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IoT-based SHM Portable Rig for Geo-Seismic Ground Motion Simulation | Qatar University

IoT-based SHM Portable Rig for Geo-Seismic Ground Motion Simulation

Ground motion stimulation system

A programmable multi-parametric four degrees of freedom electromechanical seismic wave events simulation platform was developed in the department of Electrical Engineering of the College of Engineering of Qatar University. The goal of this work was to ensure Qatar's infrastructure was secure and resilient, as well as the country's reputation for a successful and exceptional FIFA 2022.

A programmable mechanical structure capable of physically producing seismic waves, ground motions, land sliding, and earthquakes is always required for the real-time study of seismic waves, ground motions, land sliding, and earthquakes to improve the structural resilience of mass-transit, public places and A programmable mechanical framework capable of physically producing comparable geo-seismic motions is always required for vital infrastructure. The developed portable and smart mechatronic system demonstrated a 4-layer comprehensive simulation scheme, i.e. a) multi-parametric geo-Seismic realization engine (GRE), b) a programmable 4-DOF seismic machine apparatus (SMA); c) geo-mechanics motion control system (G-MCS), d) Web on-Chip interface with remote actuation and data capturing capabilities over the Wi-Fi. A user can simulate and emulate in the range of i) frequencies of extreme seismic waves from 0.1Hz to 178Hz; ii) terrestrial inclinations from -5.000° to 5.000°; iii) velocities of 1km/s to 25km/s iv) variable arrival times 1us to 3000ms; v) magnitudes M1.0 to M10.0 earthquake; vi) epi-central and hypo-central distances of 290+ and 350+ kilometers. Wadati and triangulation methods have been used for entire platform dynamics design and implementation as one of key research contributions in this work. This platform is as an enabler for a variety of applications such as training self-balancing and calibrating seismic-resistant designs and structures, in addition to studying and testing seismic detection devices as well as motion sensors. Remote users can get simulation results of any ground motions they need for testing detection and early warning algorithms. However, it serves as an adequate training colossus for machine learning algorithms and event management expert systems. This will be the first platform for seismic resilience design for infrastructure in Qatar and is expected to serve as a model reference architecture for future urban scale artificial intelligence (AI) systems in Qatar.