Keywords :
data-driven and model-based approaches; fault detection and diagnosis; fault-tolerant control; robustness and reliability; signal-based schemes; wind turbine; Control of wind turbines; Data driven; Data-driven and model-based approach; Fault detection and diagnosis; Faults diagnosis; Faults tolerant controls; Model based approach; Renewable power generation; Robustness and reliability; Signal-based scheme; Renewable Energy, Sustainability and the Environment; Building and Construction; Fuel Technology; Engineering (miscellaneous); Energy Engineering and Power Technology; Energy (miscellaneous); Control and Optimization; Electrical and Electronic Engineering
Abstract :
[en] Wind turbines are playing an increasingly important role in renewable power generation. Their complex and large-scale structure, however, and operation in remote locations with harsh environmental conditions and highly variable stochastic loads make fault occurrence inevitable. Early detection and location of faults are vital for maintaining a high degree of availability and reducing maintenance costs. Hence, the deployment of algorithms capable of continuously monitoring and diagnosing potential faults and mitigating their effects before they evolve into failures is crucial. Fault diagnosis and fault tolerant control designs have been the subject of intensive research in the past decades. Significant progress has been made and several methods and control algorithms have been proposed in the literature. This paper provides an overview of the most recent fault diagnosis and fault tolerant control techniques for wind turbines. Following a brief discussion of the typical faults, the most commonly used model-based, data-driven and signal-based approaches are discussed. Passive and active fault tolerant control approaches are also highlighted and relevant publications are discussed. Future development tendencies in fault diagnosis and fault tolerant control of wind turbines are also briefly stated. The paper is written in a tutorial manner to provide a comprehensive overview of this research topic.
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