A5007365314- Structural Health Monitoring Techniques
- Infrastructure Maintenance and Monitoring
- Concrete Corrosion and Durability
- Structural Engineering and Vibration Analysis
- Ultrasonics and Acoustic Wave Propagation
- Railway Engineering and Dynamics
- Structural Load-Bearing Analysis
- Non-Destructive Testing Techniques
- Structural Behavior of Reinforced Concrete
- Advanced Fiber Optic Sensors
- Fatigue and fracture mechanics
- Seismic Performance and Analysis
- Structural Response to Dynamic Loads
- Photonic and Optical Devices
- Mechanical stress and fatigue analysis
- Transport Systems and Technology
- Geotechnical Engineering and Underground Structures
- Transportation Safety and Impact Analysis
- Hydraulic and Pneumatic Systems
- Probabilistic and Robust Engineering Design
- Optical measurement and interference techniques
- 3D Surveying and Cultural Heritage
- Cultural Heritage Management and Preservation
- Concrete Properties and Behavior
- Dam Engineering and Safety
Queensland University of Technology
2015-2024
Beijing University of Chemical Technology
2019-2020
University of Helsinki
2020
The University of Queensland
1988-2020
Hong Kong Polytechnic University
2000-2009
Marymount University
2006
University Kebangsaan Malaysia Medical Centre
2006
Farnham Road Hospital
2006
Nanjing University of Aeronautics and Astronautics
2001
Structural damage detection using measured dynamic data for pattern recognition is a promising approach. These techniques utilize artificial neural networks and genetic algorithm to match features. In this study, an network–based method frequency response functions presented, which can effectively detect nonlinear damages given level of excitation. The main objective article present feasible structural vibration–based health monitoring, reduces the dimension initial function transforms it...
Compression index Cc is an essential parameter in geotechnical design for which the effectiveness of correlation still a challenge. This paper suggests novel modelling approach using machine learning (ML) technique. The performance five commonly used algorithms, i.e. back-propagation neural network (BPNN), extreme (ELM), support vector (SVM), random forest (RF) and evolutionary polynomial regression (EPR) predicting comprehensively investigated. A database with total number 311 datasets...
This paper addresses the problem of identifying a system forces from vehicle crossing guideway using only vibration responses caused by as input without knowledge characteristics. The is modeled single axle and two-axle loads with fixed spacing moving on simply supported beam viscous damping. equations motion are obtained through modal coordinate transformation, resulting set relating Fourier transforms converted into time domain new method proposed authors. Correctness identified checked...
This paper develops and applies a procedure for detecting damage in composite slab-on-girder bridge structure comprising of reinforced concrete slab three steel I beams, using vibration characteristics Artificial Neural Network (ANN). ANN is used conjunction with modal strain energy-based index locating quantifying the beams which are main load bearing elements bridge, while relative flexibility change to locate quantify deck. Research carried out dynamic computer simulations supported by...
Earlier impact studies on a small‐span bridge under service loads gave fractions much higher than, those specified by AASHTO. This paper represents the first stage of program to identify high‐impact vehicles. It describes theoretical that use measurements estimate not only equivalent static but also their dynamic variation with time. Acceptable estimates have been obtained. The measured bending moments gives better results than deflections. correct selection nodal spacing and arrangement is...