AI-Driven and Multi-sensor Fusion Based structural Health Monitoring System.
This project aims to develop an innovative AI-driven microsystem for structural health monitoring (SHM), targeting strain measurement and other unhealthy condition detection for different structure systems such as high-altitude Balloons.
The proposed microsystem integrates multiple sensors, including flexible dual-mode strain sensors, temperature sensors, and piezoelectric elements for vibration detection, supported by a Jetson Orin Nano Developer edge computing device. Additionally, infrared thermal cameras detect temperature differences indicative of gas leakage. Machine learning algorithms optimize strain and temperature sensor data, ensuring accurate monitoring and error reduction.
In the summer, students will help design, fabricate, and test the sensing system using micro/nanotechnology. Students will also learn the skills of literature reviews, the knowledge of MEMS (Micro-Electro-Mechanical systems), lithographic process, testing method, and basic machine learning algorithms in this project.
Mentor:
Peng Cheng, Associate professor, Department of Applied Engineering Technology, Virginia State University. pcheng@vsu.edu
Yuan Ji, Assistant professor, Department of Applied Engineering Technology, Virginia State University. yji@vsu.edu.
