occurring at each inspection run for each of the segments;
resolving location uncertainty of the approximated locations of each of the geodefects based on geo-defect type, geo-defect amplitude, and location proximity for corresponding geo-defects assessed at each inspection run, wherein the corresponding geo-defects are determined by matching identified geo-defects from multiple inspection runs within each segment of a specified length;
calculating, via the computer processor, a rate of increase in amplitude of each of the geo-defects for each of the segments between inspection runs;
predicting a deterioration rate for each of the geo-defects based on the calculating;
upon determining multiple geo-defects exist for one of the segments at one of the inspection runs and at least one geo-defect exists for the one of the segments at another of the inspection runs, aggregating the multiple geo-defects to reflect the single geo-defect;
determining an instantaneous rate of failure probability, the determining of the instantons rate of failure probability comprising for each of the segments;
calculating a likelihood of the derailment occurring at a time t;
calculating a likelihood that the segment will survive until time t; and
calculating the instantaneous rate of failure probability at time t given that the derailment has not occurred until at least time t by dividing the likelihood of the derailment occurring at time t by the likelihood that the segment will survive until time t;
generating a repair decision for each of the geo-defects based on one or more of the predicting, the calculated likelihood of derailment, or the determined instantaneous rate of failure probability; and
selectively repairing one or more of the geo-defects based on the repair decision.
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Accused Products
Abstract
Geo-defect repair modeling with location uncertainty is provided. A method includes logically dividing a railroad network into segments each of a specified length. The method also includes identifying, via a computer processor, geo-defects and approximated locations of the geo-defects occurring at each inspection run for each of the segments. The method also includes calculating, via the computer processor, a rate of increase in amplitude of each of the geo-defects for each of the segments between inspection runs, determining a correlation of the geo-defects between the inspection runs as a function of the approximated locations, and predicting a deterioration rate for each of the geo-defects based on the calculating.
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Citations
16 Claims
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1. A method, comprising:
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logically dividing a railroad network into segments each of a specified length, the railroad network comprising a railroad network infrastructure that includes a plurality of data sources, the plurality of data sources comprising sensors configured to monitor operational aspects of components of the railroad network; collecting data from the plurality of data sources with respect to monitored operational aspects of the components; identifying, via a computer processor that is communicatively coupled to the plurality of data sources, geo-defects and approximated locations of the geo-defects occurring at each inspection run for each of the segments; resolving location uncertainty of the approximated locations of each of the geodefects based on geo-defect type, geo-defect amplitude, and location proximity for corresponding geo-defects assessed at each inspection run, wherein the corresponding geo-defects are determined by matching identified geo-defects from multiple inspection runs within each segment of a specified length; calculating, via the computer processor, a rate of increase in amplitude of each of the geo-defects for each of the segments between inspection runs; predicting a deterioration rate for each of the geo-defects based on the calculating; upon determining multiple geo-defects exist for one of the segments at one of the inspection runs and at least one geo-defect exists for the one of the segments at another of the inspection runs, aggregating the multiple geo-defects to reflect the single geo-defect; determining an instantaneous rate of failure probability, the determining of the instantons rate of failure probability comprising for each of the segments; calculating a likelihood of the derailment occurring at a time t; calculating a likelihood that the segment will survive until time t; and calculating the instantaneous rate of failure probability at time t given that the derailment has not occurred until at least time t by dividing the likelihood of the derailment occurring at time t by the likelihood that the segment will survive until time t; generating a repair decision for each of the geo-defects based on one or more of the predicting, the calculated likelihood of derailment, or the determined instantaneous rate of failure probability; and selectively repairing one or more of the geo-defects based on the repair decision. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A computer program product comprising a computer-readable storage medium having program code embodied thereon, which when executed by a computer processor, causes the computer processor to implement a method, the method comprising:
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logically dividing a railroad network into segments each of a specified length, the railroad network comprising a railroad network infrastructure that includes a plurality of data sources, the plurality of data sources comprising sensors configured to monitor operational aspects of components of the railroad network; collecting data from the plurality of data sources with respect to monitored operational aspects of the components; identifying geo-defects and approximated locations of the geo-defects occurring at each inspection run for each of the segments; resolving location uncertainty of the approximated locations of each of the geodefects based on geo-defect type, geo-defect amplitude, and location proximity for corresponding geo-defects assessed at each inspection run, wherein the corresponding geo-defects are determined by matching identified geo-defects from multiple inspection runs within each segment of a specified length; calculating a rate of increase in amplitude of each of the geo-defects for each of the segments between inspection runs; and predicting a deterioration rate for each of the geo-defects based on the calculating; upon determining multiple geo-defects exist for one of the segments at one of the inspection runs and at least one geo-defect exists for the one of the segments at another of the inspection runs, aggregating the multiple geo-defects to reflect the single geo-defect; determining an instantaneous rate of failure probability, the determining of the instantons rate of failure probability comprising for each of the segments; calculating a likelihood of the derailment occurring at a time t; calculating a likelihood that the segment will survive until time t; and calculating the instantaneous rate of failure probability at time t given that the derailment has not occurred until at least time t by dividing the likelihood of the derailment occurring at time t by the likelihood that the segment will survive until time t; generating a repair decision for each of the geo-defects based on one or more of the predicting, the calculated likelihood of derailment, or the determined instantaneous rate of failure probability; and selectively repairing one or more of the geo-defects based on the repair decision. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16)
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Specification