• Smart Structures and Systems
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• v.28 no.6
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• pp.827-838
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• 2021

The dynamic displacement is considered to be an important indicator of structural safety, and becomes an indispensable part of Structural Health Monitoring (SHM) system for high-speed railway bridges. This paper proposes an indirect strain based dynamic displacement reconstruction methodology for high-speed railway box girders. For the typical box girders under eccentric train load, the plane section assumption and elementary beam theory is no longer applicable due to the bend-torsion coupling effects. The monitored strain was decoupled into bend and torsion induced strain, pre-trained multi-output support vector regression (M-SVR) model was employed for such decoupling process considering the sensor layout cost and reconstruction accuracy. The decoupled strained based displacement could be reconstructed respectively using box girder plate element analysis and mode superposition principle. For the transformation modal matrix has a significant impact on the reconstructed displacement accuracy, the modal order would be optimized using particle swarm algorithm (PSO), aiming to minimize the ill conditioned degree of transformation modal matrix and the displacement reconstruction error. Numerical simulation and dynamic load testing results show that the reconstructed displacement was in good agreement with the simulated or measured results, which verifies the validity and accuracy of the algorithm proposed in this paper.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.1
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• pp.39-45
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• 2015

Applications of smart sensors have been extended to safety systems in the aerospace, transportation and civil engineering fields. In particular, structural health monitoring techniques using smart sensors have gradually become necessary and have been developed to prevent dangers to human life and damage to assets. Generally, smart sensors are based on electro-magnets and have several weaknesses, including electro-magnetic interference and distortion. Therefore, fiber optic sensors are an outstanding alternative to overcome the weaknesses of electro-magnetic sensors. However, they require expensive devices and complex systems. This paper proposes a new, affordable and simple sensor system that uses a single fiber to monitor pressures at multiple-points. Moreover, a prototype of the sensor system was manufactured and tested for a feasibility study. Based on the results of this experimental test, a relationship was carefully observed between the bend loss conditions and light-intensity. As a result, it was shown that impacts at multiple-points could be monitored.

• Journal of Internet of Things and Convergence
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• v.5 no.2
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• pp.73-79
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• 2019

Research is underway on services and systems that provide real-time alerts for suffocating gases and potentially explosive materials, but currently smart bend type services are lacking. This study supports real-time identification of explosion hazards due to static electricity in the workplace and immediate elimination of accident occurrence factors, real-time monitoring of worker status and workplace hazards (oxygen, hazardous chemical concentration), and immediate warning and data in case of danger. We propose a method of establishing an accident prevention system through analysis. In this way, various accidents that may occur in industrial sites are monitored using IoT-based intelligent sensor nodes, wireless network technology, data processing middleware, and integrated control system, and real-time risk information at the industrial sites is prevented and accidents are prevented. By supporting a safe working environment, the company can significantly reduce costs compared to post-procurement costs.