Transient fault detection system and method
First Claim
1. A transient fault detection system for detecting transient faults in a turbine engine, the transient fault detection system comprising:
- a) a feature extractor, the feature extractor receiving measured turbine sensor data from the turbine engine during a transient condition, the feature extractor performing a principal component analysis, the principal component analysis extracting salient features from the measured turbine sensor data by transforming the measured sensor data into a substantially smaller set of uncorrelated variables; and
b) a classifier, the classifier receiving the extracted salient features and analyzing the extracted salient features to determine if a fault occurred during the transient condition, and wherein the classifier comprises a multilayer perceptron neural network classifier.
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Abstract
A transient fault detection system and method is provided that facilitates improved fault detection performance in transient conditions. The transient fault detection system provides the ability to detect symptoms of fault in engine that occur in transient conditions. The transient fault detection system includes a feature extractor that measures sensor data during transient conditions and extracts salient features from the measured sensor data. The extracted salient features are passed to a classifier that analyzes the extracted salient features to determine if a fault has occurred during the transient conditions. Detected faults can then be passed to a diagnostic system where they can be passed as appropriate to maintenance personnel.
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Citations
30 Claims
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1. A transient fault detection system for detecting transient faults in a turbine engine, the transient fault detection system comprising:
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a) a feature extractor, the feature extractor receiving measured turbine sensor data from the turbine engine during a transient condition, the feature extractor performing a principal component analysis, the principal component analysis extracting salient features from the measured turbine sensor data by transforming the measured sensor data into a substantially smaller set of uncorrelated variables; and b) a classifier, the classifier receiving the extracted salient features and analyzing the extracted salient features to determine if a fault occurred during the transient condition, and wherein the classifier comprises a multilayer perceptron neural network classifier. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. An apparatus comprising:
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a) a processor; b) a memory coupled to the processor; c) a transient fault detection program residing in the memory and being executed by the processor, the transient fault detection program including; i) a feature extractor, the feature extractor receiving measured turbine sensor data from the turbine engine during a transient condition, the feature extractor performing a principal component analysis, the principal component analysis extracting salient features from the measured turbine sensor data, by transforming the measured sensor data into a substantially smaller set of uncorrelated variables; and ii) a classifier, the classifier receiving the extracted salient features and analyzing the extracted salient features to determine if a fault occurred during the transient condition, and wherein the classifier comprises a multilayer perceptron neural network classifier. - View Dependent Claims (9, 10, 11, 12, 13, 14)
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15. A program product comprising:
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a) a transient fault detection program, the transient fault detection program including; i) a feature extractor, the feature extractor receiving measured turbine sensor data from the turbine engine during a transient condition, the feature extractor performing a principal component analysis, the principal component analysis extracting salient features from the measured turbine sensor data, by transforming the measured sensor data into a substantially smaller set of uncorrelated variables; and ii) a classifier, the classifier receiving the extracted salient features and analyzing the extracted salient features to determine if a fault occurred during the transient condition, and wherein the classifier comprises a multilayer perceptron neural network classifier; and b) computer-readable signal bearing media bearing said program. - View Dependent Claims (16, 17, 18, 19, 20, 21, 22, 23)
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24. A method of detecting faults in transient conditions in a turbine engine, the method comprising the steps of:
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a) receiving measured turbine sensor data from the turbine engine during a transient condition; b) extracting salient features from the measured turbine sensor data by performing a principal component analysis on the measured sensor data, the principal component analysis transforming the measured sensor data into a substantially smaller set of uncorrelated variables; and c) classifying the extracted salient features with a multilayer perceptron neural network to determine if a fault occurred during the transient condition. - View Dependent Claims (25, 26, 27, 28, 29, 30)
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Specification