SPC fault detection and diagnostics algorithm

• US 9,977,409 B2
• Filed: 12/12/2011
• Issued: 05/22/2018
• Est. Priority Date: 03/02/2011
• Status: Active Grant

• Current Assignee: Carrier Corporation (Carrier Global Corporation)
• Original Assignee: Carrier Corporation (Carrier Global Corporation)
• Inventors: Giering, Michael J., Tewari, Ashutosh
• Primary Examiner(s): Ngon, Ricky
• Application Number:
  US13/995,444
• Publication Number:
  US 20140142727A1
• Time in Patent Office: 2,353 Days
• Field of Search: 702183
• CPC Class Codes: F24F 11/30 for purposes related to the operation of the system, e.g. for safety or monitoring
• CPC Class Codes: F24F 11/32 Responding to malfunctions or emergencies
• CPC Class Codes: F24F 11/38 Failure diagnosis
• CPC Class Codes: F24F 11/52 Indication arrangements, e.g. displays
• CPC Class Codes: F24F 11/62 characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
• CPC Class Codes: F24F 11/64 using pre-stored data
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G05B 23/0235 based on a comparison with predetermined threshold or range, e.g. "classical methods", carried out during normal operation; threshold adaptation or choice; when or how to compare with the threshold
• CPC Class Codes: G05B 23/027 Alarm generation, e.g. communication protocol; Forms of alarm
• CPC Class Codes: G05B 9/05 fluidic
• CPC Class Codes: G05D 23/1917 using digital means
• CPC Class Codes: G06N 5/046 Forward inferencing; Production systems

Abstract

A method for diagnosing a fault condition in a climate system is disclosed and a computer program product for doing the same. The climate system may be an HVAC system. The method comprises receiving current data from a climate system in a fault condition, calculating an anomaly score for the climate system from a first set of transition probabilities based on the current data and a second set of transition probabilities based on the climate system operating in a normal condition, and generating automatically a diagnosis of a first problem causing the fault condition when the anomaly score is above a predefined threshold. In an embodiment, the current data may include a plurality of operational Parameters of the climate system.

Claims

1. A method for diagnosing a fault condition in a climate system, the method comprising:

receiving current parameters from a climate system in the fault condition, the current parameters including a plurality of current measured and estimated data from the climate system;

determining a first set of transition probabilities based on the current parameters, the first set of transition probabilities providing a likelihood that a current operating condition of the climate system will transition to a respective condition;

determining a second set of transition probabilities based on historical parameters from the climate system operating under normal conditions, the historical parameters including a plurality of historical measured and estimated data from the climate system, the second set of transition probabilities providing a likelihood that the climate system will transition to a respective condition under normal conditions;

calculating an anomaly score for the climate system from the first set of transition probabilities and the second set of transition probabilities;

when the anomaly score is above a predefined threshold, generating automatically a diagnosis of a first problem causing the fault condition;

altering operation of the climate system in response to the diagnosis of the first problem, the altering operation of the climate system comprising replacing at least one mechanical component of the climate system.

2. The method of claim 1, wherein the climate system is an HVAC system.

3. The method of claim 1, wherein the climate system is a refrigeration system.

4. The method of claim 1 further comprising determining a probability of a progression of the climate system from a first condition class to a second condition class.

5. The method of claim 4, wherein the first condition class and the second condition class are based on normal operating conditions.

6. The method of claim 4, wherein the first condition class and the second condition class are based on the current parameters.

7. The method of claim 6 further comprising displaying on a user interface a probability distribution for the first condition class.

8. The method of claim 1, further comprising determining for the climate system a baseline model derived, at least in part, from application of linear iterative Singular Value Decomposition to the historical parameters in combination with the application of Probabilistic Latent Semantic Analysis to determine a plurality of condition classes from residual score XR.

9. The method of claim 8, further comprising determining transition probabilities during normal operation of the climate system between each of the condition classes using a Markov Model.

10. The method of claim 8, further comprising updating the baseline model for a change in the refrigeration system equipment.

11. The method of claim 8, wherein each condition class comprises co-occurring problems.

12. The method of claim 8, further comprising generating for each condition class a probability distribution.

13. The method of claim 1, further comprising displaying on a user interface recommended corrective action based on the diagnosis.

14. The method of claim 1 further comprising diagnosing a second problem in the climate system that co-exists with the first problem.

15. The method of claim 1 further comprising:

determining a first class and a second class of anomaly groupings;

determining a probability of the progression of the refrigeration system from the first class of anomaly groupings to the second class of anomaly groupings;

calculating the anomaly score for the refrigeration system in response to the probability of the progression of the refrigeration system from the first class of anomaly groupings to the second class of anomaly groupings.

16. The method of claim 15, further comprising determining a plurality of condition classes based on the parameters received from the refrigeration system.

17. The method of claim 16, wherein each condition class comprises co-occurring problems.

18. The method of claim 16, further comprising matching a probability distribution for a condition class to information stored in a database to determine the first problem.

19. The method of claim 15 further comprising displaying on a user interface recommended corrective action based on the diagnosis.