Finding Critical Middle Point using Wireless Sensor Networks for Structural Health Monitoring

Because it makes it possible to identify structural damage early on, structural health monitoring, or SHM, is essential to maintaining the dependability and safety of civil infrastructure. Because of their scalability, flexibility, and ease of installation, wireless sensor networks, or WSNs, have become a viable solution for SHM. In this paper, a WSN-based method for determining a structure's critical middle point through the analysis of vibration and strain data gathered from dispersed sensor nodes is proposed. Data collection, feature extraction, damage index creation, critical middle point identification, and strategic sensor deployment are all included in the suggested methodology. A beam-like structural model with uniformly deployed wireless sensors was used for experimental evaluation. Peak acceleration, strain variation, and damage index metrics are used in performance analysis to show that the mid-span sensor continuously shows the highest structural reaction. The accuracy and dependability of the suggested system in locating the structure's critical region are further confirmed by graphic results. The wireless-based framework ensures efficient damage localization while reducing the need for cabling. In structural health monitoring applications, the suggested method offers an economical, scalable, and effective way to identify critical points. It also lays the groundwork for future machine learning and real-time monitoring integration.