US 12,429,030 B2
Turbine monitoring and maintenance
Christopher Fraser, London (GB); Thomas Humphries, London (GB); and Ty Burridge-Oakland, London (GB)
Appl. No. 17/776,701
Filed by COGNITIVE.BUSINESS LTD, London (GB)
PCT Filed Nov. 11, 2020, PCT No. PCT/GB2020/052863
§ 371(c)(1), (2) Date May 13, 2022,
PCT Pub. No. WO2021/094743, PCT Pub. Date May 20, 2021.
Claims priority of application No. 1916603 (GB), filed on Nov. 14, 2019.
Prior Publication US 2022/0397097 A1, Dec. 15, 2022
Int. Cl. F03D 17/00 (2016.01)
CPC F03D 17/00 (2016.05) [F05B 2260/80 (2013.01); F05B 2270/32 (2013.01); F05B 2270/321 (2013.01); F05B 2270/335 (2013.01); F05B 2270/404 (2013.01); F05B 2270/709 (2013.01)] 17 Claims
OG exemplary drawing
 
1. A method for turbine fault or component degradation detection comprising:
measuring the power output from a plurality of renewable energy turbines in an array,
performing a comparison of the measured power output from a target turbine with a predicted value for the target turbine, wherein the predicted value is the result of a calculation based on the measured power output from a plurality of other turbines from the array and a predictive model which includes a weighting assigned to each of the plurality of other turbines based on the strength of correlation of their historical data with historical data from the target turbine,
determining a performance change for the target turbine based on the comparison;
outputting an alert signal indicative of a fault or component degradation if a performance change is determined; and
causing repair, maintenance or inspection of the target turbine to be performed based on the alert signal;
wherein a separate predictive model is provided for each of a plurality of defined wind directions, and wherein the method selects the predictive model that corresponds to the wind direction experienced by the target turbine.