Abstract
In this article, we proposed a novel method based on principal component analysis and support vector machines was presented for fault diagnosis of three-phase rectifiers, in which the principal component analysis of fault signal is used to extract the features corresponding to various fault, then fault types are identified through the pattern recognition classifier based on support vector machines. The simulation result of fault diagnosis of a thyristor in a three-phase full-bridge controlled rectifier shows that the method can make an accurate identification of fault types as well as the location of the fault elements for power electronics circuits, and it has an excellent performance for noise robustness and calculation complexity. Therefore, it is quite practically valuable in the solution to the fault problems for power electronics rectifiers.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Electrical Power & Energy Systems
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
