相干布局囚禁(Coherent Population Trapping,CPT)原子频标是一种功耗低、体积小、启动快的新型原子频标,温控系统是影响CPT原子频标稳定度指标的重要环节.本文介绍了通过优化设计实现CPT原子频标的高性能温控系统的方案.通过仪表放大...相干布局囚禁(Coherent Population Trapping,CPT)原子频标是一种功耗低、体积小、启动快的新型原子频标,温控系统是影响CPT原子频标稳定度指标的重要环节.本文介绍了通过优化设计实现CPT原子频标的高性能温控系统的方案.通过仪表放大器的应用提高了前端温度采集电路的温度分辨能力;通过小波分析算法对温度信号进行降噪处理;通过Δ-Σ算法实现脉冲宽度调制(Pulse Width Modulation,PWM),提高温控输出调节精度并减小谐波干扰.基于该方案实现了体积小、功耗低的温控电路,获得了较好的控温效果,改善了CPT原子频标频率稳定度指标.展开更多
In this letter, we present a novel approach of valve stiction detection using wavelet technology. A new non-invasive method is developed with the closed-loop normal operating data. The redundant dyadic discrete wavele...In this letter, we present a novel approach of valve stiction detection using wavelet technology. A new non-invasive method is developed with the closed-loop normal operating data. The redundant dyadic discrete wavelet transform is used to decompose the data at different resolution scales. Based on the Lipschitz regularity theory, wavelet coefficients analysis across scales is performed to detect the jumps in the controlled variables. Adaptive wavelet de-noising is then applied to the data. Features of the valve stiction patterns are extracted from the de-noised data and the valve stiction probability is calculated.展开更多
文摘相干布局囚禁(Coherent Population Trapping,CPT)原子频标是一种功耗低、体积小、启动快的新型原子频标,温控系统是影响CPT原子频标稳定度指标的重要环节.本文介绍了通过优化设计实现CPT原子频标的高性能温控系统的方案.通过仪表放大器的应用提高了前端温度采集电路的温度分辨能力;通过小波分析算法对温度信号进行降噪处理;通过Δ-Σ算法实现脉冲宽度调制(Pulse Width Modulation,PWM),提高温控输出调节精度并减小谐波干扰.基于该方案实现了体积小、功耗低的温控电路,获得了较好的控温效果,改善了CPT原子频标频率稳定度指标.
基金Supported by the National High-Tech Research and De-velopment Plan (863) of China (No.2006AA01Z232, No.2009AA01Z212, No.200901Z202)the Natural Science Foundation of Jiangsu Province (No. BK2007603)+2 种基金High-Tech Research Plan of Jiangsu Province (No.BG2007045)Research Climbing Project of NJUPT (No.NY2007044)Foundation of Nanjing University of Information Science and Technology(No.20070025)
文摘In this letter, we present a novel approach of valve stiction detection using wavelet technology. A new non-invasive method is developed with the closed-loop normal operating data. The redundant dyadic discrete wavelet transform is used to decompose the data at different resolution scales. Based on the Lipschitz regularity theory, wavelet coefficients analysis across scales is performed to detect the jumps in the controlled variables. Adaptive wavelet de-noising is then applied to the data. Features of the valve stiction patterns are extracted from the de-noised data and the valve stiction probability is calculated.
