Literature DB >> 31550624

Diffuse ultrasonic wave-based structural health monitoring for railway turnouts.

Kai Wang1, Wuxiong Cao1, Lei Xu1, Xiongbin Yang1, Zhongqing Su2, Xiongjie Zhang3, Lijun Chen3.   

Abstract

Real-time damage evaluation is a critical step to warrant the integrity of turnout systems in railway industry. Nevertheless, existing structural health monitoring (SHM) approaches, despite their proven effectiveness in laboratory demonstration, are restricted from in-situ implementation in engineering practice. Based upon the continued endeavors of the authors in developing SHM approaches and exploring real world applications, an in-situ SHM approach, exploiting active diffuse ultrasonic waves (DUW) and a benchmark-less method, has been developed and implemented in a marshalling station in China. When trains passing a railway turnout, the train-induced loads on the rail track can lead to the growth of defects in the rail, and such growth disturbs the ultrasound traversing at the defect and gives rise to discrepancies between the DUW signals acquired before and after the train's passage. On this basis, a damage index, making use of the defect growth-induced changes in DUW signals, is proposed to identify the presence of defect. The probability of defect growth induced by the train-related load can be used to assess the severity of the defect. Via an online diagnosis system, conformance tests are implemented in Chengdu North Marshalling Station, in which defects in switch rails are identified and the health status of in-service rail tracks are continuously monitored. The results have demonstrated the effectiveness and reliability of DUW-driven SHM towards real world railway turnout applications.
Copyright © 2019 Elsevier B.V. All rights reserved.

Keywords:  Diffuse ultrasonic waves; In-situ health monitoring; Industrial implementation; PZT sensor network; Railway turnouts

Year:  2019        PMID: 31550624     DOI: 10.1016/j.ultras.2019.106031

Source DB:  PubMed          Journal:  Ultrasonics        ISSN: 0041-624X            Impact factor:   2.890


  2 in total

Review 1.  Industry 4.0 Technologies Applied to the Rail Transportation Industry: A Systematic Review.

Authors:  Camilo Laiton-Bonadiez; John W Branch-Bedoya; Julian Zapata-Cortes; Edwin Paipa-Sanabria; Martin Arango-Serna
Journal:  Sensors (Basel)       Date:  2022-03-24       Impact factor: 3.576

2.  Diffuse Ultrasonic Wave-Based Damage Detection of Railway Tracks Using PZT/FBG Hybrid Sensing System.

Authors:  Xiangtao Sun; Chuanrui Guo; Lei Yuan; Qingzhao Kong; Yiqing Ni
Journal:  Sensors (Basel)       Date:  2022-03-24       Impact factor: 3.576

  2 in total

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