太赫兹时域光谱及其成像检测技术研究
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摘要
本文以常见的β兴奋剂、面粉添加剂和茶叶为研究对象,从THz光谱光学参数的计算方法、THz光谱信噪比分析、THz光谱吸收峰的来源解析、基于THz光谱的物质量化分析、基于THz光谱的物质分类识别、THz成像检测技术的原理与应用、基于压缩感知的THz成像技术等七个方面,系统的研究了THz时域光谱检测技术和THz时域光谱成像检测技术。本文的主要研究内容和创新点如下：
(1)获取了四种常用β兴奋剂(瘦肉精)的THz时域谱,计算获取了其在THz波段的吸收特性和折射率谱,为畜牧业瘦肉精和运动员非法β兴奋剂的检测提供了一种新途径。采用小波变换深入研究了THz时域光谱的信噪比。将离散小波多层分解和重构技术、小波变换的软阈值滤波和硬阈值滤波技术应用于THz时域光谱的噪声去除,提高了THz时域光谱的信噪比。采用固体密度泛函仿真的方法对物质的吸收峰来源进行了研究,并与分子密度泛函仿真方法相比较,结合理论计算与实验结果,对其振动来源进行了分析指认。
(2)深入研究了基于THz光谱的混合物量化回归分析,在计算获取过氧化苯甲酰和聚乙烯混合物、过氧化苯甲酰和面粉混合物THz吸收谱和折射率谱的基础上,使用小波滤波、一阶导数和二阶导数进行预处理,而后分别采用PLS和KPLS对原始吸收谱、一阶导数谱和二阶导数谱回归分析建模,并给出了详细性能评价。
(3)深入研究了基于THz光谱的物质分类和识别检测。在检测获取四种常见绿茶太赫兹光谱的基础上,分别采用LS-SVM, Naive-Bayes和BP-ANN建模,实现不同品种绿茶的分类识别。同时,采用粒子群算法和遗传算法优化了LS-SVM参数的求解,并对其实验结果进行了分析比较。采用VC软件开发了一套基于THz光谱的在线检测识别系统,在建立物质THz吸收谱数据库的基础上,采用主成分分析法实现了物质的在线识别检测。
(4)详细研究了THz时域光谱成像的原理和成像方法,研究不同物质的THz成像鉴别和基于THz时域光谱的物体三维成像检测技术。针对THz时域光谱成像技术高分辨率成像时会产生海量数据的问题,引入和研究了基于压缩感知的THz时域光谱技术和基于压缩感知的THz时域光谱成像技术。研究和测试了各类不同稀疏基和各类不同压缩感知重建算法在THz时域光谱和THz时域光谱成像中的应用和评价标准,分析了压缩感知前后信号的峰值信噪比、相对误差、匹配度和运行时间等性能。最后,研究了压缩感知在THz成像复原中的应用,实现了基于GPSR压缩感知方法的THz成像复原和噪声去除,并与维纳滤波和盲反卷积相比较,详细分析了其性能指标。
Based on the commonly β-stimulants, flour additives and green tea, the detection of THz-TDS was thoroughly studied. Calculation of optical parameters of THz time domain spectroscopy was researched, the signal to noise ratio analysis of THz spectroscopy, the absorption source of spectrum of THz time domain spectroscopy was detail analyzed. Identification of substances by THz-TDS was theory researched and realized. THz-TDS imaging technology was thoroughly researched and compressed sensing was applied in THz spectroscopy. The main research and innovation were as follows.
(1) The THz time-domain spectrums of four common β-stimulants were achieved, and then the absorption spectrums and refractive index spectrums of β-stimulants were calculated. This research provides a new approach for the detection of illegal using of P-stimulants in livestock and sports. The signal to noise ratio of the THz time domain spectroscopy was in-depth analyzed by Wavelet. Multi-layer decomposition and reconstruction of discrete wavelet, soft-threshold filtering and hard-threshold filtering of wavelet transform were applied respectively in THz time domain spectroscopy, and then the signal to noise ratio of the THz time domain spectroscopy was detail analyzed and improved. The solid density functional theory simulation and the molecular density functional theory simulation were applied respectively for explaining the source of the absorption peak in absorption spectrum. The vibration source were identified by theory calculated results and experiment results.
(2)Based on the THz absorption spectra and refractive index spectrum of benzoyl peroxide and polyethylene mixture, benzoyl peroxide and flour mixture, regression analysis was applied. Wavelet filter, the first derivative and second-order derivative was applied in pretreatment. Wavelet filter, the first derivative and second-order derivative was applied in pretreatment of THz spectra. Regression analysis was carried out by algorithms of PLS and KPLS, and then the performance of the model were evaluated.
(3) Multi-class classification and regression analysis based on THz spectroscopy was in-depth studied. Terahertz time-domain spectroscopy have been applied in research of four different varieties of chinese green tea, the absorption and refractive Terahertz Spectrum of these tea were got. Least Squares Support Vector Machines, Naive Bayes and Back Propagation Artificial Neural Network were applied to achieve Multi-class classification of these four kinds of tea, and the classification results of three algorithms were analyzed in detail. The PC control platform of THz-TDS system was developed by Visual C++. Based on the database of THz spectroscopy and principal component analysis algorithm, recognition functions were realized.
(4) Simulation and experiment of THz-TDS imaging were carried out. Various THz imaging methods was tested, identify of different substances by THz imaging was achieved and3D imaging of THz time domain spectroscopy was realized. The application of compressed sensing in the THz time-domain spectroscopy and THz time domain spectroscopy imaging technology were researched. Based on the characteristics of the THz time domain spectroscopy and THz time domain spectroscopy imaging technology, various types of sparse base and various kinds of compressed sensing reconstruction algorithm were tested. Finally, signal to noise ratio of the spectra reconstructed by compressed sensing algorithms, the relative error, matching degrees and efficiency were evaluated. The application of compressed sensing in THz image deconvolution was researched. THz image deconvolution and noise removal were realized by GPSR compressed sensing algorithm, compared with the Wiener filtering and blind deconvolution, detailed analysis of its performance was carried out.
(1)获取了四种常用β兴奋剂(瘦肉精)的THz时域谱,计算获取了其在THz波段的吸收特性和折射率谱,为畜牧业瘦肉精和运动员非法β兴奋剂的检测提供了一种新途径。采用小波变换深入研究了THz时域光谱的信噪比。将离散小波多层分解和重构技术、小波变换的软阈值滤波和硬阈值滤波技术应用于THz时域光谱的噪声去除,提高了THz时域光谱的信噪比。采用固体密度泛函仿真的方法对物质的吸收峰来源进行了研究,并与分子密度泛函仿真方法相比较,结合理论计算与实验结果,对其振动来源进行了分析指认。
(2)深入研究了基于THz光谱的混合物量化回归分析,在计算获取过氧化苯甲酰和聚乙烯混合物、过氧化苯甲酰和面粉混合物THz吸收谱和折射率谱的基础上,使用小波滤波、一阶导数和二阶导数进行预处理,而后分别采用PLS和KPLS对原始吸收谱、一阶导数谱和二阶导数谱回归分析建模,并给出了详细性能评价。
(3)深入研究了基于THz光谱的物质分类和识别检测。在检测获取四种常见绿茶太赫兹光谱的基础上,分别采用LS-SVM, Naive-Bayes和BP-ANN建模,实现不同品种绿茶的分类识别。同时,采用粒子群算法和遗传算法优化了LS-SVM参数的求解,并对其实验结果进行了分析比较。采用VC软件开发了一套基于THz光谱的在线检测识别系统,在建立物质THz吸收谱数据库的基础上,采用主成分分析法实现了物质的在线识别检测。
(4)详细研究了THz时域光谱成像的原理和成像方法,研究不同物质的THz成像鉴别和基于THz时域光谱的物体三维成像检测技术。针对THz时域光谱成像技术高分辨率成像时会产生海量数据的问题,引入和研究了基于压缩感知的THz时域光谱技术和基于压缩感知的THz时域光谱成像技术。研究和测试了各类不同稀疏基和各类不同压缩感知重建算法在THz时域光谱和THz时域光谱成像中的应用和评价标准,分析了压缩感知前后信号的峰值信噪比、相对误差、匹配度和运行时间等性能。最后,研究了压缩感知在THz成像复原中的应用,实现了基于GPSR压缩感知方法的THz成像复原和噪声去除,并与维纳滤波和盲反卷积相比较,详细分析了其性能指标。
Based on the commonly β-stimulants, flour additives and green tea, the detection of THz-TDS was thoroughly studied. Calculation of optical parameters of THz time domain spectroscopy was researched, the signal to noise ratio analysis of THz spectroscopy, the absorption source of spectrum of THz time domain spectroscopy was detail analyzed. Identification of substances by THz-TDS was theory researched and realized. THz-TDS imaging technology was thoroughly researched and compressed sensing was applied in THz spectroscopy. The main research and innovation were as follows.
(1) The THz time-domain spectrums of four common β-stimulants were achieved, and then the absorption spectrums and refractive index spectrums of β-stimulants were calculated. This research provides a new approach for the detection of illegal using of P-stimulants in livestock and sports. The signal to noise ratio of the THz time domain spectroscopy was in-depth analyzed by Wavelet. Multi-layer decomposition and reconstruction of discrete wavelet, soft-threshold filtering and hard-threshold filtering of wavelet transform were applied respectively in THz time domain spectroscopy, and then the signal to noise ratio of the THz time domain spectroscopy was detail analyzed and improved. The solid density functional theory simulation and the molecular density functional theory simulation were applied respectively for explaining the source of the absorption peak in absorption spectrum. The vibration source were identified by theory calculated results and experiment results.
(2)Based on the THz absorption spectra and refractive index spectrum of benzoyl peroxide and polyethylene mixture, benzoyl peroxide and flour mixture, regression analysis was applied. Wavelet filter, the first derivative and second-order derivative was applied in pretreatment. Wavelet filter, the first derivative and second-order derivative was applied in pretreatment of THz spectra. Regression analysis was carried out by algorithms of PLS and KPLS, and then the performance of the model were evaluated.
(3) Multi-class classification and regression analysis based on THz spectroscopy was in-depth studied. Terahertz time-domain spectroscopy have been applied in research of four different varieties of chinese green tea, the absorption and refractive Terahertz Spectrum of these tea were got. Least Squares Support Vector Machines, Naive Bayes and Back Propagation Artificial Neural Network were applied to achieve Multi-class classification of these four kinds of tea, and the classification results of three algorithms were analyzed in detail. The PC control platform of THz-TDS system was developed by Visual C++. Based on the database of THz spectroscopy and principal component analysis algorithm, recognition functions were realized.
(4) Simulation and experiment of THz-TDS imaging were carried out. Various THz imaging methods was tested, identify of different substances by THz imaging was achieved and3D imaging of THz time domain spectroscopy was realized. The application of compressed sensing in the THz time-domain spectroscopy and THz time domain spectroscopy imaging technology were researched. Based on the characteristics of the THz time domain spectroscopy and THz time domain spectroscopy imaging technology, various types of sparse base and various kinds of compressed sensing reconstruction algorithm were tested. Finally, signal to noise ratio of the spectra reconstructed by compressed sensing algorithms, the relative error, matching degrees and efficiency were evaluated. The application of compressed sensing in THz image deconvolution was researched. THz image deconvolution and noise removal were realized by GPSR compressed sensing algorithm, compared with the Wiener filtering and blind deconvolution, detailed analysis of its performance was carried out.
引文
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