Monitoring and data processing equipment for wind turbines and predictive maintenance system for wind power stations

• US 7,677,869 B2
• Filed: 11/12/2004
• Issued: 03/16/2010
• Est. Priority Date: 11/14/2003
• Status: Active Grant

• Current Assignee: Siemens Gamesa Renewable Energy Innovation & Technology SL (Siemens AG)
• Original Assignee: Gamesa Innovation and Technology SL (Siemens AG)
• Inventors: Llorente Gonzalez, Jose Ignacio, Martinez De Lizarduy Romo, Maria Jose
• Primary Examiner(s): Verdier; Christopher
• Application Number:
  US10/578,825
• Publication Number:
  US 20070140847A1
• Time in Patent Office: 1,950 Days
• Field of Search: 416/1, 416/31, 416 36- 38, 416/44, 416/61, 290/44, 290/55
• US Class Current: 416/37
• 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 2270/20 to optimise the performance of a machine
• CPC Class Codes: F05B 2270/404 active, predictive, or anticipative
• CPC Class Codes: F05B 2270/807 Accelerometers
• CPC Class Codes: G01H 1/006 of the rotor of turbo 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
• CPC Class Codes: G05B 23/0283 Predictive maintenance, e.g. involving the monitoring of a system and, based on the monitoring results, taking decisions on the maintenance schedule of the monitored system; Estimating remaining useful life [RUL] preventive maintenance, i.e. planning maintenance according to the available resources without monitoring the system G06Q10/06
• 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 predictive maintenance system for wind parks, the wind park comprising a group of wind turbines (Ai), a communications network (RS), and a supervision and control system (ST). The predictive maintenance system comprises a monitoring and processing equipment (SMP) connected to the control system (PLC) of the wind turbine (Ai), such that the monitoring and processing equipment sends alarms through the control system of the wind turbine to the supervision and control system. A monitoring and processing equipment (SMP) for wind turbines is also disclosed.

Claims

1. A monitoring and processing equipment (SMP) for a wind turbine (Ai), the wind turbine including a control system (PLC), said equipment comprising:

connection means with said control system (PLC) of the wind turbine, and

connection means with a group of accelerometers (Si) placed in pre-established components (Ei, Mi and Gi) of the wind turbine,

said monitoring and processing equipment being configured to begin a capture of the signals of the group of accelerometers as long as predetermined operation variables of the wind turbine, received from the control system, are within a predetermined operation range, and

said monitoring and processing equipment being configured to complete said signal capture as long as the value of said operation variables does not vary, during the entire signal capture, beyond upper and lower limits configured in the equipment,

and said monitoring and processing equipment comprising;

processing means for processing the captured signals of the accelerometers to obtain a set of overall variables associated to the captured signals, and

means for generating alarms related to failures or malfunctionings of mechanical components of the wind turbine.

2. A monitoring and processing equipment according to claim 1, wherein said predetermined operation variables of the wind turbine (Ai) are the instantaneous power produced by the wind turbine, revolutions per minute of a generator (Gi), and rotation of a ring of the nacelle of the wind turbine.

3. A monitoring and processing equipment according to claim 1, wherein said predetermined ranges of the predetermined operation variables of the wind turbine are defined according to the rated features of the wind turbine (Ai).

4. A monitoring and processing equipment according to claim 1, wherein said upper and lower limits, for each operation variable, are determined by a percentage of the initial value of each variable.

5. A monitoring and processing equipment according to claim 1, wherein capturing the signal of the accelerometers consists of taking three consecutive samples:

one for high-frequency processing (HF), one for low-frequency processing (BF), and one for digital filtering processing (FD).

6. A monitoring and processing equipment according to claim 1, wherein said processing means comprise:

means for conditioning the signal,

means for calculating a set of overall values,

means for carrying out a level alarm detection algorithm; and

means for carrying out a tendency alarm detection algorithm.

7. A monitoring and processing equipment according to claim 5, wherein said equipment can be configured with parameters obtained from means of alarm detection algorithms and the means of maximum frequencies and frequency bands.

8. A monitoring and processing equipment according to claim 1, further comprising storage means for storing the information introduced in or generated by the monitoring and processing equipment itself.

9. A monitoring and processing equipment according to claim 8, wherein said information stored in the storage means includes spectra, overall values, alarms, operation variables of the wind turbine, complete configuration of the equipment and overall variable and alarm recordings.

10. A monitoring and processing equipment according to claim 1, wherein said pre-established components of the wind turbine are a main shaft (Ei), step-up gear (Mi) and generator (Gi).

11. A predictive maintenance system for a wind park, the wind park comprising a group of wind turbines (Ai), a communications network (RS) and a supervision and control system (ST), wherein the predictive maintenance system comprises:

a monitoring and processing equipment (SMPi) of the type claimed in claim 1, being connected to a control system (PLCi) of a wind turbine (Ai) such that the monitoring and processing equipment (SMPi) is configured to send alarms through the control system (PLCi) of a wind turbine to the supervision and control system (ST).

12. A predictive maintenance system according to claim 11, further comprising means for the spectral and vibration analysis (SP) of the information extracted from the monitoring and processing equipment (SMPi).