摘要
针对传统信号采集系统难以满足腔衰荡光谱(CRDS)信号精准采集的高采样率和高分辨率的需求,基于时间交织采样(TIADC)技术设计高采样率、高分辨率的采集模块,并提出一种基于二阶泰勒近似的两级差值(TDCST)算法来校正采集模块中的时序失配误差。对TIADC采集模块动态特性参数的仿真分析表明,TDCST算法可使信噪比达到73.94 dB,信噪失真比达到73.91 dB,无杂散失调达到96.60 dB,有效位数达到11.99 bit,且在奈奎斯特频率区间内均表现出显著的校准效果。进一步搭建基于CRDS技术的丙酮气体传感系统,将设计的采集模块集成至传感系统中进行实验验证。实验结果表明,相较于未校准和传统差值(DCA)校准算法,经TDCST算法处理后的数据与高精度示波器采集结果最为接近,皮尔逊相关系数均值为0.9977,CV值为0.04%。系统稳定性测试表明,其基线稳定性为0.30%。多次测量体积分数为10×10^(-6)的丙酮标准气体,测量结果均值为9.9865×10^(-6)。本研究不仅展示了CRDS技术在气体检测领域的潜力,还展示了基于TIADC设计的采集模块在CRDS系统中的应用价值。
Objective Cavity ring-down spectroscopy(CRDS)is a highly promising gas detection technology that offers superior sensitivity compared to conventional absorption spectroscopy methods.As a result,it has been widely applied in environmental monitoring,industrial process control,and biomedical research.However,CRDS signals are typically weak,exhibiting rapid attenuation and short decay time—often in the microsecond or nanosecond range.To enable rapid and accurate acquisition of these decay signals,the signal acquisition system must support high sampling rate and high resolution.Traditional signal acquisition systems often fail to simultaneously meet these stringent requirements,compromising data accuracy and reliability.Therefore,enhancing the performance of the acquisition system—particularly in terms of sampling speed and precision—is critical for advancing the practical utility of CRDS.This study presents a high-sampling-rate,high-resolution acquisition module based on time-interleaved analog-to-digital converter(TIADC)and introduces a simple yet precise algorithm to correct timing mismatch errors inherent in TIADC systems.The module is integrated into a custom-designed acetone gas sensing system to improve measurement accuracy and reliability.Methods This paper describes a signal acquisition module with a sampling rate of 500 MSa/s and 12 bit resolution,implemented using TIADC technology.To address timing mismatch errors common in conventional systems,we propose a novel two-stage salibration using second-order Taylor approximation(TDCST)algorithm.This algorithm employs a Taylor series expansion to approximate the signal and determines timing mismatch values through a two-stage differencing method,effectively correcting signal distortions caused by timing misalignment.A MATLAB model is developed to simulate the TIADC system,incorporating a 0.02-cycle timing mismatch error.Dynamic performance parameters are analyzed under uncalibrated,interpolation-calibrated,and TDCST-calibrated conditions to evaluate the effectiveness of the TDCST algorithm in improving key metrics:signal-to-noise ratio(SNR),signal-to-noise and distortion ratio(SNDR),spurious-free dynamic range(SFDR),and effective number of bits(ENOB).Finally,the acquisition system is integrated into a CRDS-based acetone sensing system,and its correlation with oscilloscope measurements,long-term stability,and accuracy in quantifying standard acetone gas are experimentally validated.Results and Discussions Simulation results show that introducing timing mismatch into the TIADC model generates harmonic components in the frequency spectrum,leading to a significant degradation in dynamic performance.After applying the DCA algorithm,harmonic components are reduced,resulting in improvements of 23.63 dB in SNR,23.35 dB in SNDR,23.63 dB in SFDR,and 3.92 bit in ENOB.With the TDCST algorithm,performance gains are substantially greater:SNR increased by 29.94 dB,SNDR by 29.91 dB,SFDR by 47.34 dB,and ENOB by 4.97 bit(Fig.8).Notably,calibration efficacy is pronounced across the Nyquist frequency range and becomes more effective at higher input frequencies(Fig.9),clearly surpassing the DCA algorithm.Experimental validation using the CRDS acetone sensing system demonstrates that data processed with the TDCST algorithm closely matches oscilloscope measurements(Fig.10),achieving a Pearson correlation coefficient of 0.9977 and a coefficient of variation(CV)of 0.04%(Fig.11).Repeated measurements of 10×10^(-6) standard acetone gas yields an average volume fraction of 9.9865×10^(-6)(Fig.14),confirming the module’s stability and measurement accuracy.Conclusions This study addresses the high-speed,high-resolution demands of CRDS gas sensing by developing a 500 MSa/s,12 bit acquisition module based on TIADC technology.The proposed TDCST calibration algorithm significantly enhances dynamic performance,with improvements of 29.94 dB in SNR,29.91 dB in SNDR,47.34 dB in SFDR,and 4.97 bit in ENOB,as demonstrated through simulation.Compared to the DCA algorithm,TDCST achieves superior calibration accuracy,particularly within the Nyquist frequency range.The study compares signal acquisitions from uncalibrated,DCA-calibrated,and TDCSTcalibrated modules against oscilloscope measurements,showing that TDCST-processed signals align closely with reference data(Pearson correlation coefficient r=0.9977,CV is 0.04%).Stability tests yields a system stability of S=0.30%,indicating robust performance.Background-subtracted measurements of 10×10^(-6) acetone standard gas result in a mean detection of 9.9865×10^(-6).These findings underscore the potential of CRDS in high-precision gas detection and highlight the value of the TIADC-based acquisition module.Furthermore,due to its versatility,the system can be applied to other high-speed signal acquisition domains,such as laser detection,vibration monitoring,and radar signal processing.Since the TDCST algorithm is scalable to TIADC systems with any number of channels,future work may explore parallel integration of additional ADCs to achieve even higher sampling rates and resolutions.
作者
徐凯
孙靖
葛明锋
李文轩
毕文昊
姜琛昱
石东鑫
Xu Kai;Sun Jing;Ge Mingfeng;Li Wenxuan;Bi Wenhao;Jiang Chenyu;Shi Dongxin(School of Electrical&Automation Engineering,Nanjing Normal University,Nanjing 210023,Jiangsu,China;Suzhou Institute of Biomedical Engineering and Technology,Chinese Academy of Sciences,Suzhou 215163,Jiangsu,China;School of Medical Information Engineering,Shandong University of Traditional Chinese Medicine,Jinan 250355,Shandong,China)
出处
《光学学报(网络版)》
2026年第4期37-46,共10页
Acta Optica Sinica(Online)
基金
国家重点研发计划(2022YFC2406204)
泰山产业领军人才工程(tscx202306125)
山东省重点研发计划(2023CXPT041,2024CXPT054)
山东省山东大学社会民生项目及青岛市科技惠民项目(25-1-5-smjk-5-nsh)。
关键词
腔衰荡光谱
时间交织采样
信号采集
气体检测
cavity ring-down spectroscopy
time-interleaved analog-to-digital converter
signal acquisition
gas sensing
