CBLA: Empowering Virtual Sensor Nodes with Zero Deployment Costs for SHM Systems

作者：Yang Wang, Ke Lei, Chong Zhang, Xin Wang, Xin Shi, Aihua Deng · 年份：2024 · DOI：10.1109/ijcnn60899.2024.10650833 · 被引用次数：3 · 研究领域：Modular Robots and Swarm Intelligence、Robotics and Sensor-Based Localization、Underwater Vehicles and Communication Systems

Structural Health Monitoring (SHM) monitors the working states of building structures to ensure their reliable operation, but the high cost of SHM sensor nodes limits its largescale deployment. In this paper, we propose a novel computational model that can generate "virtual" sensor nodes with reliable data output at zero deployment costs for cost-efficient SHM sensing. To achieve this, we combine one-dimensional convolutional layer in CNN with Bi-LSTM model to capture temporal and spatial correlations in the data; to improve the quality of the generated data, we design a weighted smoothing algorithm to reduce noise while preserving the integrity of the data; to enhance system robustness, we integrate attention mechanisms at the end of the model to assign different weights to each element, which can capture the limited but crucial information within the data. We evaluate our system on the dataset of the KW51 railroad bridge as an example. The results show that the generated virtual sensor node incurs zero deployment cost, and its data is 94% close to the ground truth, thus making it helpful for facilitating the largescale deployment of SHM systems.