Assessment of low-cost wireless sensors for structural health monitoring applications

Abstract

Structural Health Monitoring (SHM) programs play an essential task in the field of civil engineering, especially for assessing safety conditions involving large structures such as viaducts, bridges, stadiums, and tall buildings. In fact, some of these structures are monitored 24 hours a day, 7 days a week, to supply dynamic measurements that can be used for the identification of structural problems, e.g., presence of cracks, excessive vibration, damage, among others. SHM programs may provide automated assessment of structural health by processing vibration data obtained from sensors attached to the structure. Frequently, SHM uses wired systems, which are usually expensive due to the necessity of continuous maintenance and are not always suitable for sensing remote structures. Conversely, commercial wireless systems often demand high implementation costs. Hence, this paper proposes the use of a low-cost wireless sensing system based on the single board computer Raspberry Pi, which significantly reduces implementation expenses while keeping data’s integrity. The wireless communication is performed in real-time through a local wireless network, responsible for sending and receiving vibration data. The proposed system is validated by comparing its results with a commercial wired system through a series of controlled experimental applications. The results suggest that the proposed system is suitable for civil SHM applications.

Dynamic identification of a cable-stayed footbridge using a low-cost data acquisition system

“…The traditional systems are composed of acquisition boards and signal conditioners that offer the best performance to date, using analog sensors that offer high sensitivity and low signal noise. The most recent systems mainly pursue wireless solutions in order to eliminate interruptions to the structures' operations, as well as provide continuous and remote monitoring of the structure, as described in [9], [10]. It would be much less expensive to use low-cost sensors for this purpose that can remain fixed to or embedded in the structure (not recovered), as long as they offer acceptable performance and robustness.…”