DIAGNOSTIC ALGORITHM PARAMETER OPTIMIZATION
First Claim
1. A method for optimizing parameters of a plurality of selected diagnostic and/or prognostic algorithms in a tunable diagnostic algorithm library, the method comprising the steps of:
- a) supplying a plurality of sensed data sets to each of the selected algorithms, each of the sensed data sets having an actual diagnostic label associated therewith;
b) supplying a value for each parameter of each of the selected algorithms that are to be optimized;
c) generating a computed diagnostic label for each of the sensed data sets using each of the selected algorithms, a fault model, and the values for each parameter;
d) supplying each of the computed diagnostic labels and each of the actual diagnostic labels to a generic objective function, to thereby calculate an objective function value;
e) varying the value of one or more of the parameters using an optimization routine that repeats steps c)-e) until the objective function value is minimized.
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Abstract
A system and method are provided for optimizing parameters of a plurality of selected diagnostic and/or prognostic algorithms in a tunable diagnostic algorithm library. A plurality of sensed data sets having an actual diagnostic label associated therewith is supplied to each of the diagnostic algorithms. A value for each parameter of each of the algorithms that are to be optimized is supplied. A computed diagnostic label is generated for each of the sensed data sets using each of the selected algorithms, a fault model, and the values for each parameter, each of the computed diagnostic labels and each of the actual diagnostic labels are supplied to a generic objective function, to thereby calculate an objective function value, and the value of one or more of the parameters is varied using an optimization routine that repeats certain of these steps until the objective function value is minimized.
23 Citations
19 Claims
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1. A method for optimizing parameters of a plurality of selected diagnostic and/or prognostic algorithms in a tunable diagnostic algorithm library, the method comprising the steps of:
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a) supplying a plurality of sensed data sets to each of the selected algorithms, each of the sensed data sets having an actual diagnostic label associated therewith; b) supplying a value for each parameter of each of the selected algorithms that are to be optimized; c) generating a computed diagnostic label for each of the sensed data sets using each of the selected algorithms, a fault model, and the values for each parameter; d) supplying each of the computed diagnostic labels and each of the actual diagnostic labels to a generic objective function, to thereby calculate an objective function value; e) varying the value of one or more of the parameters using an optimization routine that repeats steps c)-e) until the objective function value is minimized. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A method for optimizing parameters of one or more diagnostic algorithms that are configured to supply one or more computed fault labels, comprising the steps of:
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a) supplying a plurality of sensed data sets to each of the one or more diagnostic algorithms, each of the sensed data sets having an actual fault label associated therewith; b) supplying a value for each parameter of each of the one or more diagnostic algorithms that is to be optimized; c) determining all possible computed labels that each of the one or more diagnostic algorithms can generate; d) generating a confusion matrix having a plurality of entries and that includes a separate row for each of the possible computed fault labels and a separate column for each actual fault label; e) assigning a relative weight value to each entry in the confusion matrix to thereby generate a weighting matrix (W); f) generating a computed fault label for each of the sensed data sets using each of the one or more diagnostic algorithms and the initial values for each parameter, each computed fault label comprising a probability vector; g) supplying each of the computed fault labels, each of the actual fault labels, and the weighting matrix to a generic objective function, to thereby calculate an objective function value; and h) varying the value of one or more of the parameters using an optimization routine that repeats steps f)-h) until the objective function value is minimized. - View Dependent Claims (9, 10, 11, 12)
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13. A system for optimizing parameters of a plurality of diagnostic algorithms in a tunable diagnostic algorithm library, the system comprising:
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a processor configured to implement each of the diagnostic algorithms and a fault model, and to receive (i) a plurality of sensed data sets, each having an actual diagnostic label associated therewith, and (ii) a value for each parameter of each of the diagnostic algorithms that are to be optimized, the processor further configured to; a) generate a computed diagnostic label for each of the sensed data sets using each of the prognostic algorithms and the initial values for each parameter; b) supply each of the computed diagnostic labels and each of the actual diagnostic labels to a generic objective function, to thereby calculate an objective function value; and c) selectively vary the value of one or more of the parameters using an optimization routine that repeats steps a)-c) until the objective function value is minimized. - View Dependent Claims (14, 15, 16, 17, 18, 19)
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Specification