• Journal of the Society of Disaster Information
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• 제18권4호
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• pp.847-860
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• 2022

Purpose: The purpose of this paper is to present a basic study on the development of a self-generation infrastructure for monitoring the health of harbour structures. Method: By developing a self-generation system and fiber optic sensors for seawater, the study provides basic research data on port structure health monitoring. Result: Through sunlight simulation analysis, 4-5 hours of sunlight can be secure in the domestic environment. Through this, the optical splitter (Introgate) that collects the raw data from the FBG sensor applicable to seawater, the MCU that calculates it, the IoT module with wireless communication functionality, the monitoring server and the supply system are set up. Conclusion: Monitoring port structures directly with fiber optic probes (FBG) and the possibility of using selfpowered systems were confirmed.

• Corrosion Science and Technology
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• 제14권3호
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• pp.147-152
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• 2015

Corrosion of steel reinforcement is a major factor in the deterioration of harbour and bridge structure. Steel corrosion in concrete must be checked for assessing the condition of a reinforced concrete structure. There are several ways how to measure the corrosion condition of reinforced concrete, but the corrosion potential measurement is a very simple, rapid, cost-effective and non-destructive technique to evaluate the severity of corrosion in reinforced concrete structure, therefore commonly used by engineers. However some particular situations may not relate to the reinforcement corrosion probability and a simple comparison of the corrosion potential data with the ASTM C876 Standard on steel reinforcement corrosion probability could be meaningless and not give reliable informations because of environment factors as oxygen concentration, chloride content, concrete resistance. Therefore this paper explains the risk of corrosion assessment in reinforced concrete structure and how many factors can affect the reliability of the corrosion potential data.