Abstract
Structural Health Monitoring (SHM) of large structures is a critical aspect due to various environmental conditions, high speed & long-distance communication, dynamic analysis of the structure, and cost of operation. These issues can be addressed using Fiber Bragg Grating (FBG) sensor technology which has evolved to a new height and is widely used in various distributed critical sensing applications. These are mostly preferred due to long-distance monitoring, low cost of operation, and immunity to Electromagnetic (EM) radiations. Similarly, the monitoring of a large structure from a long distance is also one of the crucial aspects of SHM technologies. These technological challenges can be addressed using an integrated distributed sensing solution consisting of FBG sensors, Big Data, Kafka, and the Internet of Things (IoT). In this article, the fabrication of the FBG sensor and the bonding of the sensing element to the base plate of the suspension bridge structure are discussed along with experimental details. A scalable architecture of the proposed Smart Distributed Sensing (SDS) model using FBG sensors is also discussed in this article. The experimental validation is performed using an IoT based FBG sensing mechanism to estimate the strain distribution profile at the bonding region of the base plate from a central location.
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Acknowledgements
The authors thank the personnel of Central Glass and Ceramic Research Institute (CSIR-CGCRI), Kolkata who have provided continuous support in fabricating and calibrating the FBG sensor during this research work. The authors also thank Silicon Institute of Technology, Bhubaneswar for providing licensed software like LabVIEW and state-of-the art equipment like the FBG interrogator, for successful conduction of the experiments related to this study. This article is an extension of the research work sponsored by Silicon Research Promotion Scheme (SRPS), Silicon Institute of Technology India.
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Mohapatra, A.G., Talukdar, J., Mishra, T.C. et al. Fiber Bragg grating sensors driven structural health monitoring by using multimedia-enabled iot and big data technology. Multimed Tools Appl 81, 34573–34593 (2022). https://doi.org/10.1007/s11042-021-11565-w
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DOI: https://doi.org/10.1007/s11042-021-11565-w