US 11,808,248 B2Granted

Method and system for performing condition monitoring of wind turbine components

AssigneeFischer Block, Inc.

InventorsMargaret Paietta, Gregory Wolfe

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Abstract

A technique for performing condition monitoring of a plurality of components of a plurality of wind turbines is disclosed. The technique includes, for each of the plurality of wind turbines, measuring at least one time-series electrical output signal of the wind turbine generator, each time-series electrical output signal representing an aggregate of a plurality of subset signals. Such condition monitoring further includes mathematically extracting one or more such subset signals from the at least one time-series electrical output signal of the generator, and associating one or more such subset signals with one or more wind turbine components. A fault threshold value for each such one or more subset signals may be determined, and the one or more such subset signals are compared to such fault threshold value. Based on such association and comparison, the condition of such a wind turbine component of the plurality of wind turbines is determined.

Claims82

Dependent claims

A method for performing condition monitoring of a plurality of components of a plurality of wind turbines, the method comprising:

for each of the plurality of wind turbines, measuring at least one time-series electrical output signal of a generator of the wind turbine, each time-series electrical output signal representing an aggregate of a plurality of subset signals;
mathematically extracting one or more such subset signals from the at least one time-series electrical output signal of the generator;
associating one or more such subset signals with one or more wind turbine components;
determining a fault threshold value for each such one or more subset signals;
comparing the one or more such subset signals to such fault threshold value;
and
determining the condition of such at least one wind turbine component of the plurality of wind turbines based on such association and comparison;
wherein comparing the subset signal to its fault threshold level includes calculating a health condition index, wherein calculating the health condition index includes comparing a number of standard deviations in which a value of the subset signal falls from a historical mean and a predetermined number of acceptable standard deviations from the historical mean, and wherein determining the condition of one or more wind turbine component includes outputting an alert when one or more such conditions exceeds a threshold value.

5 more elements

A condition monitoring system for a wind turbine, the condition monitoring system operationally coupled to a plurality of wind turbines in a wind farm, the condition monitoring system is configured to:

for each wind turbine of the plurality of wind turbines, measure at least one time-series electrical output signal of a generator of the wind turbine, each time-series electrical output signal representing an aggregate of a plurality of subset signals;
mathematically extract one or more such subset signals from the at least one time-series electrical output signal of the generator;
associate one or more such subset signals with one or more wind turbine components;
determine a fault threshold value for each such one or more subset signals;
compare the one or more such subset signals to such fault threshold value;
and
determine the condition of such at least one wind turbine component of the plurality of wind turbines based on such association and comparison, wherein comparing the subset signal to its fault threshold level includes calculating a health condition index, wherein calculating the health condition index includes comparing a number of standard deviations in which a value of the subset signal falls from the historical mean and a predetermined number of acceptable standard deviations from the historical mean, and wherein determining the condition of one or more wind turbine component includes outputting an alert when one or more such conditions exceeds a threshold value.

4 more elements

Dependencies are inferred from the claim text.

Facts

Application: 17/437,516Filed 18 Feb 2021 · us provisional application
Priority: 18 Feb 2020
Published: US 2022/0389912 A18 Dec 2022
Granted: 7 Nov 2023
Term ends: Not estimatedThe source records don’t support an estimate.

Classification13 codes

F03D 7/028
The wind motors having rotation axis substantially parallel to the air flow entering the rotor: controlling wind motor output power
F03D 17/00
Monitoring or testing of wind motors
F03D 7/048
By means of an electrical or electronic controller: controlling wind farms
F03D 17/005
Monitoring or testing of wind motors, e.g. diagnostics: using computation methods, e.g. neural networks