Data Fault Detection for Digital Twin Learning Action Decision of a Wind Turbine

Abstract

This paper presents the design of a classifier of variable failures in a wind turbine system. The classifier is based on a structure formed by several TS fuzzy inference systems, with projections of the data onto components of a principal component analysis. The classifier is part of a discrepancy evaluator for triggering the learning mechanism of the digital twin of the wind turbine