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学者姓名：郭晓
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Abstract ：
Vibration signals from buildings are crucial for analysis, safety prediction, and early warnings. However, acquiring and analyzing these signals requires complex systems including sensor systems, storage devices, and computing equipment. All the part of the system rely on external power. This poses a challenge for buildings where the installation of complex equipment and power systems is inconvenient. This study proposes a self- powered, high-speed, and highly sensitive vibration detection system. It integrates a triboelectric nano- generator (TENG) and an organic field-effect synaptic transistor. A synaptic transistor with analog biomimetic synapse characteristics is proposed. The TENG and synaptic transistor's working principles and carrier transport characteristics are studied. Using TENG's output and the synaptic device's memory, the system detects and evaluates building vibration signals. The system's adaptability to one-dimensional signals allows for vibration classification and recognition using 1D-CNN, achieving 88.9% accuracy. This innovative strategy has broad prospects for solving vibration detection problems in special buildings and achieving lightweight, real-time, and intelligent monitoring.
Keyword ：
Building vibration identification System Building vibration identification System Self-powered Self-powered Synaptic transistor Synaptic transistor Triboelectric nanogenerator Triboelectric nanogenerator
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| GB/T 7714 | Guo, Xiao , Fan, Yuyang , Liu, Di et al. Vibration sensing system integrating triboelectric nanogenerator and synaptic transistor for self-powered building vibration identification [J]. | MEASUREMENT , 2025 , 249 . |
| MLA | Guo, Xiao et al. "Vibration sensing system integrating triboelectric nanogenerator and synaptic transistor for self-powered building vibration identification" . | MEASUREMENT 249 (2025) . |
| APA | Guo, Xiao , Fan, Yuyang , Liu, Di , Chen, Huipeng . Vibration sensing system integrating triboelectric nanogenerator and synaptic transistor for self-powered building vibration identification . | MEASUREMENT , 2025 , 249 . |
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