Anomaly detection in wind turbines involves emphasizing its ability to improve operational efficiency,reduce maintenance costs,extend their lifespan,and enhance reliability in the wind energy sector.This is particular...Anomaly detection in wind turbines involves emphasizing its ability to improve operational efficiency,reduce maintenance costs,extend their lifespan,and enhance reliability in the wind energy sector.This is particularly necessary in offshore wind,currently one of the most critical assets for achieving sustainable energy generation goals,due to the harsh marine environment and the difficulty of maintenance tasks.To address this problem,this work proposes a data-driven methodology for detecting power generation anomalies in offshore wind turbines,using normalized and linearized operational data.The proposed framework transforms heterogeneous wind speed and power measurements into a unified scale,enabling the development of a new wind power index(WPi)that quantifies deviations from expected performance.Additionally,spatial and temporal coherence analyses of turbines within a wind farm ensure the validity of these normalized measurements across different wind turbine models and operating conditions.Furthermore,a Support Vector Machine(SVM)refines the classification process,effectively distinguishing measurement errors from actual power generation failures.Validation of this strategy using real-world data from the Alpha Ventus wind farm demonstrates that the proposed approach not only improves predictive maintenance but also optimizes energy production,highlighting its potential for broad application in offshore wind installations.展开更多
AIM：To determine the effects of peripheral corneal thickness（PCT）on dynamic contour tonometry（DCT）and Goldmann applanation tonometry（GAT）.METHODS：A cross-sectional study.We created a software which calculates ...AIM：To determine the effects of peripheral corneal thickness（PCT）on dynamic contour tonometry（DCT）and Goldmann applanation tonometry（GAT）.METHODS：A cross-sectional study.We created a software which calculates the corneal contour（CC）as a function of the radius from the corneal apex to each pixel of the contour.The software generates a central circumference with a radius of 1 mm and the remainder of the cornea is segmented in 5 rings concentric with corneal apex being its diameter not constant around the corneal circumference as a consequence of the irregular CC but keeping constant the diameter of each ring in each direction of the contour.PCT was determined as the mean thickness of the most eccentric ring.Locally weighted scatterplot smoothing（LOWESS）regression was used to determine the pattern of the relationship between PCT and both DCT and GAT respectively.Thereafter,two multivariable linear regression models were constructed.In each of them,the dependant variable was intraocular pressure（IOP）as determined using GAT and DCT respectively.In both of the models the predictive variable was PCT though LOWESS regression pattern was used to model the relationship between the dependant variables and the predictor one.Age and sex were also introduced control variables along with their first-degree interactions with PCT.Main outcome measures include amount of IOP variation explained through regression models（R2）and regression coefficients（B）.RESULTS：Subjects included 109 eyes of 109 healthy individuals.LOWESS regression suggested that a 2nd-degree polynomial would be suitable to model the relationshipbetween both DCT and GAT with PCT.Hence PCT was introduced in both models as a linear and quadratic term.Neither age nor sex nor interactions were statistically significant in both models.For GAT model,R2was 17.14%（F=9.02;P=0.0002）,PCT linear term B was-1.163（95%CI：-1.163,-0.617）.PCT quadratic term B was 0.00081（95%CI：0.00043,0.00118）.For DCT model R2was 14.28%（F=9.29;P=0.0002）,PCT linear term B was-0.712（95%CI：-1.052,-0.372）,PCT quadratic term was B=0.0005（95%CI：0.0003,0.0007）.CONCLUSION：DCT and GAT measurements are conditioned by PCT though this effect,rather than linear,follows a2nd-degree polynomial pattern.展开更多
基金supported by the Spanish Ministry of Science and Innovation under the MCI/AEI/FEDER project number PID2021-123543OBC21.
文摘Anomaly detection in wind turbines involves emphasizing its ability to improve operational efficiency,reduce maintenance costs,extend their lifespan,and enhance reliability in the wind energy sector.This is particularly necessary in offshore wind,currently one of the most critical assets for achieving sustainable energy generation goals,due to the harsh marine environment and the difficulty of maintenance tasks.To address this problem,this work proposes a data-driven methodology for detecting power generation anomalies in offshore wind turbines,using normalized and linearized operational data.The proposed framework transforms heterogeneous wind speed and power measurements into a unified scale,enabling the development of a new wind power index(WPi)that quantifies deviations from expected performance.Additionally,spatial and temporal coherence analyses of turbines within a wind farm ensure the validity of these normalized measurements across different wind turbine models and operating conditions.Furthermore,a Support Vector Machine(SVM)refines the classification process,effectively distinguishing measurement errors from actual power generation failures.Validation of this strategy using real-world data from the Alpha Ventus wind farm demonstrates that the proposed approach not only improves predictive maintenance but also optimizes energy production,highlighting its potential for broad application in offshore wind installations.
基金Supported in part by Carlos Ⅲ Health Institute,"Research Cooperative Network.Project RD07/0062:Ocular ageing pathology,visual quality of life"
文摘AIM：To determine the effects of peripheral corneal thickness（PCT）on dynamic contour tonometry（DCT）and Goldmann applanation tonometry（GAT）.METHODS：A cross-sectional study.We created a software which calculates the corneal contour（CC）as a function of the radius from the corneal apex to each pixel of the contour.The software generates a central circumference with a radius of 1 mm and the remainder of the cornea is segmented in 5 rings concentric with corneal apex being its diameter not constant around the corneal circumference as a consequence of the irregular CC but keeping constant the diameter of each ring in each direction of the contour.PCT was determined as the mean thickness of the most eccentric ring.Locally weighted scatterplot smoothing（LOWESS）regression was used to determine the pattern of the relationship between PCT and both DCT and GAT respectively.Thereafter,two multivariable linear regression models were constructed.In each of them,the dependant variable was intraocular pressure（IOP）as determined using GAT and DCT respectively.In both of the models the predictive variable was PCT though LOWESS regression pattern was used to model the relationship between the dependant variables and the predictor one.Age and sex were also introduced control variables along with their first-degree interactions with PCT.Main outcome measures include amount of IOP variation explained through regression models（R2）and regression coefficients（B）.RESULTS：Subjects included 109 eyes of 109 healthy individuals.LOWESS regression suggested that a 2nd-degree polynomial would be suitable to model the relationshipbetween both DCT and GAT with PCT.Hence PCT was introduced in both models as a linear and quadratic term.Neither age nor sex nor interactions were statistically significant in both models.For GAT model,R2was 17.14%（F=9.02;P=0.0002）,PCT linear term B was-1.163（95%CI：-1.163,-0.617）.PCT quadratic term B was 0.00081（95%CI：0.00043,0.00118）.For DCT model R2was 14.28%（F=9.29;P=0.0002）,PCT linear term B was-0.712（95%CI：-1.052,-0.372）,PCT quadratic term was B=0.0005（95%CI：0.0003,0.0007）.CONCLUSION：DCT and GAT measurements are conditioned by PCT though this effect,rather than linear,follows a2nd-degree polynomial pattern.
