Researcher's Information

Professor

NOMURA, Yasutoshi

Civil Engineering

Applied informatics to structural health and safety management

Recently, monitoring the integrity of the structures accurately and reliably has become extremely important in various fields in order to increase operational lifetime and improve safety. To this end, numerous methods which include structural health monitoring (SHM) systems have been researched. SHM involves the observation of a structure over time using dynamic response measurements, the extraction of damage-sensitive features from these measurements, and the statistical analysis of these features to determine the current state of structural soundness. 
Our laboratory is aiming to develop efficient/labor-saving SHM systems for social infrastructures by automating a series of inspection and diagnostic actions through utilization of Artificial Intelligence techniques and IoT systems. The current activities include (1) vibration-based abnormality detection for mechanical system, (2) structural damage localization based on deep learning, (3) quantification based on image correlation for localized damage and (4) structural parameter identification based on data assimilation.
  • Damage localization by deep learning

  • Damage quantification by image correlation