Abstract
Catenary has been exposed outdoors for a long term, and its failure rate is very high, which has seriously affected the operation and development of traction power supply system. Due to the problems of long detection time, backward detection means and influenced by human factors in traditional catenary fault identification methods, this paper proposed a fault identification method based on PSO-ELM. This method could reduce the hidden layer nodes of traditional ELM and improve the accuracy of identification. In this paper, this method was compared with ELM, GA-ELM, BP, GA-BP and PSO-BP. A sample of catenary detection data of a power supply section in 2018 was selected. The results show that PSO-ELM is an efficient method for the fault identification of catenary.
Published Version (
Free)
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.
