System and method for detecting and diagnosing pump cavitation

• US 6,655,922 B1
• Filed: 08/10/2001
• Issued: 12/02/2003
• Est. Priority Date: 08/10/2001
• Status: Expired due to Term

• Current Assignee: Rockwell Automation Technologies Incorporated (Rockwell Automation, Inc.)
• Original Assignee: Rockwell Automation Technologies Incorporated (Rockwell Automation, Inc.)
• Inventors: Flek, Ondrej
• Primary Examiner(s): Thrope, Timothy
• Assistant Examiner(s): Sayoc, Emmanuel
• Application Number:
  US09/927,969
• Time in Patent Office: 844 Days
• Field of Search: 417/44.1, 417/53, 417/63, 417/473.1, 417/44.2, 417/43, 706/903, 706/904, 706/906, 415/17, 415/30, 415/47, 415/914, 73/13.5, 73/13.7, 73/310.4, 731/701.4
• US Class Current: 417/44.1
• CPC Class Codes: F04D 15/0088 Testing machines
• CPC Class Codes: F04D 15/0209 responsive to a condition of the working fluid F04D15/029 takes precedence
• CPC Class Codes: F04D 15/0245 responsive to a condition of the pump
• CPC Class Codes: F04D 29/669 especially adapted for liquid pumps F04D29/18 takes precedence
• CPC Class Codes: Y10S 706/904 Manufacturing or machine, e.g. agricultural machinery, machine tool
• CPC Class Codes: Y10S 706/906 Process plant

Abstract

The present invention provides cavitation detection systems and methods employing a classifier for detecting, diagnosing and/or classifying cavitation in a pumping system. The classifier can be integral to tie cavitation detection system and/or operatively coupled to the cavitation system via a controller, diagnostic device and/or computer. Parameters such as flow, pressure and motor speed arc measured and/or estimated, and then provided to a classifier system Such systems include Bayesian, Fuzzy Set, nonlinear regression, neural networks and other training systems, for example The classifier system provides a signal indicative of the existence and extent of cavitation. An exemplary classification system is presented that delineates cavitation extent into one or more of the following categories: 0 (no cavitation), 1 (incipient cavitation), 2 (medium cavitation), 3 (fill cavitation) and 4 (surging cavitation). The cavitation signal can be utilized for monitoring and/or controlling a pumping system to mitigate pump wear, failure and other conditions associated with cavitation.

Claims

1. A system for detecting cavitation in a motorized pumping system, comprising:

a measuring system adapted to measure pump flow and pressure data associated with the pumping system; and

an adaptive classifier system adapted to detect pump cavitation existence and extent according to the flow and pressure data.

2. The system of claim 1, wherein the classifier system comprises a neural network.

3. The system of claim 2, wherein the neural network is trained using back propagation.

4. The system of claim 1, wherein the measuring system comprises sensors for measuring suction pressure data and discharge pressure data associated with an inlet and an outlet, respectively, of the pumping system.

5. The system of claim 1, further comprising a speed sensor for measuring pump speed, wherein the classifier system is adapted to detect pump cavitation according to the flow, pressure, and speed data.

6. The system of claim 2, wherein the neural network is adapted to provide a cavitation signal indicative of the existence and extent of cavitation in the pumping system, further comprising a system adapted to change the operation of the pumping system according to the cavitation signal.

7. A system for detecting cavitation in a motorized pumping system, comprising:

an adaptive classifier system adapted to detect pump cavitation existence and extent according to flow and pressure data.

8. The system of claim 7, wherein the classifier system comprises a neural network receiving flow and pressure signals from flow and pressure sensors associated with the pumping system.

9. The system of claim 8, wherein the neural network is trained using back propagation.

10. The system of claim 9, wherein the neural network receives suction pressure data and discharge pressure data from suction and discharge pressure sensors associated with an inlet and an outlet, respectively, of the pumping system.

11. The system of claim 10, wherein the neural network further receives pump speed data from a speed sensor associated with the pumping system and wherein the neural network is adapted to detect pump cavitation according to the flow, pressure, and speed data.

12. The system of claim 11, wherein the neural network is adapted to provide a cavitation signal indicative of the existence and extent of cavitation in the pumping system.

13. The system of claim 11, further comprising means for changing the operation of the pumping system according to the cavitation signal.

14. A method of detecting cavitation in a pumping system having a motorized pump, comprising:

measuring pump flow and pressure data;

providing the flow and pressure data to an adaptive classifier system; and

detecting pump cavitation existence and extent according to the flow and pressure data using the classifier system.

15. The method of claim 14, wherein providing the flow and pressure data to a classifier system comprises providing flow and pressure data as inputs to a neural network.

16. The method of claim 15, wherein measuring pump flow and pressure data comprises reading flow and pressure sensors operatively associated with the pump so as to sense at least one flow and at least one pressure, respectively, associated with the pumping system.

17. The method of claim 16, wherein measuring pump pressure data comprises reading suction pressure data and discharge pressure data associated with an inlet and an outlet, respectively, of the pumping system.

18. The method of claim 17, further comprising teaching the classifier system.

19. The method of claim 18, further comprising:

measuring pump speed data;

providing the speed data to the classifier system; and

detecting pump cavitation existence and extent according to the flow, pressure, and speed data using the classifier system.

20. The method of claim 19, wherein detecting pump cavitation according to the flow, pressure, and speed data using the classifier system comprises providing a cavitation signal from the classifier system to the pumping system.

21. The method of claim 20, further comprising changing the operation of the pump according to the cavitation signal.

22. The method of claim 14, wherein detecting pump cavitation according to the flow, pressure using the classifier system comprises providing a cavitation signal from the classifier system to the pumping system.

23. The method of claim 22, further comprising changing the operation of the pump according to the cavitation signal.

24. The method of claim 22, wherein providing the flow and pressure data to a classifier system comprises providing flow and pressure data as inputs to a neural network, and wherein detecting pump cavitation according to the flow and pressure data comprises providing a cavitation signal from the classifier system indicative of the existence and extent of pump cavitation.

25. The method of claim 24, further comprising:

measuring pump speed data;

providing the speed data to the classifier system; and

detecting pump cavitation according to the flow, pressure, and speed data using the classifier system.

26. The method of claim 24, further comprising changing the operation of the pump according to the cavitation signal.

27. The method of claim 15, wherein detecting pump cavitation according to the flow and pressure data using the classifier system comprises providing a cavitation signal from the classifier system to the pumping system.

28. The method of claim 27, further comprising changing the operation of the pump according to the cavitation signal.

29. The method of claim 15, further comprising:

measuring pump speed data;

providing the speed data to the classifier system; and

detecting pump cavitation existence and extent according to the flow, pressure, and speed data using the classifier system.

30. The method of claim 14, further comprising diagnosing the extent of pump cavitation according to the flow and pressure data using the classifier system.

31. The method of claim 30, wherein detecting pump cavitation according to the flow, pressure, and speed data using the classifier system comprises providing a cavitation signal from the classifier system to the pumping system.

32. The method of claim 31, further comprising changing the operation of the pump according to the cavitation signal.

33. The method of claim 32, further comprising:

measuring pump speed data;

providing the speed data to the classifier system; and

detecting pump cavitation existence and extent according to the flow, pressure, and speed data using the classifier system.

34. The method of claim 31, wherein the cavitation signal comprises a classification of pump cavitation having one of a plurality of class values, wherein each of the plurality of class values is indicative of the extent of cavitation in the pumping system, and wherein at least one of the plurality of class values is indicative of no cavitation in the pumping system.