Process device diagnostics using process variable sensor signal

• US 7,010,459 B2
• Filed: 06/05/2003
• Issued: 03/07/2006
• Est. Priority Date: 06/25/1999
• Status: Expired due to Term

• Current Assignee: Rosemount Incorporated (Emerson Electric Company)
• Original Assignee: Rosemount Incorporated (Emerson Electric Company)
• Inventors: Eryurek, Evren, Kavaklioglu, Kadir, Esboldt, Steven R.
• Primary Examiner(s): Hoff, Marc S.
• Assistant Examiner(s): Charioui, Mohamed
• Application Number:
  US10/455,815
• Publication Number:
  US 20040024568A1
• Time in Patent Office: 1,006 Days
• Field of Search: 702/45, 702/55, 702/69, 702/104, 702/105, 702/183, 702/191, 702/195, 702/182, 73/16.9, 738/613.54, 738/613.55, 738/613.56, 738/613.57, 738/612.2, 340/606
• US Class Current: 702/182
• CPC Class Codes: G01F 1/3209 using Karman vortices
• CPC Class Codes: G01F 1/60 Circuits therefor
• CPC Class Codes: G01F 1/8477 with multiple measuring conduits
• CPC Class Codes: G01F 25/10 of flowmeters
• CPC Class Codes: G01K 15/00 Testing or calibrating of thermometers
• CPC Class Codes: G05B 23/0221 Preprocessing measurements, e.g. data collection rate adjustment; Standardization of measurements; Time series or signal analysis, e.g. frequency analysis or wavelets; Trustworthiness of measurements; Indexes therefor; Measurements using easily measured parameters to estimate parameters difficult to measure; Virtual sensor creation; De-noising; Sensor fusion; Unconventional preprocessing inherently present in specific fault detection methods like PCA-based methods
• CPC Class Codes: G05B 23/024 Quantitative history assessment, e.g. mathematical relationships between available data; Functions therefor; Principal component analysis [PCA]; Partial least square [PLS]; Statistical classifiers, e.g. Bayesian networks, linear regression or correlation analysis; Neural networks
• CPC Class Codes: G05B 9/03 with multiple-channel loop, i.e. redundant control systems
• CPC Class Codes: G07C 3/00 Registering or indicating the condition or the working of machines or other apparatus, other than vehicles
• CPC Class Codes: G08C 19/02 in which the signal transmitted is magnitude of current or voltage G08C19/36, G08C19/38 take precedence

Abstract

A diagnostic device for use in a process control system receives a sensor signal related to a process variable of a process sensed by a process variable sensor. A signal preprocessor provides a sensor power signal output as a function of a frequency distribution of power in the sensor signal. A process condition is determined based upon the sensor power signal.

Claims

1. A diagnostic device for use in a process control system which includes a process device used to control the process, comprising:

a sensor signal input, the sensor signal related to a process variable of a process fluid of a process, the process variable sensed by a process variable sensor;

a signal preprocessor coupled to the sensor input having a sensor power signal output as a function of a frequency distribution of power in the sensor signal; and

a signal evaluator coupled to the sensor power signal output having a process device condition output related to an operation condition of the process device of the process control system.

2. The diagnostic device of claim 1 wherein the diagnostic device couples to a communication bus.

3. The diagnostic device of claim 2 wherein the communication bus comprises a two-wire loop.

4. The diagnostic device of claim 3 wherein the diagnostic device is fully powered with power received from the two-wire loop.

5. The diagnostic device of claim 1 wherein the sensor signal has a frequency content of at least 50 Hz.

6. The diagnostic device of claim 1, wherein the diagnostic device is included in a transmitter.

7. The diagnostic device of claim 1 wherein the process variable sensor comprises a pressure sensor.

8. The diagnostic device of claim 1 wherein the process variable sensor comprises electrodes in a magnetic flowmeter.

9. The diagnostic device of claim 1 wherein the process variable sensor comprises a sensor in a vortex flowmeter.

10. The diagnostic device of claim 1 wherein the process variable sensor comprises a sensor in a coriolis flowmeter.

11. The diagnostic device of claim 1 wherein the signal preprocessor isolates a frequency range of the sensor signal.

12. The diagnostic device of claim 1 wherein the sensor signal has a frequency of between 0 Hz and 200 Hz.

13. The diagnostic device of claim 1 wherein the function comprises power spectral density.

14. The diagnostic device of claim 1 wherein the function is related to a Fourier transform of the sensor signal.

15. The diagnostic device of claim 1 wherein the function comprises a wavelet transform of the sensor signal.

16. The diagnostic device of claim 1 wherein the signal preprocessor includes a filter.

17. The diagnostic device of claim 1 wherein the diagnostic device is implemented in a process monitor.

18. The diagnostic device of claim 1 wherein the diagnostic device is implemented in a control system.

19. The diagnostic device of claim 1 wherein the sensor power signal output relates to a vibration noise signal carried in process fluid of the process.

20. The diagnostic device of claim 1 wherein the process variable sensor comprises a sensor in an ultrasonic flowmeter.

21. The diagnostic device of claim 1 wherein the condition of the process device condition is related to condition of a process device selected from the group of devices consisting of valves, pumps, pump seals, discharge systems, actuators, solenoids, compressors, turbines, agitators, dampers, piping, fixtures and tanks.

22. The diagnostic device of claim 1 wherein the signal evaluator compares the sensor power signal with a stored value.

23. The diagnostic device of claim 1 wherein the signal evaluator comprises a neural network.

24. The diagnostic device of claim 1 signal evaluator comprises fuzzy logic.

25. A diagnostic method performed in a process control environment which includes a process device used to control the process, the method comprising:

obtaining a process variable sensor signal;

determining a frequency distribution of power in the process variable sensor signal; and

evaluating the frequency distribution of power in the process variable sensor signal and providing a process device condition output related to an operation condition of the process device of the process control system.

26. The method of claim 25 wherein determining includes performing a Fourier transformation on the process variable sensor signal.

27. The method of claim 26 wherein determining includes performing a wavelet transformation.

28. The method of claim 27 wherein performing a wavelet transform comprises performing a discrete wavelet transform.

29. The method of claim 25 wherein determining includes filtering the process variable sensor signal.

30. The method of claim 25 wherein evaluating comprises comparing frequency distribution of power in the process variable sensor signal to a stored value.

31. The method of claim 25 wherein evaluating comprises evaluating the frequency distribution of power in the process variable sensor signal to a neural network.

32. The method of claim 25 wherein evaluating comprises applying a rule to the frequency distribution of power in the process variable sensor signal.

33. The method of claim 25 wherein the process variable sensor signal comprises a pressure sensor signal.

34. The method of claim 25 wherein the process variable sensor signal comprises a sensor output from a coriolis flowmeter.

35. The method of claim 25 wherein the process variable sensor signal comprises a sensor output from a vortex flowmeter.

36. The method of claim 25 wherein the process variable sensor signal comprises electrode outputs from a magnetic flowmeter.

37. The method of claim 25 wherein the process variable sensor signal has a bandwidth of at least 50 Hz.

38. The method of claim 25 including fully powering the diagnostic device with power from a two-wire loop.

39. The method of claim 25 wherein the frequency distribution of power in the process variable sensor signal comprises power spectral density.

40. A computer-readable medium having stored thereon instructions executable by a microprocessor system in a diagnostic device to diagnose condition of a process which includes a process device used to control the process, the instructions comprising:

obtaining a process variable sensor signal;

determining a frequency distribution of power in the process variable sensor signal; and

evaluating the frequency distribution of power in the process variable sensor signal and providing a process device condition output related to an operation condition of the process device of the process control system.

41. A diagnostic device for use in a process control system which includes a process device used to control the process, comprising:

a sensor signal input, the sensor signal related to a process variable of a process fluid of a process, the process variable sensed by a process variable sensor;

signal preprocessing means for determining a frequency distribution of power in the sensor signal; and

signal evaluating means for diagnosing a process device operation condition of the process device of the process control system based upon the frequency distribution of power in the sensor signal.