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Performance Optimization of Fault Diagnosis Methods for Power Systems / by Dinghui Wu, Juan Zhang, Junyan Fan, Dandan Tang

By: Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Engineering Applications of Computational Methods ; 9Publisher: Singapore : Springer Nature Singapore, 2023Publisher: Singapore : Imprint: Springer, 2023Edition: 1st ed. 2023Description: 1 Online-Ressource(XIII, 127 p. 61 illus., 44 illus. in color.)ISBN:
  • 9789811945786
Subject(s): Additional physical formats: 9789811945779 | 9789811945793 | 9789811945809 | Erscheint auch als: 9789811945779 Druck-Ausgabe | Erscheint auch als: 9789811945793 Druck-Ausgabe | Erscheint auch als: 9789811945809 Druck-AusgabeDOI: DOI: 10.1007/978-981-19-4578-6Online resources: Summary: Introduction -- Fault Diagnosis of Variable Pitch for Wind Turbine Based on Multi-innovation Forgetting Gradient Identification Algorithm -- Active Fault-tolerant Linear Parameter Varying Control for the Pitch Actuator of Wind Turbines -- Fault Estimation and Fault-tolerant Control of Wind Turbines Using the SDW-LSI Algorithm -- A New Fault Diagnosis Approach for the Pitch System of Wind Turbines.Summary: This book focuses on the performance optimization of fault diagnosis methods for power systems including both model-driven ones, such as the linear parameter varying algorithm, and data-driven ones, such as random matrix theory. Studies on fault diagnosis of power systems have long been the focus of electrical engineers and scientists. Pursuing a holistic approach to improve the accuracy and efficiency of existing methods, the underlying concepts toward several algorithms are introduced and then further applied in various situations for fault diagnosis of power systems in this book. The primary audience for the book would be the scholars and graduate students whose research topics including the control theory, applied mathematics, fault detection, and so on.PPN: PPN: 1816991082Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-INR | ZDB-2-SXIT
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