A5017943288- Innovative Energy Harvesting Technologies
- Advanced Sensor and Energy Harvesting Materials
- Vibration Control and Rheological Fluids
- Advanced Battery Technologies Research
- Structural Engineering and Vibration Analysis
- Advancements in Battery Materials
- Vibration and Dynamic Analysis
- Seismic Performance and Analysis
- Energy Harvesting in Wireless Networks
- Hydrogen embrittlement and corrosion behaviors in metals
- Wind Energy Research and Development
- Fluid Dynamics and Vibration Analysis
- Vehicle emissions and performance
- Structural Health Monitoring Techniques
- Fatigue and fracture mechanics
- Catalytic Processes in Materials Science
- Wireless Power Transfer Systems
- Conducting polymers and applications
- Machine Fault Diagnosis Techniques
- Advanced Combustion Engine Technologies
- Gear and Bearing Dynamics Analysis
- Electric Vehicles and Infrastructure
- Multiferroics and related materials
- Wave and Wind Energy Systems
- Non-Destructive Testing Techniques
Hunan Institute of Engineering
2016-2025
New York State Energy Research and Development Authority
2024
Xi'an Jiaotong University
2024
Xiangtan University
2011-2024
Nanchang Hangkong University
2024
Nanyang Medical College
2024
Nanjing University of Science and Technology
2023
Chinese Academy of Sciences
2001-2023
University of Science and Technology of China
2023
Civil Aviation University of China
2021
Abstract The Artificial Intelligence of Things (AIoT) connects everything with intelligence, while the increase in energy consumption generated by numerous electronic devices puts forward an impending demand on power supply. Energy harvesting technology has emerged as a compelling innovation for net zero emissions supply AIoT. Although significant advances have been witnessed harvesting, some issues such poor electrical output, weak environmental adaptability, and low reliability are...
Due to constantly varying wind speed, turbine (WT) components often operate at variable speeds in order capture more energy from wind. As a consequence, WT condition monitoring (CM) signals always contain intra‐wave features, which are difficult extract through performing conventional time–frequency analysis (TFA) because none of is locally adaptive. So far, only empirical mode decomposition (EMD) and its extension forms can features. However, the EMD those EMD‐based techniques also suffer...
Small-scale wind energy harvesting, which can replace batteries to power small electronic devices and realize self-powered systems, has been extensively studied. To improve the working wind-speed range output of small-scale generation we propose a synergetic hybrid piezoelectric triboelectric mechanism for galloping harvesting. In this mechanism, harvester (PEH) works in vibration area starts at low speeds, while nanogenerators work boundaries cooperate with PEH high speeds. The...