AUTOMATED KERNEL EXTRACTION
First Claim
1. A method for automated segregation of kernels, comprising:
- collecting sensor data in a time series format;
labeling sensor data in a time series format as either normal, or one of one or more possible faults;
segmenting sensor data in a time series format into blocks having a substantially uniform slope with respect to time;
labeling the blocks as having a rising, falling, or flat slope;
joining adjacent blocks with slopes having a same sign;
identifying candidate kernels;
convoluting the sensor data in a time series format with candidate kernels;
applying a feature selection method to determine which kernels have discriminatory power; and
training a fault classification system based on kernels having discriminatory power.
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Accused Products
Abstract
A method and system for automatically developing a fault classification system from time series data. The sensors need not have been intended for diagnostic purposes (e.g., control sensors). These methods and systems are functionally independent of knowledge related to a particular equipment system, thereby allowing seamless application to multiple systems, regardless of the suite of sensors in each system. Because this algorithm is totally automated, substantial savings in time and development cost can be achieved. The algorithm results in a classification system and a set of features that might be used to develop alternative classification systems without human intervention.
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Citations
20 Claims
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1. A method for automated segregation of kernels, comprising:
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collecting sensor data in a time series format; labeling sensor data in a time series format as either normal, or one of one or more possible faults; segmenting sensor data in a time series format into blocks having a substantially uniform slope with respect to time; labeling the blocks as having a rising, falling, or flat slope; joining adjacent blocks with slopes having a same sign; identifying candidate kernels; convoluting the sensor data in a time series format with candidate kernels; applying a feature selection method to determine which kernels have discriminatory power; and training a fault classification system based on kernels having discriminatory power. - View Dependent Claims (2, 3, 4, 5, 6, 10)
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7. A method operable to develop a fault classification system based on the extracted features, comprising:
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collecting sensor data in a time series format; labeling sensor data in a time series format as either normal, or one of one or more possible faults; segmenting sensor data in a time series format into blocks having a substantially uniform slope with respect to time; labeling the blocks as having a rising, failing, or flat slope; joining adjacent blocks with slopes having a same sign; identifying candidate kernels; convoluting the sensor data in a time series format with candidate kernels; applying a feature selection method to determine which extracted features have discriminatory power; and training a fault classification system based on extracted features having discriminatory power. - View Dependent Claims (8, 9, 11, 12)
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13. A method operable to generating classifier systems for univariate or multivariate equipment sensor data, comprising:
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collecting univariate or multivariate equipment sensor data in a time series format; labeling univariate or multivariate equipment sensor data in a time series format as either normal, or one of one or more possible faults; segmenting univariate or multivariate equipment sensor data in a time series format into blocks having a substantially uniform slope with respect to time; labeling the blocks as having a rising, falling, or flat slope; joining adjacent blocks with slopes having a same sign; identifying candidate kernels; convoluting the univariate or multivariate equipment sensor data in a time series format with candidate kernels; applying a feature selection method to determine which extracted features have discriminatory power; and training a fault classification system based on extracted features having discriminatory power. - View Dependent Claims (14, 15, 16, 17, 18)
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19. A system operable to develop a fault classification system based on the extracted features, comprising:
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a data collection system operable to gather and store sensor data in a time series format; and a processing system operable to; receive the sensor data in a time series format; label the sensor data in a time series format as either normal, or one of one or more possible faults; segment sensor data in a time series format into blocks having a substantially uniform slope with respect to time; label the blocks as having a rising, falling, or flat slope; join adjacent blocks with slopes having a same sign; identifying candidate kernels; convolute the sensor data in a time series format with candidate kernels; apply a feature selection method to determine which extracted features have discriminatory power; and train a fault classification system based on extracted features having discriminatory power.
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20. A system operable to generating classifier systems for univariate or multivariate equipment sensor data, comprising:
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a data collection system operable to gather and store univariate or multivariate equipment sensor data in a time series format; and a processing system operable to; receive the univariate or multivariate equipment sensor data in a time series format; label the univariate or multivariate equipment sensor data in a time series format as either normal, or one of one or more possible faults; segment univariate or multivariate equipment sensor data in a time series format into blocks having a substantially uniform slope with respect to time; label the blocks as having a rising, falling, or flat slope; join adjacent blocks with slopes having a same sign;
identifying candidate kernels;convolute the univariate or multivariate equipment sensor data in a time series format with candidate kernels; apply a feature selection method to determine which extracted features have discriminatory power; and train a fault classification system based on extracted features having discriminatory power.
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Specification