The research group have proposed innovative Bayesian methodologies to tackle challenging inverse problems for establishing reliable Bayesian intelligent structural health monitoring framework. For operation and maintenance and real-time monitoring of electromechanical equipment, the group focus on the analysis and transmission of IoT based multi-source heterogeneous signals, the development of intelligent mobile monitoring platform, and multi-dimensional fault diagnosis techniques. For fire hazards, the group carry out research on the development of dynamic patrolling system and the establishment of fire prevention and control system. For safe construction and intelligent maintenance of underground infrastructures, the group aim to investigate the fundamental problems on constructing intelligent decision-making platforms which integrate multi-source heterogeneous data fusion with multi-scale model analysis, and thereby explore and establish the disaster risk assessment system for extreme conditions.
Structural health monitoring The main purpose of structural health monitoring for civil engineering structures is to utilize automation to detect damage and its severity at the possibly earliest stage so that evacuation or retrofitting can be conducted to minimize the casualties or economic loss. However, this is difficult to achieve due to larg [...]