Chemical Engineering Journal, Journal Year: 2025, Volume and Issue: unknown, P. 164272 - 164272
Published: May 1, 2025
Language: Английский
Chemical Engineering Journal, Journal Year: 2025, Volume and Issue: unknown, P. 164272 - 164272
Published: May 1, 2025
Language: Английский
Small, Journal Year: 2025, Volume and Issue: unknown
Published: May 24, 2025
Abstract With the advancement of intelligent and refined manufacturing, demand for vibration sensors in smart equipment has surged. Traditional commercial triboelectric nanogenerator (TENG)‐based are limited to basic amplitude frequency recognition, failing address both self‐powering diagnostic needs due inherent design constraints. To overcome these limitations, this study introduces a novel mechanism combining interface dipole energy vacuum level optimization materials explain charge generation separation under vibration. A TENG device with polydimethylsiloxane (PDMS)‐encapsulated metal electrode is designed developed, enabling precise recognition operating status through waveform analysis. By optimizing contact area electron transfer capacity, achieves enhanced signal clarity introduction subtler characteristics waveform. Furthermore, integration deep learning algorithm enables high‐resolution classification states an accuracy 98.3% approximately, achieving effective monitoring jaw crusher vibrating screen. This work not only verifies feasibility designing self‐powered sensor but also demonstrates its potential real‐time applications equipment.
Language: Английский
Citations
0Chemical Engineering Journal, Journal Year: 2025, Volume and Issue: unknown, P. 164272 - 164272
Published: May 1, 2025
Language: Английский
Citations
0