INTEGRATED CONDITION BASED MAINTENANCE SYSTEM FOR WIND TURBINES

• US 20110020122A1
• Filed: 07/22/2010
• Published: 01/27/2011
• Est. Priority Date: 07/24/2009
• Status: Abandoned Application

• Current Assignee: Honeywell International Inc.
• Original Assignee: Honeywell International Inc.
• Inventors: Brotherton, Tom, Graber, Wendy Foslien, Parthasarathy, Girija
• Application Number:
  US12/841,301
• Publication Number:
  US 20110020122A1
• Time in Patent Office: Days
• US Class Current: 416/61
• CPC Class Codes: F03D 17/00 Monitoring or testing of wind motors, e.g. diagnostics testing during commissioning of wind motors F03D13/30
• CPC Class Codes: F03D 80/50 Maintenance or repair
• CPC Class Codes: F05B 2230/80 Repairing, retrofitting or upgrading methods
• CPC Class Codes: F05B 2240/96 as part of a wind turbine farm
• CPC Class Codes: F05B 2270/804 Optical devices
• CPC Class Codes: F05B 2270/808 Strain gauges; Load cells
• CPC Class Codes: F05B 2270/81 Microphones
• CPC Class Codes: Y02E 10/72 Wind turbines with rotation axis in wind direction
• CPC Class Codes: Y02P 70/50 Manufacturing or production processes characterised by the final manufactured product

Abstract

A computer implemented method includes receiving condition information from a plurality of condition detection sensors coupled to a wind turbine and receiving wind turbine controller information. An anomaly detection algorithm is applied to identify maintenance activities for the wind turbine as a function of both the wind turbine condition information and the wind turbine controller information.

Claims

1. A computer implemented method comprising:

receiving and storing on a computer readable device, wind turbine condition information from multiple sensors monitoring the wind turbine;

receiving and storing on a computer readable device, wind turbine controller information regarding performance of the wind turbine; and

applying an automated anomaly detection algorithm via the computer to identify maintenance activities for the wind turbine as a function of both the wind turbine condition information and the wind turbine controller information.

2. The computer implemented method of claim 1 and further comprising processing the received information via a computer to convert to at least one of a time domain and a frequency domain.

3. The computer implemented method of claim 1 wherein the condition information includes one or more of strain, acoustic emission, and optical or piezoelectric sensor information.

4. The computer implemented method of claim 1 and further comprising processing condition information to produce an image of a monitored structure.

5. The computer implemented method of claim 1 and further comprising automating the sensors to gather and transmit data at particular regimes of operation or at trigger conditions.

6. The computer implemented method of claim 1 and further comprising receiving further sensor information regarding the condition of at least one of generator, gearbox bearing, and lube oil temperature, yaw position and pitch position information, rotor, gearbox, and generator speed, generator terminal, currents, voltages, and power electrical signals.

7. The computer implemented method of claim 1 and further comprising receiving inner control loop data on demanded and measured pitch angle.

8. A computer implemented method comprising:

receiving condition information from a plurality of sensors coupled to a wind turbine;

receiving performance information proximate the wind turbine;

processing the received information to convert to at least one time domain and frequency domain; and

combining the received information at an integrated maintenance station and applying an automated anomaly detection algorithm to identify maintenance activities for the wind turbine.

9. The computer implemented method of claim 8 and further including processing the received information to convert at least some of the information to a synchronous order domain.

10. The computer implemented method of claim 8 and further comprising applying principal component analysis to the domain information to reduce the information to a subset of linear or non-linear combinations.

11. The computer implemented method of claim 10 and further comprising clustering observations as a function of similarity of the observations to each other.

12. The computer implemented method of claim 8 wherein the sensor information includes one or more of strain, acoustic emission, and optical or piezoelectric sensor information.

13. The computer implemented method of claim 8 and further comprising processing sensor information to produce an image of a monitored structure.

14. The computer implemented method of claim 8 and further comprising automating the sensors to gather and transmit data at particular regimes of operation or at trigger conditions.

15. The computer implemented method of claim 8 and further comprising receiving further sensor information and signals including at least one of generator, gearbox bearing, and lube oil temperature, yaw position and pitch position information, rotor, gearbox, and generator speed, generator terminal, currents, voltages, and power electrical signals.

16. A system comprising:

a wind generator having a blade coupled to a gearbox coupled to a generator;

a plurality of sensors arranged to sense multiple condition and controller parameters associated with the wind generator; and

a controller coupled to the wind generator to receive information from the plurality of sensors, to control operation of the wind generator, and to identify maintenance activities for the wind generator as a function of the information from the plurality of sensors when the information corresponds to a predicted failure of a portion of the wind generator.

17. The system of claim 16 and wherein the plurality of sensors provide information regarding the condition of at least one of generator, gearbox bearing, and lube oil temperature, yaw position and pitch position information, rotor, gearbox, and generator speed, generator terminal, currents, voltages, and power electrical signals.

18. The system of claim 16 wherein the controller performs principal component analysis to the sensed information to reduce the information to a subset of linear or non-linear combinations.

19. The system of claim 16 wherein the sensors provide structural health sensor information.

20. The system of claim 16 and further comprising a central controller coupled to receive information from multiple systems regarding multiple wind generators in a farm of wind generators.