Damage Detection of Wooden Structural Members Using Piezoelectric Sensor and Autoencoder for Structural Health Monitoring

Abstract

We tried to identify the state of members injured by natural disasters by machine learning using the vibration response waveform of a piezoelectric sensor attached a wooden element. We destroyed step by step a wooden wall connected to columns. In each destruction stage, the vibrational characteristic is measured by a piezoelectric sensor. The oscillating source to obtain data models vibrations of natural vibration coming from a wind and so on. We detected the injury of a member by using autoencoder which learned only the waveform of the element which is not injured.