Vehicle system prognosis device and method
First Claim
1. A method for determining a vehicle system prognosis, the method comprising:
- detecting a predetermined characteristic of a vehicle with one or more sensors onboard the vehicle;
obtaining a plurality of sensor signals corresponding to the predetermined characteristic from the one or more sensors;
receiving, with a processor onboard the vehicle, the plurality of sensor signals from the one or more sensors onboard the vehicle and determining, with the processor onboard the vehicle, an input time series of data based on the sensor signals;
generating, with the processor onboard the vehicle, a matrix of time series data based on the input time series of data;
clustering, with the processor onboard the vehicle, the matrix of time series data based on predetermined clustering criteria into a predetermined number of clusters;
generating a sparse temporal matrix, with the processor onboard the vehicle, based on the predetermined number of clusters, where each cluster comprises a hyperplane within the sparse temporal matrix;
extracting, with the processor onboard the vehicle, extracted features that are indicative of an operation of a vehicle system from the sparse temporal matrix based on data point behavior with respect to two or more hyperplanes within the sparse temporal matrix and determining an operational status of the vehicle system based on the extracted features; and
communicating, with the processor onboard the vehicle, the operational status of the vehicle system to an operator or crew member of the vehicle.
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Abstract
A method for determining a vehicle system prognosis includes detecting a predetermined characteristic of a vehicle with one or more sensors, obtaining a plurality of sensor signals corresponding to the predetermined characteristic, receiving the plurality of sensor signals from the one or more sensors and determining an input time series of data based on the sensor signals, generating, a matrix of time series data based on the input time series of data, clustering the matrix of time series data based on predetermined clustering criteria into a predetermined number of clusters, generating a sparse temporal matrix based on the predetermined number of clusters, extracting extracted features that are indicative of an operation of a vehicle system from the sparse temporal matrix and determining an operational status of the vehicle system based on the extracted features, and communicating the operational status of the vehicle system to an operator or crew member of the vehicle.
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Citations
20 Claims
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1. A method for determining a vehicle system prognosis, the method comprising:
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detecting a predetermined characteristic of a vehicle with one or more sensors onboard the vehicle; obtaining a plurality of sensor signals corresponding to the predetermined characteristic from the one or more sensors; receiving, with a processor onboard the vehicle, the plurality of sensor signals from the one or more sensors onboard the vehicle and determining, with the processor onboard the vehicle, an input time series of data based on the sensor signals; generating, with the processor onboard the vehicle, a matrix of time series data based on the input time series of data; clustering, with the processor onboard the vehicle, the matrix of time series data based on predetermined clustering criteria into a predetermined number of clusters; generating a sparse temporal matrix, with the processor onboard the vehicle, based on the predetermined number of clusters, where each cluster comprises a hyperplane within the sparse temporal matrix; extracting, with the processor onboard the vehicle, extracted features that are indicative of an operation of a vehicle system from the sparse temporal matrix based on data point behavior with respect to two or more hyperplanes within the sparse temporal matrix and determining an operational status of the vehicle system based on the extracted features; and communicating, with the processor onboard the vehicle, the operational status of the vehicle system to an operator or crew member of the vehicle. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A vehicle system prognosis device comprising:
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one or more sensors onboard a vehicle, the one or more sensors being configured to detect a predetermined characteristic of the vehicle system and generate a plurality of sensor signals corresponding to the predetermined characteristic; an indicator device; and a processor onboard the vehicle, the processor being connected to the one or more sensors and the indicator device and being configured to receive the plurality of sensor signals from the one or more sensors onboard the vehicle and determine an input time series of data based on the sensor signals; generate a matrix of time series data based on the input time series of data; cluster the matrix of time series data based on predetermined clustering criteria into a predetermined number of clusters; generate a sparse temporal matrix based on the predetermined number of clusters, where each cluster comprises a hyperplane within the sparse temporal matrix; extract extracted features that are indicative of an operation of a vehicle system from the sparse temporal matrix based on data point behavior with respect to two or more hyperplanes within the sparse temporal matrix and determine an operational status of the vehicle system based on the extracted features; and communicate the operational status of the vehicle system to an operator or crew member of the vehicle through the indicator device. - View Dependent Claims (11, 12, 13, 14, 15)
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16. A method for determining a vehicle system prognosis, the method comprising:
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detecting a predetermined characteristic of a vehicle with one or more sensors onboard the vehicle; obtaining a plurality of sensor signals corresponding to the predetermined characteristic from the one or more sensors; receiving, with a processor onboard the vehicle, the plurality of sensor signals from the one or more sensors onboard the vehicle and determining, with the processor onboard the vehicle, an input time series of data based on the sensor signals; generating, with the processor onboard the vehicle, a matrix of time series data within a data distribution space based on the input time series of data; clustering, with the processor onboard the vehicle, the matrix of time series data based on predetermined clustering criteria into a predetermined number of data regions of the data distribution space; generating a sparse temporal matrix, with the processor onboard the vehicle, based on data within the predetermined number of data regions, where each data region comprises a hyperplane within the sparse temporal matrix; extracting, with the processor onboard the vehicle, extracted features that are indicative of an operation of a vehicle system from the sparse temporal matrix based on data point behavior with respect to at least two hyperplanes within the sparse temporal matrix and determining an operational status of the vehicle system based on the extracted features; and communicating, with the processor onboard the vehicle, the operational status of the vehicle system to an operator or crew member of the vehicle. - View Dependent Claims (17, 18, 19, 20)
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Specification