A Study on Wheel Member Condition Recognition Using Machine Learning (Support Vector Machine)

• Published in: Sensors (Basel, Switzerland) Vol. 23; no. 20; p. 8455
• Main Authors: Lee, Jin-Han, Lee, Jun-Hee, Yun, Kwang-Su, Bae, Han Byeol, Kim, Sun Young, Jeong, Jae-Hoon, Kim, Jin-Pyung
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 13.10.2023; MDPI
• Subjects: Acoustics; Algorithms; Cameras; Classification; Communication; Data collection; Data mining; Light rail transportation; Load; Machine learning; machine learning algorithm; Methods; Railroads; recognizing condition algorithm; Rubber; Sensors; Strain gauges; Support vector machines; tire; Tires; Vehicles; Vibration; wheel; Wheels; South Korea; recognizing condition algorithm; machine learning algorithm; wheel; tire

The wheels of railway vehicles are of paramount importance in relation to railroad operations and safety. Currently, the management of railway vehicle wheels is restricted to post-event inspections of the wheels whenever physical phenomena, such as abnormal vibrations and noise, occur during the ope...