Structural Reliability Estimation with Participatory Sensing and Mobile Cyber-Physical Structural Health Monitoring Systems

Abstract

With the help of community participants, smartphones can become useful wireless sensor network (WSN) components, form a self-governing structural health monitoring (SHM) system, and merge structural mechanics with participatory sensing and server computing. This paper presents a methodology and framework of such a cyber-physical system (CPS) that generates a bridge finite element model (FEM) integrated with vibration measurements from smartphone WSNs and centralized/distributed computational facilities, then assesses structural reliability based on updated FEMs. Structural vibration data obtained from smartphones are processed on a server to identify modal frequencies of an existing bridge. Without design drawings and supportive documentation but field measurements and observations, FEM of the bridge is drafted with uncertainties in the structural mass, stiffness, and boundary conditions (BCs). Then, 2700 FEMs are autonomously generated, and the baseline FEM is updated by minimizing the error between the crowdsourcing-based modal identification results and the FEM analysis. Furthermore, using 151 strong ground motion records from databases, the bridge response time history simulations are conducted to obtain displacement demand distribution. Finally, based on reference performance criteria, structural reliability of the bridge is estimated. Integrating the cyber (FEM analysis) and the physical (the bridge structure and measured vibration characteristics) worlds, this crowdsourcing-based CPS can provide a powerful tool for supporting rapid, remote, autonomous, and objective infrastructure-related decision-making. This study presents a new example of the emerging fourth industrial revolution from structural engineering and SHM perspective.

Innovative Methods and Materials in Structural Health Monitoring of Civil Infrastructures

“…The Structural Health Monitoring Systems is performed with the Artificial Intelligence by Chiaia and De Biagi [22], while Ozer and Feng propose the Participatory Sensing and Mobile Cyber-Physical [23].…”

Sensor Reliability in Cyber-Physical Systems Using Internet-of-Things Data: A Review and Case Study

“…The quantification of the reliability of grid splitting under degraded communication conditions in the presence of cyber interdependencies was presented in [51]. Recently, a method based on the finite element model of a bridge integrated with structural vibration data for a self-governing structural health monitoring system was shown in [52]. A set of algorithms for estimating the reliability of the system under certain responsible time constraints was also recently suggested in [53].…”

Human being emotion in cognitive intelligent robotic control. Pt.I: Quantum/ soft computing approach

“…The neuronal lattice sets up the spatial potential energy V(x). A quantum process described by the quantum state ψ which mediates the collective response of neuronal lattice, evolves in this spatial potential V (x) according to (2). As V (x) sets up the evolution path of the wave function, any desired response can be obtained by properly modulating the potential energy.…”

“…The state-of-the-art sensing and processing tools, health-monitoring technologies attract significant attention in research and industry in the last three decades [1,2]. The inclusion of human being operator in the feedback loop of intelligent control systems (ICS) for decision-making in complex situations creates both an information resource that can improve the efficiency of the development and application of ICS.…”

“…The inclusion of human being operator in the feedback loop of intelligent control systems (ICS) for decision-making in complex situations creates both an information resource that can improve the efficiency of the development and application of ICS. Unfortunately, it is often associated with an increasing in the information risk of hazard situations due to the presence of an unpredictable human health-monitoring and emotion state factors [2].…”