Intelligent analysis system and method for fluid-filled electrical equipment

• US 6,446,027 B1
• Filed: 09/17/1999
• Issued: 09/03/2002
• Est. Priority Date: 09/17/1999
• Status: Expired due to Term

• Current Assignee: Prolec Ge, S. De R.L. De C.V. (GE Aerospace), General Electric Company
• Original Assignee: Prolec Ge, S. De R.L. De C.V. (GE Aerospace), General Electric Company
• Inventors: Betancourt, Enrique, Coulter, Gregory Dennis, Crouse, John Charles, Delgado Cruz, Alfonso M., Jammu, Vinay Bhaskar, Azzaro, Steven Hector, Stokes, Edward Brittain, OʼKeeffe, Thomas Gary
• Primary Examiner(s): Bui, Bryan
• Application Number:
  US09/398,034
• Time in Patent Office: 1,082 Days
• Field of Search: 702/181, 702/182, 702/183, 702/184, 702/185, 706/45, 706/50, 706/52, 700/275, 700/281, 700/282, 340/5.22, 340/5.23, 340/5.25
• US Class Current: 702/183
• CPC Class Codes: G01R 31/14 Circuits therefor , e.g. for generating test voltages, sensing circuits G01R31/1209 - G01R31/1227 take precedence; for testing switches G01R31/327
• CPC Class Codes: G01R 31/3271 of high voltage or medium voltage devices G01R31/333 takes precedence
• CPC Class Codes: G01R 31/50 Testing of electric apparatus, lines, cables or components for short-circuits, continuity, leakage current or incorrect line connections testing of sparking plugs H01T13/58
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: H01F 27/12 Oil cooling

Abstract

An intelligent analysis apparatus and method for fluid filled electrical equipment includes sensors for measuring various parameters of the electrical equipment. Analytical models calculate parameters based on measurements of other parameters. The measured and calculated parameters are compared and the result of the comparison is used as an indicator in a causal network. The probabilities of the causal network are recalculated by a belief network. The analytical models are adjusted over time to account for acceptable changes in behavior of the equipment over time. The output of the causal network can be used for diagnostic and prognostic indication.

Claims

1. An intelligent analysis apparatus for fluid-filled electrical equipment of the type having components surrounded by fluid, said apparatus comprising:

plural sensors adapted to be coupled to electrical equipment having a containment vessel configured to contain a fluid and at least one electrical component disposed in said containment vessel, said sensors being configured to output signals indicative of plural operating parameters of said electrical equipment; and

a diagnostic device coupled to said sensors, said diagnostic device having a processor operative to determine operating characteristics of the electrical equipment based on at least one analytical model of the electrical equipment and the signals outputted by said sensors by applying values of parameters calculated by the at least one analytical model and values of parameters as indicated by the signals of said sensors in a causal network, wherein said diagnostic device compares a parameter calculated by the at least one analytical model with a corresponding measured parameter and uses a result of the comparison as an indicator in the causal network, and further wherein probabilities of the causal network are updated based on the probability of the indicators obtained from the analytical model or sensed parameters; and

still further wherein the variables of the at least one analytical model are adjusted over time in correspondence to acceptable behavioral changes of the electrical equipment over time.

2. An apparatus as recited in claim 1, wherein said sensors comprise a temperature sensor configured to output a signal indicative of fluid temperature inside the containment vessel of the electrical equipment, a gas sensor configured to output a signal indicative of gas content of fluid inside the containment vessel of the electrical equipment, a load sensor configured to output a signal indicative of the electrical load on the electrical equipment, and a pressure sensor configured to output a signal indicative of pressure in the containment vessel of the electrical equipment.

3. An apparatus as recited in claim 2, wherein said gas sensor is configured to output a signal indicative of a hydrogen content of fluid inside the containment vessel.

4. An apparatus as recited in claim 3, wherein the at least one analytical model comprises a temperature model and a hydrogen model.

5. An apparatus as recited in claim 4, wherein the at least one analytical model further comprises a pressure model.

6. An apparatus as recited in claim 2, wherein said gas sensor is configured to output a signal indicative of at least one of hydrogen, carbon monoxide, carbon dioxide, oxygen, nitrogen, hydrocarbons, and hydrocarbon derivatives.

7. An apparatus as recited in claim 1, wherein said sensors are adapted to be disposed inside the containment vessel, said apparatus further comprising means for conducting the signals from said sensors to said processor.

8. An apparatus as recited in claim 1, said diagnostic device further comprising a user interface module having a display for displaying an indication of the operating characteristics of the electrical equipment and an input device for permitting a user to input at least one of data and commands to said diagnostic device.

9. An apparatus as recited in claim 1, wherein said processor comprises a computer having a CPU and a memory device.

10. An apparatus as recited in claim 1, wherein the electrical equipment is a transformer.

11. An intelligent analysis apparatus for fluid-filled electrical transformers, said apparatus comprising:

plural sensors adapted to be coupled to a transformer having a containment vessel configured to contain a fluid and coil disposed in said containment vessel, said sensors being configured to output signals indicative of plural operating parameters of the transformer; and

a diagnostic device coupled to said sensors, said diagnostic device having a processor operative to determine operating characteristics of the transformer based on at least one analytical model of the transformer and the signals outputted by said sensors by applying values of parameters calculated by the at least one analytical model and values of parameters as indicated by the signals of said sensors in a causal network, wherein said diagnostic device compares a parameter calculated by the at least one analytical model with a corresponding measured parameter and uses a result of the comparison as an indicator in the causal network, and further wherein probabilities of the causal network are adjusted based on the probability of the indicators obtained from the analytical model or sensed parameters; and

still further wherein the at least one analytical model is adjusted over time in correspondence to acceptable behavioral changes of the transformer over time.

12. An apparatus as recited in claim 11, wherein said sensors comprise a temperature sensor configured to output a signal indicative of fluid temperature inside said containment vessel, a gas sensor configured to output a signal indicative of gas content of fluid inside said containment vessel, a load sensor configured to output a signal indicative of the electrical load on the transformer and a pressure sensor configured to output a signal indicative of pressure in said containment vessel.

13. An apparatus as recited in claim 12, wherein said gas sensor is configured to output a signal indicative of a hydrogen content of fluid inside said containment vessel.

14. An apparatus as recited in claim 13, wherein the at least one analytical model comprises a temperature model and a hydrogen model.

15. An apparatus as recited in claim 14, wherein the at least one analytical model comprises a pressure model.

16. An apparatus as recited in claim 12, wherein said gas sensor is configured to output a signal indicative of at least one of hydrogen, carbon monoxide, carbon dioxide, oxygen, nitrogen, hydrocarbons, and hydrocarbon derivatives.

17. An apparatus as recited in claim 11, wherein said processor is disposed outside of said containment vessel and said sensors are disposed inside said containment vessel, said system further comprising means for conducting signals from said sensors to said processor.

18. An apparatus as recited in claim 11, said diagnostic device further comprising a user interface module having a display for displaying an indication of the operating characteristics of the transformer and an input device for permitting a user to input at least one of data and commands to said diagnostic device.

19. An apparatus as recited in claim 11, wherein said processor comprises a computer having a CPU and a memory device.

20. An intelligent analysis apparatus for fluid-filled electrical equipment of the type having components surrounded by fluid, said apparatus comprising:

sensing means for sensing plural operating parameters of electrical equipment having a containment vessel configured to contain a fluid and at least one electrical component disposed in said containment vessel and for outputting signals indicative of the plural operating parameters of said electrical equipment; and

diagnostic means for determining operating characteristics of the electrical equipment based on at least one analytical model of the electrical equipment and the signals outputted by said sensing means by applying values of parameters calculated by the at least one analytical model and values of parameters as indicated by the signals of said sensing means in causal network, wherein said diagnostic means comprises means for comparing a parameter calculated by the at least one analytical model with a corresponding measured parameter and means for using a result of the comparison as an indicator in the causal network, and further wherein said diagnostic means comprises means for adjusting probabilities of the causal network based on the probability of the indicators obtained from the analytical model or sensed parameters; and

still further wherein said diagnostic means comprises means for adjusting variables of the at least one analytical model over time in correspondence to acceptable behavioral changes of the electrical equipment over time.

21. An apparatus as recited in claim 20, wherein said sensing means comprises temperature sensing means for outputting a signal indicative of fluid temperature inside said containment vessel, gas sensing means for outputting a signal indicative of gas content of fluid inside said containment vessel, load sensing means for outputting a signal indicative of the electrical load on the electrical equipment and pressure sensing means for outputting a signal indicative of pressure in said containment vessel.

22. An apparatus as recited in claim 21, wherein said gas sensing means comprises means for outputting a signal indicative of a hydrogen content of fluid inside said containment vessel.

23. An apparatus as recited in claim 22, wherein the at least one analytical model comprises a temperature model and a hydrogen model.

24. An apparatus as recited in claim 23, wherein the at least one analytical model comprises a pressure model.

25. An apparatus as recited in claim 21, wherein said gas sensing means comprises means for outputting a signal indicative of an amount of at least one of hydrogen, carbon monoxide, carbon dioxide, oxygen, nitrogen, hydrocarbons, and hydrocarbon derivatives.

26. An apparatus as recited in claim 20, further comprising means for conducting signals from said sensor means to said processor.

27. An apparatus as recited in claim 20, said diagnostic means further comprising user interface means for displaying an indication of the operating characteristics of the electrical equipment and input means for permitting a user to input at least one of data and commands to said diagnostic means.

28. An apparatus as recited in claim 20, wherein said diagnostic means comprises a computer having a CPU and a memory device.

29. An apparatus as recited in claim 20, wherein the electrical equipment comprises a transformer.

30. A method for intelligent analysis of fluid-filled electrical equipment of the type having components surrounded by fluid, said method comprising the steps of:

coupling plural sensors to electrical equipment having a containment vessel configured to contain a fluid and at least one electrical component disposed in said containment vessel;

sensing plural operating parameters of the electrical equipment with the sensors;

generating signals indicative of the plural operating parameters of the electrical equipment sensed in said sensing step; and

determining operating characteristics of the electrical equipment based on at least one analytical model of the electrical equipment and the signals generated in said generating step by applying values of parameters calculated by the at least one analytical model and values of parameters as indicated by the generated in said generating step in a causal network, wherein said determining step comprises the steps of comparing a parameter calculated by the at least one analytical model with a corresponding measured parameter as indicated by signals in said generating step and using a result of said comparing step as an indicator in the causal network, and further wherein said determining step comprises the step of adjusting the probabilities of the causal network based on the probability of the indicators obtained from the analytical model or sensed parameters; and

still further wherein said determining step comprises the step of adjusting variables of the at least one analytical model over time in correspondence to acceptable behavioral changes of the electrical equipment over time.

31. A method as recited in claim 30, wherein said sensing step comprises the steps of sensing temperature inside the containment vessel, sensing gas content of fluid inside the containment vessel, sensing the electrical load on the electrical equipment and sensing pressure in the containment vessel.

32. A method as recited in claim 31, wherein said step of sensing gas content comprises sensing a hydrogen content of fluid inside the containment vessel.

33. A method as recited in claim 32, wherein the at least one analytical model used in said determining step comprises a temperature model and a hydrogen model.

34. A method as recited in claim 33, wherein the at least one analytical model comprises a pressure model.

35. A method as recited in claim 31, wherein said step of sensing gas content comprises sensing at least one of hydrogen, carbon monoxide, carbon dioxide, oxygen, nitrogen, hydrocarbons, and hydrocarbon derivatives.

36. A method as recited in claim 30, further comprising the steps of displaying an indication of the operating characteristics of the electrical equipment and inputting at least one of data and commands.