Abstract
Effective Structural Health Monitoring (SHM) often requires continuous monitoring to capture changes of features of interest in structures, which are often located far from power sources. A key challenge lies in continuous low-power data transmission from sensors. Despite significant developments in long-range, low-power telecommunication (e.g., LoRa NB-IoT), there are inadequate demonstrative benchmarks for low-power SHM. Damage detection is often based on monitoring features computed from acceleration signals where data are extensive due to the frequency of sampling (~100–500 Hz). Low-power, long-range telecommunications are restricted in both the size and frequency of data packets. However, microcontrollers are becoming more efficient, enabling local computing of damage-sensitive features. This paper demonstrates the implementation of an Edge-SHM framework through low-power, long-range, wireless, low-cost and off-the-shelf components. A bespoke setup is developed with a low-power MEM accelerometer and a microcontroller where frequency and time domain features are computed over set time intervals before sending them to a cloud platform. A cantilever beam excited by an electrodynamic shaker is monitored, where damage is introduced through the controlled loosening of bolts at the fixed boundary, thereby introducing rotation at its fixed end. The results demonstrate how an IoT-driven edge platform can benefit continuous monitoring.
Highlights
IntroductionImplementing a monitoring system on full-scale structures is a complex and often expensive task, which requires both domain expertise and experience in the development of an end-to-end data pipeline, from sensor acquisition and communication to data analysis and inference [1,2,3]
Implementing a monitoring system on full-scale structures is a complex and often expensive task, which requires both domain expertise and experience in the development of an end-to-end data pipeline, from sensor acquisition and communication to data analysis and inference [1,2,3].Wired sensing systems are difficult to install, for an operational structure, have large power consumption, are susceptible to disturbances and damage and have a high cost of implementation and maintenance [4]
As indicated in the previous section, bolts are first loosened in discrete stages in the first set of experiments, which is subsequently followed by a set of tests where continuous and progressive loosening is carried out while the shaker excites the system via swept sine and white noise (5–200 Hz), respectively
Summary
Implementing a monitoring system on full-scale structures is a complex and often expensive task, which requires both domain expertise and experience in the development of an end-to-end data pipeline, from sensor acquisition and communication to data analysis and inference [1,2,3]. Wired sensing systems are difficult to install, for an operational structure, have large power consumption, are susceptible to disturbances and damage and have a high cost of implementation and maintenance [4]. Long-term monitoring of an infrastructure network requires low-cost, wireless, battery-powered sensing devices. There are several challenges involved in the deployment of wireless sensor networks (WSN) for SHM These include data storage and transmission, the requirement for low power and the cost and complexity of implementation. The data can either be stored locally or communicated to an offsite or cloud database for analysis
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