RF Energy Harvesting for Batteryless and Maintenance-Free Condition Monitoring of Railway Tracks

被引:45
|
作者
Li, Pengyu [1 ]
Long, Zhihe [1 ]
Yang, Zhengbao [1 ]
机构
[1] City Univ Hong Kong, Dept Mech Engn, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
Radio frequency; Rail transportation; Wireless sensor networks; Wireless communication; Monitoring; Inspection; Energy harvesting; Dickson voltage multiplier (DVM); Internet of Things (IoT); radio frequency (RF) energy harvesting; railway tracks inspection; structural health monitoring;
D O I
10.1109/JIOT.2020.3023475
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Current railway track condition monitoring relies on inefficient human inspectors and expensive inspection vehicles, where high-frequency inspection is unreachable since these methods occupy the tracks. This article proposes a batteryless railway monitoring system based on radio-frequency (RF) energy harvesting to detect early defects on rail tracks. The key part of the system is a batteryless wireless sensor tag (BLWST) installed on railway tracks. The BLWST can harvest RF energy from a reader installed on the train, and precisely measure and wirelessly transmit the vibration condition of tracks back to the reader. The proposed system eliminates the demands for cables and battery replacement, thus achieving low installation and maintenance costs. The high-frequency monitoring also provides a more reliable inspection than the existing methods. The BLWST is based on the 3-stage Dickson voltage multiplier (DVM) and can be activated by a dedicated RF power source at a maximum distance of 2.3 m. Experiments show that a maximum energy conversion efficiency of 25% and 500 working cycles per second are achieved. For demonstration, we construct a miniaturized railway system with the batteryless prototype and exhibit a reliable wireless power transfer and data communication.
引用
收藏
页码:3512 / 3523
页数:12
相关论文
共 50 条
  • [21] A Batteryless Chronic Wound Monitoring System With 13.56-MHz Energy Harvesting
    Cho, Han-Won
    Jo, Sung-Hun
    Yoon, Jo Hee
    Goh, Tae-Sik
    Choi, Bong Gill
    Yoo, Hyung-Joun
    IEEE SENSORS JOURNAL, 2019, 19 (20) : 9431 - 9440
  • [22] Condition monitoring of railway tracks using in-service vehicles - Development of probe system for track condition monitoring
    Tsunashima, Hitoshi
    Matsumoto, Akira
    Kojima, Takashi
    Mizuma, Takeshi
    Japanese Railway Engineering, 2008, (161): : 6 - 10
  • [24] Condition monitoring and e-maintenance solution of railway wheels
    Asplund, Matthias
    Famurewa, Stephen
    Rantatalo, Matti
    JOURNAL OF QUALITY IN MAINTENANCE ENGINEERING, 2014, 20 (03) : 216 - 232
  • [25] Unsupervised domain adaptation for drive-by condition monitoring of multiple railway tracks
    Ghiasi, Ramin
    Lestoille, Nicolas
    Diaine, Cassandre
    Malekjafarian, Abdollah
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2025, 139
  • [26] Energy Harvesting for Structural Health Monitoring of Railway Bridges
    Camara-Molina, J. C.
    Romero, Antonio
    Moliner, Emma
    Dolores Martinez-Rodrigo, Maria
    Galvin, Pedro
    EUROPEAN WORKSHOP ON STRUCTURAL HEALTH MONITORING (EWSHM 2022), VOL 2, 2023, : 855 - 864
  • [27] RF energy harvesting for intraoral orthodontic force monitoring
    Li, Pengyu
    Zhu, Luying
    Ding, Yongtao
    Long, Zhihe
    Yang, Yanqi
    Pan, Jia
    Gu, Min
    Wang, Wenping
    Yang, Zhengbao
    NANO ENERGY, 2024, 121
  • [28] A residential maintenance-free long-term activity monitoring system for healthcare applications
    Xenofon Fafoutis
    Evgeny Tsimbalo
    Evangelos Mellios
    Geoffrey Hilton
    Robert Piechocki
    Ian Craddock
    EURASIP Journal on Wireless Communications and Networking, 2016
  • [29] Designing an open source maintenance-free Environmental Monitoring Application for Wireless Sensor Networks
    Delamo, Manuel
    Felici-Castell, Santiago
    Perez-Solano, Juan J.
    Foster, Andrew
    JOURNAL OF SYSTEMS AND SOFTWARE, 2015, 103 : 238 - 247
  • [30] A critical review of Information Assurance (IA) framework for condition-based maintenance of railway tracks
    Al-Douri, Y. K.
    Tretten, P.
    RISK, RELIABILITY AND SAFETY: INNOVATING THEORY AND PRACTICE, 2017, : 1072 - 1078