Rail head surface defect magnetic flux leakage signal filtering based on the relativity among the adjacent sensors
Author:
Publisher
Elsevier BV
Subject
Applied Mathematics,Electrical and Electronic Engineering,Condensed Matter Physics,Instrumentation
Reference25 articles.
1. Supervised machine learning approach for detecting missing clamps in rail fastening system from differential eddy current measurements;Chandran;Appl. Sci.,2021
2. Kim, Geonwoo, et al. “Development of phased array ultrasonic system for detecting rail cracks.” Sensors and Actuators A: Physical 311 (2020): 112086.
3. Zheng, Zhong, et al. “Automated rail surface crack analytics using deep data-driven models and transfer learning.” Sustainable Cities and Society 70 (2021): 102898..
4. Rail component detection, optimization, and assessment for automatic rail track inspection;Ying Li;IEEE Trans. Intell. Transp. Syst.,2014
5. Kim, YoungChae, et al. “Design of spider-type non-destructive testing device using magnetic flux leakage.” 2019 IEEE Student Conference on Electric Machines and Systems (SCEMS 2019). IEEE, 2019.
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