부산대학교 도서관

We are finding the location of damage to timber and wooden houses. Two years ago, we succeeded in classifying the damage location with 90% accuracy in a wooden brace house. Last year, we conducted an experiment on a model house in Oita Prefecture and improved the classification rate by preprocessing data. Therefore, we conducted experiments to further improve the classification rate and practical application. The vibration data of the model house in Oita Prefecture was collected using multiple 3-axis acceleration sensors equipped with wireless communication means and monitored at Katsushika Campus, Tokyo University of Science, about 969 km away. By classifying the waveform data by CNN, we succeeded in classifying the damage location and degree of damage with a maximum accuracy of 86.0%.