使用垂直导热结构和基于传感器响应过程的神经网络预测算法的超快探测系统
Ruilin Yang1, Zhen Yuan1,2, Changrong Jiang1
1State Key Laboratory of Electronic Thin Films and Integrated Devices, School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu 610054, China.
ACS sensors
|March 11, 2025
概括
这项研究介绍了一种超快的探测系统,响应时间为0.4秒. 使用一种新的神经网络算法,它可以快速检测泄漏,从而提高能应用中的安全性.
科学领域:
- 材料科学 材料科学 材料科学
- 化学工程是化学工程的重要组成部分.
- 传感器技术 传感器技术
背景情况:
- 检测对于能应用中的安全至关重要,包括车辆,运输和储存.
- 现有的探测系统往往缺乏及时泄漏检测 (<1秒) 所需的超快响应时间.
研究的目的:
- 开发一个超快的探测系统,响应时间低于1秒.
- 使用先进的传感器和信号处理技术,提高泄漏检测的速度和效率.
主要方法:
- 开发了一种低功率 (20.2mW) 的传感器,采用了通过晶圆尺度工艺制造的垂直导热结构.
- 集成了一个信号处理电路与神经网络预测算法来分析传感器响应数据.
- 采用神经网络,使用初始传感器数据点预测度 (100 Hz采样频率的40个数据点).
主要成果:
- 实现了0.4秒的超快响应时间来检测气.
- 传感器展示了广泛的检测范围,广泛的操作温度耐受性,良好的长期稳定性和出色的选择性.
- 神经网络模型通过在传感器完全响应之前进行预测,显著加快了检测速度.
结论:
- 开发的系统为超快的探测提供了一种新的方法.
- 这项技术对低功率传感器和能能源领域的快速气体检测应用具有重大前景.
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