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Self-learning fault detection for HVAC systems

  • US 10,592,821 B2
  • Filed: 06/20/2016
  • Issued: 03/17/2020
  • Est. Priority Date: 06/19/2015
  • Status: Active Grant
First Claim
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1. A heating, ventilation and air conditioning (HVAC) system fault detection method for optimizing fault detection and diagnosis, comprising:

  • providing an electronic data gathering device configured to acquire data from one or more components associated with the heating, ventilation and air conditioning system;

    receiving, at a server, a plurality of signals indicative of sensed HVAC system operating parameters based on data acquired by the electronic data gathering device;

    identifying, at the server coupled to a database, a sensed operating parameter of the plurality of the signals indicative of sensed HVAC system operating parameters that exceeds a parameter threshold to determine a set of error parameters;

    normalizing, at the server, the sensed operating parameter according to a defined scale;

    determining, at the server, from the set of error parameters, a potential fault and a corresponding fault threshold;

    multiplying, at the server, each error parameter by a predetermined weighting factor to generate a set of weighted error parameters;

    summing, at the server, the set of weighted error parameters to generate a summed value;

    confirming, at the server, that the potential fault is a detected fault in response to a determination that the summed value exceeds the corresponding fault threshold;

    storing, in the database coupled to the server, a dataset including a set of optimization parameters comprising the parameter threshold, the predetermined weighting factor, and the corresponding fault threshold;

    applying an adjustment to the server to improve accuracy of the fault detection and diagnosis; and

    performing the applying step periodically based on a predetermined time interval or on a predetermined number of instances of receiving information related to the potential fault.

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