Signal processing techniques for IoT-based structural health monitoring

Abstract

With the advancement of modern technology, structures like buildings, bridges, etc. are getting structurally complicated, and safety has become an issue. Structural Health Monitoring (SHM) with Internet of Things (IoT) can help improving security and safety. However, efficient signal processing for IoT is a challenge. In this paper, a signal processing based SHM is proposed where a simple Butterworth filter was used to remove noises. Cross-Correlation was used for damage detection. If there was any damage found, using a mathematical model, damage size and location were determined. After analyzing the experimental data, error found in damage localization is 2.9% and error in determining damage size is 3.344%. Since the whole algorithm does not associate with complex mathematical calculations, this system can be used for low-cost distributed system for SHM.