• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.6 s.52
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• pp.1-8
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• 2006

This paper describes the procedures developing the algorithm for analyzing signals acquired from the Bridge Weigh-in-Motion (BWIM) system installed in Seohae Bridge as a part of the bridge monitoring system. Through the analysis procedure, information about heavy traffics such as weight, speed, and number of axles are attempted to be extracted from time domain strain data of the BWIM system. One of numerous pattern recognition techniques, artificial neural network (ANN) is employed since it can effectively include dynamic effects, bridge-vehicle interaction, etc. A number of vehicle running experiments with sufficient load cases are executed to acquire training and/or test set of ANN. Extracted traffic information can be utilized for developing quantitative database of loading effect. Also, it can contribute to estimate fatigue lift or current health condition, and design truck can be revised based on the database reflecting recent trend of traffic.

• Journal of Navigation and Port Research
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• v.37 no.2
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• pp.143-148
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• 2013

The aim of this study is to investigate the characteristics on the profile of local ice load acting on side shell of port side in bow part due to broken ice during icebreaking of ships in ice covered waters. The first Korean icebreaking research vessel 'ARAON' had a sea ice field trial in the Arctic Sea during early August, 2010, and the signals due to local ice impact measured from several strain gauges installed at bow part were gathered. It is known that these data with structural response characteristics due to local ice impact have some different characteristics with a typical hydraulic impact pressure - time history. In this study, the time history on the measured signals was analyzed and the characteristic values were presented using non-dimensional parameters.