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Detection of Rail Defects Using NDT Methods.
Xiong, Longhui; Jing, Guoqing; Wang, Jingru; Liu, Xiubo; Zhang, Yuhua.
Afiliação
  • Xiong L; Postgraduate Department, China Academy of Railway Sciences, Beijing 100081, China.
  • Jing G; Infrastructure Inspection Research Institute, China Academy of Railway Sciences Co., Ltd., Beijing 100081, China.
  • Wang J; School of Civil Engineering, Beijing Jiaotong University, Beijing 100044, China.
  • Liu X; Infrastructure Inspection Research Institute, China Academy of Railway Sciences Co., Ltd., Beijing 100081, China.
  • Zhang Y; School of Civil Engineering, Beijing Jiaotong University, Beijing 100044, China.
Sensors (Basel) ; 23(10)2023 May 10.
Article em En | MEDLINE | ID: mdl-37430540
ABSTRACT
The rapid development of high-speed and heavy-haul railways caused rapid rail defects and sudden failure. This requires more advanced rail inspection, i.e., real-time accurate identification and evaluation for rail defects. However, existing applications cannot meet future demand. In this paper, different types of rail defects are introduced. Afterwards, methods that have the potential to achieve rapid accurate detection and evaluation of rail defects are summarized, including ultrasonic testing, electromagnetic testing, visual testing, and some integrated methods in the field. Finally, advice on rail inspection is given, such as synchronously utilizing the ultrasonic testing, magnetic flux leakage, and visual testing for multi-part detection. Specifically, synchronously using the magnetic flux leakage and visual testing technologies can detect and evaluate surface and subsurface defects, and UT is used to detect internal defects in the rail. This will obtain full rail information, to prevent sudden failure, then ensure train ride safety.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China