Anomaly warning of gearbox oil temperature in wind turbine generator system based on iForest -DBSCAN -RF and optimized CATBoost

Authors

Liangyu MA, School of Control and Computer Engineering ， North China Electric Power University ， Baoding 071003， China;Baoding Key Laboratory of State Detection and Optimization for Integrated Energy System ， Baoding 071003， ChinaFollow
Likai HAN, School of Control and Computer Engineering ， North China Electric Power University ， Baoding 071003， China
Liangliang ZHAI, School of Control and Computer Engineering ， North China Electric Power University ， Baoding 071003， China

Keywords

wind turbine generator sy stem;fault warning;iForest;DBSCAN;RF

Abstract

Data cleaning，feature selection，and the estab lishment of a prediction model are indispensable steps to realize anomaly warning of the wind turbine generator system based on data collection and supervisory control and data acquisition （SCADA）.Firstly，isolated forest （iForest） and density-based spatial clustering of applications with noise （DBSCAN ） algorithm are combined to effectively clean the data outliers of SCADA，and random forest （RF） and Pearson correlation coefficient method are used to optimize the input parameters of the model.Based on the categorical boosting （CATBoost ） algorithm optimized by Optuna，a prediction model of gearbox oil pool temperature in the wind turbine generator system under normal operating conditions is established.Then，the state evaluation index is constructed with the sliding window method，and the interval estimation theory is employed to determine its critical threshold for anomaly discrimination of oil temperature.Finally，the anomaly warning of oil temperature is realized.The real historical fault data of oil temperature anomaly in the SCADA system of the wind turbine generator system are used to verify the effectiveness of the method.

DOI

10.19781/j.issn.1673-9140.2025.04.018

First Page

193

Last Page

204

Recommended Citation

MA, Liangyu; HAN, Likai; and ZHAI, Liangliang (2025) "Anomaly warning of gearbox oil temperature in wind turbine generator system based on iForest -DBSCAN -RF and optimized CATBoost," Journal of Electric Power Science and Technology: Vol. 40: Iss. 4, Article 18.
DOI: 10.19781/j.issn.1673-9140.2025.04.018
Available at: https://jepst.researchcommons.org/journal/vol40/iss4/18