研究基于QNN-PID控制器的热电偶的时间常数测试
Chenyang Xu1,2, Xiaojian Hao1,2, Pan Pei1,2
1State Key Laboratory of Extreme Environment Optoelectronic Dynamic Measurement Technology and Instrument, North University of China, Taiyuan 030051, China.
Sensors (Basel, Switzerland)
|June 27, 2025
概括
这项研究引入了一种新的激光激发系统,用于精确的热电偶时间常数测试. 量子神经网络-PID控制器增强了实时激光功率调整,提高了快速热电偶的测试准确性和可重复性.
科学领域:
- 热电偶技术的热电偶技术
- 计量学 计量学 计量学
- 控制系统工程 控制系统工程
背景情况:
- 精确测量热电偶时间常数对于可靠的温度传感至关重要.
- 现有的激光激发方法在定量步骤信号采集方面面临挑战,影响测试的准确性和可重复性.
- 需要实时调整激光功率,以克服传统热电偶测试的局限性.
研究的目的:
- 开发一种改进的系统,使用激光激发测试热电偶时间常数.
- 为了提高热电偶时间常数测量的准确性和可重复性.
- 实现一个量子神经网络-PID控制器,用于精确的实时激光功率调整.
主要方法:
- 设计了一个热电偶时间常数测试系统,具有实时可调节的激光功率.
- 使用圆镜将色度温度计图像放在热电偶上,在联的焦点上.
- 实现了一个量子神经网络-PID控制器,以优化基于热电偶表面温度反的激光功率.
- 使用量子神经网络模拟和分析PID参数调整,与BP神经网络进行比较.
主要成果:
- 该系统实现了精确的实时激光功率调节,使稳定状态热电偶输出曲线成为可能.
- 量子神经网络-PID控制器表现出优于BP基于神经网络的优化.
- 经过测试的热电偶在各种温度 (800-1100°C) 中表现出150毫秒内的时间常数.
- 在1000°C的重复实验验证了系统的可行性和实验的可重复性.
结论:
- 开发的系统有效地测量了快速热电偶的时间常数,具有很高的准确性和可重复性.
- 量子神经网络-PID控制器显著提高了热电偶测试系统的性能.
- 这项研究为热电偶时间常数测试提供了可靠的方法,并有助于为各种应用选择热电偶.
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