Non-contact Integrity Assessment of Façade Panels of High-rise Buildings. Disintegration of the external façade (with tiles, plates, etc.) of high-rise buildings presents a great challenge and a threat to community. This project develops fundamental knowledge and algorithms that underpin the deployment of a new technique for fast and automated quantitative integrity assessment of façade units of high-rise buildings, integrating mechanisms of directional acoustic waves, vibro-acoustics of façade ....Non-contact Integrity Assessment of Façade Panels of High-rise Buildings. Disintegration of the external façade (with tiles, plates, etc.) of high-rise buildings presents a great challenge and a threat to community. This project develops fundamental knowledge and algorithms that underpin the deployment of a new technique for fast and automated quantitative integrity assessment of façade units of high-rise buildings, integrating mechanisms of directional acoustic waves, vibro-acoustics of façade tiles or panels, laser sensing technology, deep learning algorithms and drone technology. Outcomes of this project are critical for implementing the new technology for enhanced safety to community and the development of new procedures for driving down maintenance costs of the external façade of high-rise buildings.Read moreRead less
AI Assisted Probabilistic Structural Health Monitoring with Uncertain Data. This project aims to develop an advanced Artificial Intelligence (AI) assisted probabilistic structural health monitoring approach for civil engineering structures. The developed approach applies novel deep learning techniques with a large amount of data measured from uncertain and complex environment, for reliable structural condition monitoring and performance prediction. This project expects to make a step change in d ....AI Assisted Probabilistic Structural Health Monitoring with Uncertain Data. This project aims to develop an advanced Artificial Intelligence (AI) assisted probabilistic structural health monitoring approach for civil engineering structures. The developed approach applies novel deep learning techniques with a large amount of data measured from uncertain and complex environment, for reliable structural condition monitoring and performance prediction. This project expects to make a step change in data mining and interpretation. Expected outcomes of the project include novel AI assisted approaches to conduct probabilistic structural condition monitoring with sensitive features and future structural performance prediction. This will provide significant benefits to infrastructure asset owners to reduce maintenance costs.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE220100909
Funder
Australian Research Council
Funding Amount
$350,000.00
Summary
Innovative Soft-computing for Condition Assessment of Large Infrastructure. Health conditions of large infrastructure, such as bridges, have been difficult to determine due to their large scales, associated incomplete data and high uncertainties in measurement and system identification. This project will develop an innovative condition assessment method based on the advancements in structural dynamics analysis, multi-objective topology and soft-computing techniques, for reliably evaluating the h ....Innovative Soft-computing for Condition Assessment of Large Infrastructure. Health conditions of large infrastructure, such as bridges, have been difficult to determine due to their large scales, associated incomplete data and high uncertainties in measurement and system identification. This project will develop an innovative condition assessment method based on the advancements in structural dynamics analysis, multi-objective topology and soft-computing techniques, for reliably evaluating the health conditions of large infrastructure. The outcomes will enhance the current practices in infrastructure asset management to deliver timely retrofitting and extended life cycle. The development will provide benefits to Australia by enhancing operational efficiency and preventing catastrophic failure of infrastructure.Read moreRead less