Method and apparatus for diagnosing a pump system

• US 6,260,004 B1
• Filed: 12/31/1997
• Issued: 07/10/2001
• Est. Priority Date: 12/31/1997
• Status: Expired due to Term

• Current Assignee: Innovation Management Group, Inc.
• Original Assignee: Innovation Management Group, Inc.
• Inventors: Lenz, Gary A., Hays, Coy L., Brunson, Thomas A.
• Primary Examiner(s): SHAH, KAMINI S
• Application Number:
  US09/002,053
• Time in Patent Office: 1,287 Days
• Field of Search: 702/183, 702/166, 702/185, 702/34, 702/35, 731/68, 166/265, 166/266
• US Class Current: 702/183
• CPC Class Codes: F04D 15/0088 Testing machines
• 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

Abstract

An apparatus and method for diagnosing rotating equipment commonly used in the factory and process control industry are provided. The apparatus and method are intended for use in assisting a maintenance engineer in the diagnosis of turbines, compressors, fans, blowers and pumps. The preferred embodiments are an apparatus and method for diagnosing pumps, with a focus on centrifugal pumps. The apparatus and method are based on the comparison of the current pump signature curves resulting from the acquisition of process variables from sensors monitoring the current condition of the pump and the original or previous pump performance curve from prior monitoring or knowledge of the pump geometry, installation effects and properties of the pumped process liquid. The diagnostic apparatus and method can be applied to any rotating machine, but the apparatus and method for pumps are described herein.

Claims

1. A method for diagnosing rotating equipment comprising:

storing original data for constructing an original performance curve for the rotating equipment, said original data having a recognized recommended operating design regime;

acquiring process variables from operating rotating equipment;

inputting said process variables into a computing device;

obtaining a process data point from said process variables, said process data point representing an operating condition of the rotating equipment;

comparing said process data point with said original data; and

determining from said comparison of said process data point with said original data whether said rotating equipment is operating efficiently by determining whether said process data point is outside of said operating design regime.

2. The method according to claim 1, wherein said operating design regime is a BEP regime.

3. The method according to claim 1, wherein said step of determining if said process data point is outside of said operating regime further comprises determining from said comparison of said process data point with said original data whether said process data point is below said recommended operating design regime.

4. The method according to claim 1, wherein said step of determining if said process data point is outside of said operating regime further comprises determining from said comparison of said process data point with said original data whether said process data point is above said recommended operating design regime.

5. The method according to claim 1, wherein:

said rotating equipment is a pump; and

said step of determining if said process data point is outside of said operating regime further comprises determining from said comparison of said process data point with said original data whether said process data point is below said recommended operating design regime for determining if the pump is experiencing possible recirculation.

6. The method according to claim 1, wherein:

said rotating equipment is a pump; and

said step of determining if said process data point is outside of said operating regime further comprises determining from said comparison of said process data point with said original data whether said process data point is above said recommended operating design regime for determining if the rotating equipment is experiencing possible cavitation.

7. The method according to claim 1, further comprising the step of acquiring equipment condition monitoring variables during operation of said rotating equipment for verifying said step of determining whether said process data point is outside of said operating design regime.

8. The method according to claim 7, wherein said rotating equipment is a pump.

9. The method according to claim 8, further comprising:

constructing an original performance curve from said original data;

constructing a measured pump performance curve from said process variables; and

comparing said measured pump performance curve with said original pump performance curve for determining if the rotating equipment is cavitating.

10. A The method according to claim 8, wherein:

said original data is comprised of an original flow rate,

said process variable is comprised of measured flow rate, said method further comprising the steps of;

deducing that a pump seal may be leaking from comparing said original flow rate with said measured flow rate and finding a reduction in measured flow.

11. The method according to claim 10, wherein:

said equipment condition monitoring variables are comprised of;

measured seal leak sensor data;

said method further comprising the step of;

verifying that said pump seal is leaking by examining leak sensor data.

12. The method according to claim 7, wherein,

said original data is comprised of original condition dynamic pressure spectra having amplitude, frequency and phase components;

said equipment condition monitoring variables are comprised of measured dynamic pressure sensor spectra having amplitude, frequency and phase components;

said method further comprising the step of;

comparing at least one of said components selected from the group of amplitude, frequency and phase of said measured dynamic pressure sensor spectra with at least one of said components selected from the group of amplitude, frequency and phase of said original condition pressure spectra; and

determining from said comparison of said amplitude, frequency and phase components of said measured dynamic pressure sensor spectra with said amplitude, frequency and phase components of said original condition pressure spectra whether recirculation or cavitation exists.

13. The method according to claim 7, wherein,

said original data is comprised of at least one of:

original condition velocity vibration spectra having amplitude, frequency and phase components;

or

original condition acceleration vibration spectra having amplitude, frequency and phase components;

said equipment condition monitoring variables are comprised of at least one of;

measured velocity vibration spectra having amplitude, frequency and phase components; and

measured acceleration vibration spectra having amplitude, frequency and phase components;

said method further comprising the steps of;

comparing at least one of said components selected from the group of amplitude, frequency and phase of said original condition velocity vibration spectra with at least one of said components selected from the group of amplitude, frequency and phase of said measured velocity vibration spectra;

comparing at least one of said components selected from the group of amplitude, frequency and phase of said original condition acceleration vibration spectra with at least one of said components selected from the group of amplitude, frequency and phase of said measured acceleration vibration spectra; and

determining from said comparisons if impeller degradation exists.

14. The method according to claim 13, further comprising:

comparing said phase component of said original condition velocity vibration spectra with said phase component of said measured velocity vibration spectra;

comparing said phase component of said original condition acceleration vibration spectra with said phase component of said measured acceleration vibration spectra;

determining whether a phase shift has occurred; and

diagnosing impeller fouling.

15. The method according to claim 7, wherein,

said original data is comprised of at least one of:

original condition velocity vibration spectra having amplitude, frequency and phase components;

or

original condition acceleration vibration spectra having amplitude, frequency and phase components;

said equipment condition monitoring variables are comprised of at least one of;

measured velocity vibration spectra having amplitude, frequency and phase components;

or

measured acceleration vibration spectra having amplitude, frequency and phase components;

said method further comprising the steps of;

comparing at least one of said components selected from the group of amplitude, frequency and phase of said original condition velocity vibration spectra with at least one of said components selected from the group of amplitude, frequency and phase of said measured velocity vibration spectra;

comparing at least one of said components selected from the group of amplitude, frequency and phase of said original condition acceleration vibration spectra with at least one of said components selected from the group of amplitude, frequency and phase of said measured acceleration vibration spectra; and

determining from said comparisons if bearing degradation exists.

16. The method according to claim 7, wherein:

said equipment condition monitoring variables further comprise;

pump input torque data from a torque sensor; and

pump shaft angular velocity data from a shaft speed sensor; and

said original data further comprises original condition computed frictional torque;

said method further comprising the steps of;

calculating measured condition frictional torque in the rotating equipment;

comparing said measured condition frictional torque with said original condition frictional torque; and

diagnosing bearing, seal or wear plate wear.

17. The method according to claim 16, wherein:

said measured condition frictional torque is less than said original condition frictional torque;

said method further comprising diagnosing pump seal leakage.

18. The method according to claim 16, wherein:

said measured frictional torque is greater than said original condition frictional torque;

said method further comprising diagnosing that bearing friction is excessive.

19. The method according to claim 16, wherein:

said original data is comprised of original vibration velocity or acceleration spectra having amplitude, frequency and phase components;

said equipment condition monitoring data is further comprised of;

measured vibration velocity or acceleration spectra having amplitude, frequency and phase components;

said method further comprising the steps of;

determining from said frictional torque comparison that said bearing friction is excessive; and

comparing at least one of said components selected from the group of amplitude, frequency and phase of said original vibration velocity or acceleration spectra with at least one of said components selected from the group of amplitude, frequency and phase of said measured vibration velocity spectra; and

diagnosing radial bearing failure.

20. The method according to claim 7, wherein,

said original data is comprised of:

original radial bearing vibration velocity spectra having amplitude, frequency and phase components, or

original radial bearing acceleration spectra having amplitude, frequency and phase components;

said equipment condition monitoring variables are comprised of;

measured radial bearing vibration velocity spectra having amplitude, frequency and phase components, or

measured radial bearing acceleration spectra having an amplitude, frequency and phase components;

said method further comprising the steps of;

comparing at least one of said components selected from the group of amplitude, frequency and phase of said original radial bearing vibration velocity spectra with at least one of said components selected from the group of amplitude, frequency and phase of said measured radial bearing vibration velocity spectra;

comparing at least one of said components selected from the group of amplitude, frequency and phase of said original radial bearing acceleration spectra with at least one of said components selected from the group of amplitude, frequency and phase of said measured radial bearing acceleration spectra; and

determining if said radial bearing degradation exists.

21. The method according to claim 7, wherein,

said original data is further comprised of:

original radial bearing operating temperature, and

said condition monitoring variable are further comprised of;

measured radial bearing operating temperature; and

said method further comprising the step of;

comparing said original radial bearing operating temperature with said measured radial bearing operating temperature to determine if radial bearing degradation exists.

22. The method according to claim 7, wherein:

said original data is comprised of;

original thrust bearing vibration velocity spectra having amplitude, frequency and phase components, or

original thrust bearing acceleration spectra having amplitude, frequency and phase components, and

original thrust bearing operating temperature;

said equipment condition monitoring variables are comprised of;

measured thrust bearing vibration velocity spectra having amplitude, frequency and phase components, and

measured thrust bearing acceleration spectra having amplitude, frequency and phase components;

the method further comprising the steps of;

comparing at least one of said components selected from the group of amplitude, frequency and phase of said original thrust bearing vibration velocity spectra with at least one of said components selected from the group of amplitude, frequency and phase of said measured velocity vibration spectra;

comparing at least one of said components selected from the group of amplitude, frequency and phase of said original thrust bearing acceleration spectra with at least one of said components selected from the group of amplitude, frequency and phase of said measured acceleration spectra; and

determining if thrust bearing degradation exists.

23. The method according to claim 7, wherein:

said original data is further comprised of;

original thrust bearing operating temperature;

said equipment condition monitoring variables are comprised of;

measured thrust bearing operating temperature; and

said method further comprising the step of;

comparing said original thrust bearing operating temperature and said measured thrust bearing operating temperature to determine whether thrust bearing degradation exists.

24. The method according to claim 7, wherein:

said original data is comprised of original required net positive suction head;

said condition monitoring data is comprised of measured available net positive suction head;

the method further comprising the steps of;

comparing said original required net positive suction head with said measured available net positive suction head; and

determining if sufficient measured available net positive suction head exists to operate without cavitation.

25. The method according to claim 7, wherein:

said original data is comprised of original required net positive suction head; and

fluid vapor pressure of a process fluid at a temperature;

said condition monitoring data is comprised of;

measured net positive suction head,

measured operating temperature of a process fluid, and

the method further comprising the step of;

correcting said measured net positive suction head data for said measured operating temperature and said fluid vapor pressure,

comparing said corrected original required net positive suction head with said measured available net positive suction head; and

determining if sufficient measured available net positive suction head exists to operate without cavitation.

26. The method according to claim 7, wherein:

said original data is comprised of original axial thrust bearing displacement data;

said condition monitoring data is comprised of measured axial thrust bearing displacement data obtained from a proximity sensor positioned proximate a thrust bearing on the rotating equipment;

the method further comprising the steps of;

comparing said original axial thrust bearing displacement data with said measured axial thrust bearing displacement data; and

determining if thrust bearing degradation exists.

27. The method according to claim 7, wherein:

said original data is comprised of original radial bearing displacement data;

said condition monitoring data is comprised of measured radial bearing displacement data obtained from a displacement sensor positioned proximate a radial bearing on the rotating equipment;

the method further comprising the steps of;

comparing said original radial bearing displacement data with said measured radial bearing displacement data; and

determining if radial bearing degradation exists.

28. The method according to claim 7, wherein:

said original data is comprised of original motor manufacturer'"'"'s breakdown torque;

said equipment condition monitoring data is comprised of;

measured electric motor output torque;

said method further comprising the steps of;

comparing said original motor manufacturer'"'"'s breakdown torque with said original equipment condition monitoring data for diagnosing impending motor failure; and

generating an alert.

29. The method according to claim 7, further comprising:

constructing an original performance curve from said original data;

constructing secondary curves from said equipment condition monitoring variables; and

displaying said original performance curve and said secondary curves for comparison.

30. The method according to claim 7, further comprising:

constructing an original performance curve from said original data;

constructing a measured performance curve from said process variables and equipment condition monitoring variables;

said method further comprising the step of comparing said original performance curve and said measured performance curve and generating necessary alerts.

31. The method according to claim 30, wherein said host computer time stamps said original performance curve for comparison with said measured performance curve for use in predicting rotating equipment component failures.

32. The method according to claim 7, further comprising:

plotting said process operating data point from said process variables;

plotting a secondary data point from said equipment condition monitoring variables;

said method further comprising the step of communicating said original performance curve and said secondary performance curve for comparison and generating of necessary alerts.

33. The method according to claim 7, further comprising:

constructing an original performance curve from said original data;

constructing an original secondary curve from said original data;

variables;

constructing a measured performance curve from said equipment monitoring variables;

constructing a measured secondary curve from said equipment monitoring variables;

comparing said original performance curve with said measured performance curve;

comparing said original secondary curve with said measured secondary curve; and

alerting a controller to correct pump operating conditions to within said operating design regime.

34. The method according to claim 7, wherein;

said original data is comprised of;

original condition dynamic pressure sensor spectra having amplitude, frequency and phase components;

said equipment condition monitoring variables are comprised of;

measured condition dynamic pressure sensor spectra having amplitude, frequency and phase components;

said method further comprising the steps of;

comparing at least one of said components selected from the group of amplitude, frequency and phase of said measured dynamic pressure sensor spectra with at least one of said components selected from the group of amplitude, frequency and phase of said original condition dynamic pressure sensor spectra to determine if said rotating equipment is operating inside said design regime; and

determining from said comparison that cavitation exists.

35. The method according to claim 34, wherein:

said original data is comprised of original net positive suction head required;

said equipment condition monitoring variables are comprised of;

measured net positive suction head available;

operating fluid temperature; and

fluid vapor pressure;

said method further comprising the steps of;

correcting said original net positive suction head required and said measured net positive suction head available for said operating fluid temperature and said fluid vapor press;

verifying said determination of valve cavitation by determining that sufficient corrected measured net positive suction available exists and pump is not cavitating; and

determining that the source of cavitation is the valve.

36. The method according to claim 34, wherein:

said original data is comprised of original condition vibration spectra having amplitude, frequency and phase components;

said equipment condition monitoring variables are comprised of measured vibration spectra having amplitude, frequency and phase components;

said method further comprising the step of;

comparing at least one of said components selected from the group of amplitude, frequency and phase of said measured vibration spectra with at least one of said components selected from the group of amplitude, frequency and phase of said original condition vibration spectra; and

determining from said comparison that said measured vibration spectra has increased in an expected pump cavitation frequency range.

37. The method according to claim 7, wherein:

said original data is comprised of original condition vibration spectra having amplitude, frequency and phase components;

said equipment condition monitoring variables are comprised of measured vibration spectra having amplitude, frequency and phase components;

said method further comprising the steps of;

comparing at least one of said components selected from the group of amplitude, frequency and phase of said measured vibration spectra with at least one of said components selected from the group of amplitude, frequency and phase of said original condition vibration spectra to determine whether said measured vibration spectra amplitude has increased in the expected cavitation frequency range; and

diagnosing pump cavitation.

38. The method according to claim 7, wherein:

a control valve shaft position is determined from a control valve shaft position sensor;

said original data comprises original pump head;

said condition monitoring variables comprise measured head;

said method further comprising the steps of;

determining whether said valve is closed;

determining whether said measured head is greater than said original maximum head;

diagnosing a pump deadhead condition; and

sending a signal to shut down the rotating equipment or open said valve.

39. The method according to claim 7, wherein:

said original data comprises control valve flow data;

said equipment condition monitoring variables comprise measured pump flow; and

said process variables comprise control valve position;

said method further comprising the steps of;

calculating valve flow from said valve data at said control valve position; and

comparing said measured pump output flow with said calculated valve flow to determine valve packing leakage or valve seat leakage.

40. The method according to claim 7, wherein:

said original data comprises;

original head; and

original outlet pipe flow;

said measured process variables comprise measured outlet pipe flow and measured pump head;

said method further comprising the steps of;

operating the rotating equipment at said original head;

comparing said original head with said measured pump head; and

diagnosing a plugged output pipe if flow is less than said original pump output flow.

41. The method according to claim 7, wherein:

said original data is comprised of;

original flow rate; and

original net positive suction head available;

said process variable are comprised of;

measured net positive suction head;

said method further comprising the steps of;

comparing said original net positive suction head available with said measured net positive suction head available; and

diagnosing a plugged suction line if said original net positive suction head available is greater than said measured net positive suction head available.

42. The method according to claim 7, further comprising the step of adjusting said original data for varying motor speeds by using affinity laws.

43. The method according to claim 1, further comprising the steps of:

constructing an original performance curve from said original data;

constructing a measured performance curve from said process variables;

comparing said original performance curve with said measured performance curve; and

determining from said comparison of said original performance curve with said measured performance curve whether a condition of impending radial bearing failure exists.

44. The method according to claim 8, further comprising diagnosing a fouling or coating of an impeller in the rotating equipment if said measured performance curve is shifted downward compared with said original performance curve.

45. The method according to claim 1, wherein:

said original data is comprised of;

a calculated system demand curve at a flow rate, said calculated system demand curve determined by piping system geometry,

a calculated fluid frictional head loss at a flow rate, said calculated fluid frictional head loss determined by piping system geometry, and

a calculated velocity head at a flow rate, said calculated velocity head determined by piping system geometry;

said method further comprising the steps of;

construction a measured performance curve from said process variables;

calculating a system head operating point from said calculated system demand curve at a flow rate, said calculated fluid frictional head loss and said calculated velocity head; and

determining if the rotating equipment is operating in said recognizable recommended operating design regime by comparing said system head operating point with said measured performance curve.

46. The method according to claim 1, wherein:

said equipment condition monitoring variables are comprised of;

rotating machine input torque data, and

rotating machine shaft angular velocity data;

said method further comprising the steps of;

calculating measured rotating machine efficiency; and

diagnosing degraded rotating machine efficiency by comparing said measured rotating machine efficiency with said original machine efficiency.

48. The method according to claim 1, further comprising the step of adjusting a pump final control element to a desired setting.

49. The method according to claim 48, wherein said pump final control element is a valve.

50. The method according to claim 48, wherein said pump final control element is a variable speed drive.

47. A method for diagnosing rotating equipment comprising;

storing original data for constructing an original performance curve for the rotating equipment, said original data having a recognized recommended operating design regime;

acquiring a process variable from operating rotating equipment, said process variable selected from the group of fluid outlet pressure and fluid flow;

inputting said process variable into a computing device; and

determining if said process variable is within said recommended operating design regime.