Abstract
This work describes a network of low power/low-cost microelectromechanical- (MEMS-) based three-axial acceleration sensors with local data processing and data-to-cloud capabilities. In particular, the developed sensor nodes are capable to acquire acceleration time series and extract their frequency spectrum peaks, which are autonomously sent through an ad hoc developed gateway device to an online database using a dedicated transfer protocol. The developed network minimizes the power consumption to monitor remotely and in real time the acceleration spectra peaks at each sensor node. An experimental setup in which a network of 5 sensor nodes is used to monitor a simply supported steel beam in free vibration conditions is considered to test the performance of the implemented circuitry. The total weight and energy consumption of the entire network are, respectively, less than 50 g and 300 mW in continuous monitoring conditions. Results show a very good agreement between the measured natural vibration frequencies of the beam and the theoretical values estimated according to the classical closed formula. As such, the proposed monitoring network can be considered ideal for the SHM of civil structures like long-span bridges.
Highlights
Real-time structural health monitoring (SHM) of civil and industrial buildings requires a network of smart sensors which are capable to simultaneously acquire signals coming from a plurality of transducers [1]
Among the algorithms of the first group, we considered autoregressive (AR) [37] and AR + noise models [38] which are suited for operational modal analysis in presence of strong acquisition noise
As concerning the nonparametric approaches, we have considered the frequency domain decomposition (FDD) [39], periodogram, and Welch estimation [38] methods
Summary
Real-time structural health monitoring (SHM) of civil and industrial buildings requires a network of smart sensors which are capable to simultaneously acquire signals coming from a plurality of transducers [1]. Among the variety of monitoring approaches, techniques based on the changes of structural natural frequencies and modes shapes have been largely investigated and adopted in the civil engineering field spanning from historical buildings [2,3,4,5] to more modern long-span bridges [6,7,8,9]. As such, advanced sensing networks capable to be permanently installed on the structure to be monitored are currently under investigation. Research developments strive to reduce (i) the weight and cost of the sensing elements, (ii) the sensor network power consumption, and (iii) the cost for the deployment of centralized data acquisition systems, as well as (iv) the amount of cables [10,11,12,13] whereas, in the other end, aimed at (v) handling and sharing large amount of collected data
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