Embedded compressive sampling (CS) algorithm under ultra-low rate wireless communication for long-term bridge monitoring

Wentao Wang; Jianing Wang; Bin Han; Guangyou Mu; Jingtang Xu; Yang Li

doi:10.1117/12.2613189

18 April 2022 Embedded compressive sampling (CS) algorithm under ultra-low rate wireless communication for long-term bridge monitoring

Wentao Wang, Jianing Wang, Bin Han, Guangyou Mu, Jingtang Xu, Yang Li

Author Affiliations +

Proceedings Volume 12046, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2022; 1204603 (2022) https://doi.org/10.1117/12.2613189
Event: SPIE Smart Structures + Nondestructive Evaluation, 2022, Long Beach, California, United States

Abstract

Wireless sensor offers impressive functionality compared with traditional wired sensor, including straightforward installation, lightweight, low-cost circuits, high-performance microcontroller and sensors, easy maintenance, and flexibility and scalability for projects. While, there are various challenges to be considered in wireless sensors such as energy efficiency, communication rate, reliability, and data loss. And these drawbacks constrain its applications on specific projects, e.g., long-term monitoring for infrastructures. To overcome the aforementioned drawbacks, this study aims to explore a comprehensive solution from two sides: both the hardware achievement and the communication algorithm. Ultralow power Urbano wireless sensing node with a high-performance computational microcontroller is proposed as the backbone of the wireless sensing system. Satellite communication is employed to ensure the proposed wireless sensing node is completely autonomous to suit a wider range of fields without the requirements of additional base stations (that host single-board computers). In addition, this paper advances compressive sampling (CS) framework as an alternative to traditional Nyquist/Shannon sampling for SHM. An embedded CS-based algorithm is developed to compress the acquired time-history signal, save the storage space of Urbano, reduce data rate requirements, and ensure the accuracy of data via ultra-low rate communication.

Citation Download Citation

Wentao Wang, Jianing Wang, Bin Han, Guangyou Mu, Jingtang Xu, and Yang Li "Embedded compressive sampling (CS) algorithm under ultra-low rate wireless communication for long-term bridge monitoring", Proc. SPIE 12046, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2022, 1204603 (18 April 2022); https://doi.org/10.1117/12.2613189

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KEYWORDS

Bridges

Structural health monitoring

Reconstruction algorithms

Sensors

Satellites

Wireless communications

Intelligence systems

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