Abstract
The detection of noncatastrophic faults in conjunction with other factors can be used to determine the remaining life of an electric drive. As the frequency and severity of these faults increase, the working life of the drive decreases, leading to eventual failure. In this paper, four methods to identify developing electrical faults are presented and compared. They are based on the short-time Fourier transform, undecimated-wavelet analysis, and Wigner and Choi-Williams distributions of the field-oriented currents in permanent-magnet ac drives. The different fault types are classified using the linear-discriminant classifier and k-means classification. The comparison between the different methods is based on the number of correct classifications and Fisher's discriminant ratio. Multiple-class discrimination analysis is also introduced to remove redundant information and minimize storage requirements.
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 callDisclaimer: 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.
