Statistical Diagnostics of Electric Power Equipment

di Sergii Babak (Autore)

Vitalii Babak (Autore)

Artur Zaporozhets (Autore)

Springer, 2024

This book considers the issues of constructing mathematical probabilistic models of diagnostic signals, the development of statistical methods of their analysis in order to make diagnostic decisions and, finally, the technical implementation of the proposed diagnostic methods. Following the concept of primacy of the mathematical model of the diagnostic signal, the authors considered it expedient to consider first of all the questions connected with the theory of random processes possessing infinitely divisible distribution laws, linear and linear periodic random processes. Considerable attention is paid to the issues of simulation modeling of diagnostic signals and their statistical evaluation. Modern element base and new information technologies allowed to develop, build and practically test a number of experimental samples of information-measuring systems of statistical diagnostics of electric power engineering objects. Among these IMS, the systems are realized by means of unmanned diagnostic complexes, and also IMS of vibrodiagnostics of moving units of electric machines represents an important role. A large amount of experimental research has shown the operability and efficiency of the built IMS samples. Particular attention is paid to the selection of diagnostic spaces, formation of training sets, construction of solving rules for diagnosis and classification of EE defects. The authors do not pretend to a comprehensive consideration of the issues of EE diagnostics using statistical methods and IMS realized on their basis. At the same time, the results of researches, stated in this monograph, were a natural continuation of the subject of application of statistical methods in the field of control, monitoring and diagnostics for objects of electric power industry.

• Autore: Sergii Babak, Vitalii Babak, Artur Zaporozhets
• Anno edizione: 2024
• Editore: Springer
• Formato: EPUB3 con Adobe DRM
• Lingua: Inglese
• Compatibilità: Tutti i dispositivi (eccetto Kindle)
• Layout: Reflowable
• EAN: 9783031762536