A5037200592- Structural Health Monitoring Techniques
- Infrastructure Maintenance and Monitoring
- Ultrasonics and Acoustic Wave Propagation
- Seismic Performance and Analysis
- Structural Engineering and Vibration Analysis
- Non-Destructive Testing Techniques
- Optical measurement and interference techniques
- Concrete Corrosion and Durability
- 3D Surveying and Cultural Heritage
- Hydraulic and Pneumatic Systems
- Aquatic Ecosystems and Phytoplankton Dynamics
- Vibration Control and Rheological Fluids
- Robotic Path Planning Algorithms
- Cholinesterase and Neurodegenerative Diseases
- Probabilistic and Robust Engineering Design
- Supramolecular Self-Assembly in Materials
- Genetic diversity and population structure
- Advanced Polymer Synthesis and Characterization
- Extracellular vesicles in disease
- Seaweed-derived Bioactive Compounds
- Facial Nerve Paralysis Treatment and Research
- Constructed Wetlands for Wastewater Treatment
- Evolutionary Algorithms and Applications
- Electrodeposition and Electroless Coatings
- Protein Hydrolysis and Bioactive Peptides
Hong Kong Polytechnic University
2022-2025
Tongji University
2019-2023
Chinese Academy of Sciences
2022-2023
Fudan University
2023
Affiliated Hospital of Hebei University
2023
University of Chinese Academy of Sciences
2023
Institute of Hydrobiology
2023
East China Jiaotong University
2022
South China University of Technology
2022
Institute of Hydrobiology, Biology Centre, Academy of Sciences of the Czech Republic
2022
Images contain abundant valuable information about the health state of photographed infrastructures. However, local defects are mostly detected in vision-based structural monitoring (SHM), while global safety and risk at a larger scale rarely assessed. To fill up this gap, geometrical morphology-based image analysis framework is developed for assessment. A structured random forest edge detector adopted to extract edges an image, morphological operations subsequently used highlight skeleton,...
Structural health monitoring (SHM) systems evaluate the state of infrastructures by analyzing monitored responses. As measuring all target responses is difficult to accomplish due technical or economic limitations, converting other easy-measuring one a popular way. Relative approaches are separated into data-driven and model-driven ones. This paper proposes deep learning-based framework reconstruct multitypes full-field The adopted architecture convolutional neural network (CNN) with an...
Vibrio parahaemolyticus is the leading cause of seafood-borne bacterial poisoning in China and a threat to human health worldwide. The aim this study was assess antibiotic resistance profiles distribution heavy metal V. strains isolated Penaeus vannamei from freshwater farms, seawater farms their corresponding markets Zhejiang, relationship between multi drug (MDR) (MHMR). Of 360 P. samples that we tested, 90 (25.00%) were parahaemolyticus-positive, but occurrence pathogenic carrying toxic...
Abstract As civil infrastructures often exhibit nonlinearities, the identification of nonlinear behaviors is crucial to assess structural safety state. However, existing physics-driven methods can only estimate parameters given a known behavior pattern. By contrast, data-driven merely map load-response relationship at level, rather than identify an accurate mapping component level. To address these issues, hybrid physics-data-driven strategy developed in this study blind nonlinearity. The...
The digital twin (DT) technique for infrastructures has been developed and attracted a significant amount of attention since 2020. Nonetheless, the key technologies used DT, including load identification (LID), response reconstruction (RRE), damage detection, have much longer history than DT itself. By employing these methods, cyber models are established updated to represent operational state real structure, meanwhile, monitored data at discrete locations can be expanded full-field...
When monitoring structural data, incompleteness is a crucial issue that affects health (SHM). Information on displacement particularly important for bridge state estimation, but it difficult to measure. To obtain the required data at any position, hybrid (HM) algorithm combines finite-element model (FEM) with monitored proposed extend these from discrete points full structure. The aim of this study demonstrate accuracy and adaptiveness by adopting complex, large-scale considering modeling...
As a structural health monitoring (SHM) system can hardly measure all the needed responses, estimating target response from measured responses has become an important task. Deep neural networks (NNs) have strong nonlinear mapping ability, and they are widely used in reconstruction works. The relation among different is learned by NN given large training set. In some cases, however, especially for rare events such as earthquakes, it difficult to obtain dataset. This paper convolution...
Traditional damage identification (DI) approaches are based on the structural modal information, which is unstable and affected by environment. This study proposes a novel bridge DI algorithm for elastically supported beams with constant cross-section. The expression of equivalent load (EDL) deduced from force–displacement relationship. EDL only exists in damaged areas, it good indicator. Then, principal component analysis-based estimation method adopted to estimate external nodal force EDL....
For structural health monitoring, estimating the external load is a typical ill-posed problem but significant. Because with force and finite element model, any required response can be calculated, which advantageous for further monitoring works. This article first defines an underdetermined equation using limited number of in-field measurements model–calculated influence line matrix, it proposes estimation method Penrose–Moore pseudo-inverse (generalized inverse). The objective proposed to...
Abstract The polymerization of n ‐butyl acrylate in the presence two cyclic trithiocarbonates (CTTCs) and synthesis multiblock poly( acrylate) have been investigated. CTTCs not only can be stepwise incorporated into polymer chain via reversible addition–fragmentation transfer (RAFT) but also polymerized polytrithiocarbonate, which functions as a macro‐RAFT agent turn. Through kinds mechanisms, containing narrow‐polydispersity blocks prepared. © 2006 Wiley Periodicals, Inc. J Polym Sci Part...