Abstract
This work describes a miniaturized sensor network based on low-power, light-weight and small footprint microelectromechanical (MEMS) sensor nodes capable to simultaneously measure tri-axial accelerations and tri-axial angular velocities. A real-time data fusion algorithm based on complementary filters is applied to extract tilt angles. The resulting device is designed to show competitive performance over the whole frequency range of the inertial units. Besides the capability to provide accurate measurements both in static and dynamic conditions, an optimization process has been designed to efficiently make the fusion procedure running on-sensor. An experimental campaign conducted on a pinned-pinned steel beam equipped with a network comprising several sensor nodes was used to evaluate the reliability of the developed architecture. Performance metrics revealed a satisfactory agreement to the physical model, thus making the network suitable for real-time tilt monitoring scenarios.
Highlights
The deployment of vibration-based Structural Health Monitoring (SHM) systems involves a plurality of requirements to be satisfied
With the aforementioned scenarios, the presented work describes a monitoring system based on small footprint, low-power and light-weight MEMS sensors which can be interchangeably used as accelerometers, gyroscopes, or tilt nodes thanks to an embedded data fusion algorithm
Devices are connected by a Sensor Area Network (SAN) bus exploiting data-over-power (DoP) communication, whereas meaningful information is pre-processed by means of a lossless encoding technique; data is transmitted to a connected PC via a purposely designed companion gateway device
Summary
Nicola Testoni 1, * , Federica Zonzini 2 , Alessandro Marzani 3 , Valentina Scarponi 2 and. Advanced Research Center on Electronic Systems “Ercole De Castro” (ARCES), University of Bologna, Via V. Received: 30 November 2018; Accepted: 29 December 2018; Published: 1 January 2019
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