A Novel Supervised Filter Feature Selection Method Based on Gaussian Probability Density for Fault Diagnosis of Permanent Magnet DC Motors

For permanent magnet DC motors (PMDCMs), the amplitude of the current signals gradually decreases after the motor starts. In this work, the time domain features and time-frequency-domain features extracted from several successive segments of current signals make up a feature vector, which is adopted...

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Detalles Bibliográficos
Autores principales: Wang, Weihao, Lu, Lixin, Wei, Wang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9572652/
https://www.ncbi.nlm.nih.gov/pubmed/36236219
http://dx.doi.org/10.3390/s22197121

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9572652/
https://www.ncbi.nlm.nih.gov/pubmed/36236219
http://dx.doi.org/10.3390/s22197121

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