Wind turbine and method for evaluating health state of blade thereof

Patent metadata

Field	Value
Publication number	US-10072635-B2
Application number	US-201414528101-A
Country	US
Kind code	B2
Filing date	Oct 30, 2014
Priority date	Oct 30, 2013
Publication date	Sep 11, 2018
Grant date	Sep 11, 2018

Abstract

A wind turbine including a plurality of blades, a micro inertial measurement unit installed on each blade and configured to sense a plurality of detection parameter signals at corresponding installation positions, and a monitoring system configured to monitor an operating state of the blades. The monitoring system includes a signal processing unit configured to obtain a processing parameter signal through calculation based on the detection parameter signals, a signal analyzing unit configured to analyze each analysis parameter signal, selected from the plurality of detection parameter signals and the processing parameter signal, to obtain a fault estimation signal, used to estimate whether a corresponding blade works in a fault state, and a fault evaluating unit configured to evaluate, based on a plurality of fault estimation signals, whether a corresponding blade fails or a probability that the corresponding blade fails.

First claim

What is claimed is:

1. A wind turbine comprising:
a plurality of blades;
a micro inertial measurement unit mounted on each of the plurality of blades, and configured to sense a plurality of detection parameter signals at corresponding blade; and
a monitoring system, configured to monitor an operating state of the plurality of blades, and the monitoring system comprises:
a signal processing unit, configured to obtain a plurality of processed parameter signals by processing the plurality of detection parameter signals obtained by the micro inertial measurement unit, wherein the plurality of processed parameter signals comprises at least one from a blade pitch, a blade rotating speed, a blade deflection, a local blade angle, a blade torque, a blade tip offset, and a three-dimensional motion trail;
a signal analyzing unit, configured to analyze each of a plurality of analysis parameter signals to obtain a plurality of fault estimation signals, wherein the plurality of analysis parameter signals are selected from the plurality of detection parameter signals and the plurality of processed parameter signals, and each of the plurality of fault estimation signals is used to estimate whether a corresponding blade works in a fault state, wherein the signal analyzing unit comprises a comparer configured to compare the plurality of analysis parameter signals with a preset parameter signal to generate the plurality of fault estimation signals; and
a fault evaluating unit, configured to evaluate, based on a plurality of fault estimation signals, whether a corresponding blade fails or a probability that the corresponding blade fails,
wherein when a corresponding blade fails or a probability that the corresponding blade fails is greater than a threshold, the corresponding blade is adapted to be maintained or replaced.

2. The wind turbine according to claim 1 , wherein the plurality of processed parameter signals comprises a local blade angle.

3. The wind turbine according to claim 2 , wherein the comparer is further configured to compare and to analyze amplitude-frequency characteristics of one of the analysis parameter signals and the preset parameter signal, and, when a deviation between an amplitude-frequency characteristic of the one of the plurality of analysis parameter signals and an amplitude-frequency characteristic of the preset parameter signal is greater than a set threshold, to estimate that a corresponding blade works in a fault state.

4. The wind turbine according to claim 3 , wherein the preset parameter signal comes from simulation data, which is based on a blade model and corresponds to the one of the plurality of analysis parameter signals, and test data or historical data, which is based on blade operation and corresponds to the one of the plurality of analysis parameter signals.

5. The wind turbine according to claim 1 , wherein the signal analyzing unit comprises a comparer, and the comparer is configured to compare same analysis parameter signals corresponding to the plurality of blades, and when, a deviation between an analysis parameter signal of one blade and an analysis parameter signal of any other blade is greater than a set threshold and all deviations between analysis parameter signals of other blades are less than the set threshold, to estimate that the blade works in a fault state.

6. The wind turbine according to claim 5 , wherein the comparer is configured to compare statistical characteristics of the same analysis parameter signals corresponding to the plurality of blades.

7. The wind turbine according to claim 1 , wherein the fault evaluating unit evaluates, by using a weighting algorithm based on the plurality of fault estimation signals, the probability that the corresponding blade fails.

8. The wind turbine according to claim 7 , wherein the monitoring system further comprises a life cycle predictor, and the life cycle predictor is configured to analyze the fault probability signal to predict a life cycle of a corresponding blade.

9. A method for operating a wind turbine, the method comprising:
sensing a plurality of detection parameter signals by a micro inertial measurement unit mounted on each of the plurality of blades;
obtaining a plurality of processed parameter signals by processing the plurality of detection parameter signals, wherein the plurality of processed parameter signals comprises at least one from a blade pitch, a blade rotating speed, a blade deflection, a local blade angle, a blade torque, a blade tip offset, and a three-dimensional motion trail;
analyzing each of a plurality of analysis parameter signals to obtain a plurality of fault estimation signals, wherein the plurality of analysis parameter signals are selected from the plurality of detection parameter signals and the plurality of processing parameter signals, and each of the plurality of fault estimation signals is used to estimate whether a corresponding blade works in a fault state; and
evaluating, based on a plurality of fault estimation signals, whether a corresponding blade fails or a probability that the corresponding blade fails; and;
when a corresponding blade fails or a probability that the corresponding blade fails is greater than a threshold, maintaining or replacing the corresponding blade,
wherein the step of obtaining the fault estimation signal comprises:
comparing the plurality of analysis parameter signals with a preset parameter signal; and
when a deviation between one of the plurality of analysis parameter signals and the preset parameter signal is greater than a set threshold, estimating that the corresponding blade works in a fault state.

10. The method according to claim 9 , wherein the plurality of processed parameter signals comprises a local blade angle.

11. The method according to claim 10 , wherein the comparing step comprises comparing and analyzing amplitude-frequency characteristics of the plurality of analysis parameter signals and the preset parameter signal.

12. The method according to claim 9 , wherein the comparing step comprises:
comparing and analyzing same analysis parameter signals corresponding to the plurality of blades; and
when a deviation between an analysis parameter signal of one blade and an analysis parameter signal of any other blade is greater than a set threshold and all deviations between analysis parameter signals of other blades are less than the set threshold, estimating that the blade works in a fault state.

13. The method according to claim 12 , wherein the comparing and analyzing step comprises comparing and analyzing statistical characteristics of the same analysis parameter signals corresponding to the plurality of blades.

14. The method according to claim 9 , wherein the step of evaluating the probability that the corresponding blade fails comprises evaluating, by using a weighting algorithm based on the plurality of fault estimation signals, the probability that the corresponding blade fails.

Assignees

• Gen Electric

Inventors

• Fu Xu
• Wu Zhilin
• Qiu Hai

Classifications

• F05B2270/807

  Accelerometers · CPC title

• F03D17/00 Primary

  Monitoring or testing of wind motors, e.g. diagnostics (testing during commissioning of wind motors F03D13/30) · CPC title

• F05B2270/80

  Devices generating input signals, e.g. transducers, sensors, cameras or strain gauges · CPC title

• G01L3/02

  Rotary-transmission dynamometers · CPC title

• F03D11/0091 Primary

  Mechanical Engineering · mapped topic