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首頁> 中文期刊> 《光譜學(xué)與光譜分析》 >基于等離激元增強(qiáng)拉曼光譜的便攜式快速檢測儀設(shè)計(jì)與實(shí)現(xiàn)

基于等離激元增強(qiáng)拉曼光譜的便攜式快速檢測儀設(shè)計(jì)與實(shí)現(xiàn)

     
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用于食品安全、環(huán)境污染、毒品、化學(xué)戰(zhàn)劑檢測等的現(xiàn)場快速檢測要求檢測設(shè)備便攜、快速和準(zhǔn)確.目前的常規(guī)實(shí)驗(yàn)室檢測方法雖然能夠?qū)崿F(xiàn)準(zhǔn)確檢測,但是其實(shí)時(shí)性較差,無法滿足現(xiàn)場快速檢測的要求.因此,設(shè)計(jì)開發(fā)了基于等離激元增強(qiáng)拉曼光譜的便攜式快速檢測儀,能夠?qū)崿F(xiàn)對濫用添加劑、違禁食品添加劑、農(nóng)藥殘余、毒品、化學(xué)戰(zhàn)劑和環(huán)境水污染等大量有害物質(zhì)的現(xiàn)場快速定性檢測.該檢測儀基于A RM嵌入式系統(tǒng)開發(fā),編寫了其操作交互界面和底層驅(qū)動程序,實(shí)現(xiàn)了拉曼光譜數(shù)據(jù)自動標(biāo)定和特征譜圖快速識別等算法.在儀器中搭建了檢測物質(zhì)拉曼光譜的標(biāo)譜數(shù)據(jù)庫,數(shù)據(jù)庫根據(jù)檢測科目進(jìn)行分類,每種科目包含該類別的多種物質(zhì),每種物質(zhì)均包含其高中低多種濃度的標(biāo)準(zhǔn)品和樣本譜圖.設(shè)計(jì)實(shí)現(xiàn)了大類科目的辨識比對算法和GPU硬件加速算法,實(shí)現(xiàn)了對某一類科目的所有物質(zhì)的快速比對,與傳統(tǒng)的純CPU算法實(shí)現(xiàn)相比較,在辨識速度上提高了20倍以上.通過市場購買的功能飲料、違規(guī)葡萄酒與果汁等實(shí)際樣品對所制備的樣機(jī)儀器進(jìn)行測試,測試結(jié)果符合預(yù)期,具有良好的靈敏度與重現(xiàn)性,滿足了現(xiàn)場快速檢測的要求.%The detection equipment for food safety ,environmental pollution ,drug safety ,chemical warfare agents requires port-able ,fast and accurate detection .The traditional laboratory test methods can meet accurate requirement ,but it is slow and cum-bersome .This paper proposes a portable and rapid detection equipment based on plasmon-enhanced Raman spectroscopy ,which can realize rapid qualitative and accuracy detection .The equipment system is based on ARM embedded architecture .The UI in-terface and drivers are finished and the algorithms of auto calibration of Raman spectroscopy data and characteristic spectra fast recognition is designed .The spectrum database of standard subjects is constructed in this local equipment ,which is classified ac-cording to the test required subject .The database includes a variety of substances in every subject ,which contains standard and sample spectrum of different concentration .The algorithms of multiple substances identification and GPU hardware acceleration are designed and presented in this paper ,which can detect mixed sample with more than twenty times faster then CPU soft calcu-late .A series of experiments are finished in the end to verify the algorithms and performance of the proposed equipment ,such as wine ,fruit juice and functional drinks getting from shop .The result meets the expectation with good sensitivity and reproduc-ibility .

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