SYSTEM AND METHOD FOR DETECTING AND/OR DIAGNOSING FAULTS IN MULTI-VARIABLE SYSTEMS
First Claim
1. A method for detecting faulty operation of a HVAC system, the method including:
- receiving operational data from a plurality of components of the HVAC system;
processing the operational data in accordance with a plurality of dynamic machine learning fault detection models to generate a plurality of fault detection results,each fault detection model using a plurality of variables to model one or more components of the HVAC system and being adapted to detect normal or faulty operation of an associated component or set of components of the HVAC system; and
outputting the plurality of fault detection results.
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Abstract
A method for detecting faulty operation of a multi-variable system is described. The method includes receiving operational data from a plurality of components of the multi-variable system and processing the operational data in accordance with a plurality of dynamic machine learning fault detection models to generate a plurality of fault detection results. Each fault detection model uses a plurality of variables to model one or more components of the multi-variable system and is adapted to detect normal or faulty operation of an associated component or set of components of the multi-variable system. The plurality of fault detection results are output.
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Citations
48 Claims
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1. A method for detecting faulty operation of a HVAC system, the method including:
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receiving operational data from a plurality of components of the HVAC system; processing the operational data in accordance with a plurality of dynamic machine learning fault detection models to generate a plurality of fault detection results, each fault detection model using a plurality of variables to model one or more components of the HVAC system and being adapted to detect normal or faulty operation of an associated component or set of components of the HVAC system; and outputting the plurality of fault detection results. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 48)
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24. A method for detecting faulty operation of a multi-variable system, the method including:
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receiving operational data from a plurality of components of the multi-variable system; processing the operational data in accordance with a plurality of dynamic machine learning fault detection models to generate a plurality of fault detection results, each fault detection model using a plurality of variables to model one or more components of the multi-variable system and being adapted to detect normal or faulty operation of an associated component or set of components of the multi-variable system; and outputting the plurality of fault detection results. - View Dependent Claims (25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47)
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Specification