Systems and methods for statistical control and fault detection in a building management system

• US 9,069,338 B2
• Filed: 09/09/2013
• Issued: 06/30/2015
• Est. Priority Date: 06/22/2009
• Status: Active Grant

• Current Assignee: Johnson Controls Technology Company (Johnson Controls International plc)
• Original Assignee: Johnson Controls Technology Company (Johnson Controls International plc)
• Inventors: Drees, Kirk H., Kummer, James P.
• Primary Examiner(s): Fennema, Robert
• Assistant Examiner(s): STEVENS, THOMAS H
• Application Number:
  US14/021,971
• Publication Number:
  US 20140142760A1
• Time in Patent Office: 659 Days
• Field of Search: 700286-305
• US Class Current: 1/1
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G05B 2219/2642 Domotique, domestic, home control, automation, smart house
• CPC Class Codes: H02J 13/00001 characterised by the display of information or by user interaction, e.g. supervisory control and data acquisition systems [SCADA] or graphical user interfaces [GUI]
• CPC Class Codes: H02J 13/00002 characterised by monitoring
• CPC Class Codes: H02J 13/00016 using a wired telecommunication network or a data transmission bus
• CPC Class Codes: Y02B 70/30 Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
• CPC Class Codes: Y02B 70/3225 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y02B 90/20 Smart grids as enabling technology in buildings sector smart grids supporting the management or operation of end-user stationary applications in general, or like technologies with no associated climate change mitigation effect Y04S20/00
• CPC Class Codes: Y02E 60/00 Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
• CPC Class Codes: Y04S 10/30 State monitoring, e.g. fault, temperature monitoring, insulator monitoring, corona discharge
• CPC Class Codes: Y04S 10/40 Display of information, e.g. of data or controls
• CPC Class Codes: Y04S 20/00 Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
• CPC Class Codes: Y04S 20/20 End-user application control systems
• CPC Class Codes: Y04S 20/221 General power management systems
• CPC Class Codes: Y04S 20/222 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y04S 40/124 using wired telecommunication networks or data transmission busses

Abstract

A building management strategy includes using exponentially weighted moving averages with statistical models to detect changes in the behavior of the building management system. Detected changes in the behavior of the system may indicate a detected fault, a change in a predicted behavior, or a need for the statistical models to be updated.

Claims

1. A controller for a building management system comprising:

a processing circuit configured to at least one of receive or calculate an updated performance value for the building management system;

wherein the processing circuit is further configured to maintain at least one threshold parameter relative to a history of performance values, to determine an exponentially weighted moving average of the performance values, and to compare the moving average to the at least one threshold parameter, wherein the threshold parameter is maintained by multiplying an estimator of scale of the history by a constant value and at least one of adding or subtracting a result of the multiplication to or from a median of the history; and

wherein the processing circuit is further configured to generate an output that indicates a result of the comparison.

2. The controller of claim 1, wherein the processing circuit is further configured to update the threshold parameter automatically and without user input.

3. The controller of claim 1, wherein the threshold parameter is a threshold for a predicted power consumption and the performance values comprise measured power consumptions.

4. The controller of claim 1, wherein the processing circuit is further configured to cause a graphical user interface to be displayed on an electronic display device, wherein the graphical user interface comprises indicia that a fault has occurred.

5. A method of detecting faults in a building management system, the method comprising:

at a computer of the building management system, receiving first performance values for the building management system;

calculating an exponentially weighted moving average using the first performance values;

generating a threshold parameter by multiplying an estimator of scale of the first performance values by a constant value and at least one of adding or subtracting a result of the multiplication to or from a median of the first performance values;

comparing the moving average to the threshold parameter;

receiving new performance values for the building management system; and

updating the threshold parameter using the new performance values.

6. The method of claim 5, wherein updating the threshold parameter comprises:

generating a target parameter, wherein the target parameter is a median of a history of performance values;

generating an estimator of scale of the history, wherein the estimator of scale reduces an effect of outliers in the history;

using the estimator of scale and the target parameter to generate the threshold parameter; and

storing the threshold parameter in a memory of the computer.

7. The method of claim 6, wherein using the computer to generate at least one threshold parameter comprises:

determining if the history is autocorrelated;

applying an autoregressive model to the history; and

using the autoregressive model to generate the threshold parameter.

8. The method of claim 5, further comprising:

updating the threshold parameter automatically and without user input in response to a result of the comparison.

9. The method of claim 5, wherein updating the threshold parameter using the new performance values further comprises:

applying an anti-spike filter to the new performance values.

10. The method of claim 5, wherein the new performance values are measured power consumptions and the at least one threshold parameter is selected based on a model of a predicted power consumption.