CONDITION-BASED MAINTENANCE SYSTEM FOR WIND TURBINES

1 . A condition-based maintenance system comprising:

an instrument set for connection to one or more wind turbines; and

a performance monitor connected to the instrument set; and

wherein:

the performance monitor is for recording and indicating conditions of the one or more wind turbines; and

the conditions are a basis for determining whether maintenance is recommended for the one or more wind turbines.

2 . The system of claim 1 , further comprising a wind turbine anomaly detector connected to the instrument set and the performance monitor.

3 . The system of claim 2 , further comprising a multiple wind turbine anomaly detector connected to the performance monitor and the wind turbine anomaly detector.

4 . The system of claim 2 , wherein an anomaly detector comprises principal component analysis.

5 . The system of claim 2 , wherein an anomaly detector comprises a self organizing feature map.

6 . The system of claim 3 , further comprising an associative model connected to the performance monitor.

7 . The system of claim 6 , wherein the associative model comprises:

an input for actual wind turbine performance parameters from the instrument set;

a mapping layer connected to the input;

a bottleneck layer connected to the mapping layer;

a demapping layer connected to the bottleneck layer; and

an output, connected to the demapping layer, for providing expected wind turbine performance parameters.

8 . The system of claim 3 , wherein the instrument set, the wind turbine anomaly detector, the multiple wind turbine anomaly detector and the performance monitor indicate conditions about the one or more wind turbines.

9 . The system of claim 8 , wherein the instrument set comprises sensors as needed to take measurements at the one or more wind turbines.

10 . The system of claim 8 , wherein the conditions are classified as normal, anomalous, excessive, deficient, or unclassified, relative to expected conditions.

11 . The system of claim 8 , wherein the conditions are classified into particular component faults in a specific wind turbine of the one or more wind turbines.

12 . The system of claim 10 , wherein the conditions as classified result in condition-based maintenance recommendations by a system process of the conditions.

13 . The system of claim 12 , wherein the system process comprises:

a principal components analysis;

a self organizing feature map approach;

a neural network approach;

a spectral analysis;

an envelope analysis;

pattern matching;

predictive trending;

future projection;

fault diagnosis;

fault prognosis;

a sequential ratio test;

fuzzy logic;

least squares estimation;

partial least squares regression;

data cluster plots; and/or

statistical analysis.

14 . A condition-based wind turbine maintenance system comprising:

a first sensor set for connection to a first wind turbine;

a first anomaly detector for connection to the first wind turbine; and

a performance monitor connected to the first sensor set and the first anomaly detector; and

wherein:

the performance monitor is for indicating conditions of the first wind turbine; and

the conditions are a basis for indicating whether maintenance to be recommended for the first wind turbine.

15 . The system of claim 14 , wherein the conditions are classified into a category relative to expected conditions for the first wind turbine.

16 . The system of claim 15 , wherein the conditions as classified result in condition-based maintenance recommendations for the first wind turbine.

17 . The system of claim 15 , further comprising:

a second sensor set for connection to two or more wind turbines;

a second anomaly detector for connection to the two or more wind turbines; and

a second performance monitor connected to the second sensor set and the second anomaly detector.

18 . The system of claim 17 , wherein the second sensor set, the second performance monitor and the second anomaly detector provide wind turbine population-based parameter sensing and anomaly detection as criteria for classifying conditions of the first wind turbine into a category relative to conditions common to the two or more wind turbines.

19 . The system of claim 18 , wherein the conditions of the first wind turbine classified into a category relative to expected conditions and the conditions of the first turbine classified into a category relative to conditions common to the two or more wind turbines, are combined to result in conditions for providing condition-based maintenance recommendations for the first wind turbine.

20 . A method for providing condition-based maintenance, comprising:

collecting data about one or more wind turbines;

analyzing the data to obtain performance information about the one or more wind turbines;

detecting anomalies, if any, of the one or more wind turbines; and

developing conditions from the performance information and any anomalies of the one or more wind turbines; and

wherein the conditions are a basis for determining whether maintenance is recommended for the one or more wind turbines.

21 . The method of claim 20 , wherein the data about the one or more turbines comprises measurements as needed at the one or more wind turbines.

22 . The method of claim 21 , wherein the conditions are classified as normal, anomalous, excessive, deficient, or unclassified, relative to expected conditions of the one or more wind turbines, or their components.

23 . The method of claim 22 , wherein:

the conditions as classified result in condition-based maintenance recommendations by system processing the conditions; and

system processing comprises:

principal components analysis;

self organizing feature mapping;

neural networking;

spectral analysis;

envelope analysis;

pattern matching;

predictive trending;

future projection;

fault diagnosis;

fault prognosis;

sequential ratio testing;

fuzzy logic;

least squares estimation;

partial least squares regression;

data cluster plotting; and/or

statistical analysis.