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.
Explore Performance Optimization of Fault Diagnosis Methods for Power Systems by Dinghui Wu, Juan Zhang, Junyan Fan & Dandan Tang on eBooksStore by Arnlweb. Discover book details, reader ratings, reviews, release information, genres, and related digital books available through the iTunes Store.
This book is part of our growing collection of bestselling eBooks, popular digital reading materials, and trending author releases. Readers can explore similar books, discover new authors, and browse related genres including fiction, romance, mystery, fantasy, business, self-help, educational books, and more.
Our platform helps readers discover highly rated digital books optimized for smartphones, tablets, laptops, and desktop devices. Browse fast-loading book pages, reader reviews, and popular recommendations from bestselling authors worldwide.