TY - GEN
T1 - Realizing a self-powered real-time monitoring system on high-speed trains
AU - Lai, S. K.
AU - Wang, C.
AU - Zhang, L. H.
AU - Ni, Y. Q.
N1 - Funding Information:
The work described here was supported by the Research Impact Fund (Project No. R5020‐18) from the Research Grants Council of the Hong Kong Special Administrative Region. The funding support from the Innovation and Technology Commission of the HKSAR Government to the Hong Kong Branch of National Rail Transit Electrification and Automation Engineering Technology Research Center (Grant No. K‐BBY1) is gratefully acknowledged. In addition, the authors would like to express our sincere gratitude to the support of the CRRC National Innovation Center of Advanced Rail Transit Equipment for conducting the full-scale rolling-vibration test. We also thank Dr. S.M. Wang and Mr. T.T. Wai for data collection.
Publisher Copyright:
© INTER-NOISE 2021 .All right reserved.
PY - 2021/8
Y1 - 2021/8
N2 - The development of the worldwide high-speed rail network is expanding at a rapid pace, imposing great challenges on the operation safety. Recent advances in wireless communications and information technology can integrate the Internet of Things and cloud computing to form a real-time monitoring platform of high-speed trains. To realize this system, a sustainable power source is indispensable. In this case, an ideal solution is to deploy a vibration-based energy harvester instead of batteries for the electrical supply of wireless sensors/devices, as vibrations induced by rail/wheel contact forces and vehicle dynamics are an abundant energy source. To address this challenge, a multi-stable, broadband and tri-hybrid energy harvesting technique was recently proposed, which can work well under low-frequency, low-amplitude, and time-varying ambient sources. In this work, we will introduce our idea, following the recently proposed energy harvester and the dynamic responses of a train vehicle, to design a self-sustained sensing system on trains. Supported by this self-powered system, accelerometers and microphones deployed on an in-service train (in axle boxes/bogie frames) can measure vibration and noise data directly. The correlation of the vibration and noise data can then be analyzed simultaneously to identify the dynamic behavior (e.g., wheel defects) of a moving train.
AB - The development of the worldwide high-speed rail network is expanding at a rapid pace, imposing great challenges on the operation safety. Recent advances in wireless communications and information technology can integrate the Internet of Things and cloud computing to form a real-time monitoring platform of high-speed trains. To realize this system, a sustainable power source is indispensable. In this case, an ideal solution is to deploy a vibration-based energy harvester instead of batteries for the electrical supply of wireless sensors/devices, as vibrations induced by rail/wheel contact forces and vehicle dynamics are an abundant energy source. To address this challenge, a multi-stable, broadband and tri-hybrid energy harvesting technique was recently proposed, which can work well under low-frequency, low-amplitude, and time-varying ambient sources. In this work, we will introduce our idea, following the recently proposed energy harvester and the dynamic responses of a train vehicle, to design a self-sustained sensing system on trains. Supported by this self-powered system, accelerometers and microphones deployed on an in-service train (in axle boxes/bogie frames) can measure vibration and noise data directly. The correlation of the vibration and noise data can then be analyzed simultaneously to identify the dynamic behavior (e.g., wheel defects) of a moving train.
UR - http://www.scopus.com/inward/record.url?scp=85117373886&partnerID=8YFLogxK
U2 - 10.3397/IN-2021-1476
DO - 10.3397/IN-2021-1476
M3 - Conference article published in proceeding or book
AN - SCOPUS:85117373886
T3 - Proceedings of INTER-NOISE 2021 - 2021 International Congress and Exposition of Noise Control Engineering
BT - Proceedings of INTER-NOISE 2021 - 2021 International Congress and Exposition of Noise Control Engineering
A2 - Dare, Tyler
A2 - Bolton, Stuart
A2 - Davies, Patricia
A2 - Xue, Yutong
A2 - Ebbitt, Gordon
PB - The Institute of Noise Control Engineering of the USA, Inc.
T2 - 50th International Congress and Exposition of Noise Control Engineering, INTER-NOISE 2021
Y2 - 1 August 2021 through 5 August 2021
ER -