近紅外檢測模型在乙醇生產(chǎn)中的開發(fā)及應用
發(fā)布時間:2019-03-22 12:39
【摘要】:由于天冠燃料乙醇有限公司生產(chǎn)工藝的獨特性,以及原料的復雜性,公司所使用的部分原料和生產(chǎn)的產(chǎn)品在市場上不通用,儀器生產(chǎn)廠家沒有開發(fā)相關的產(chǎn)品模型,特別是在木薯和谷朊粉產(chǎn)品等方面也沒有近紅外模型開發(fā)的報道。乙醇公司亟需一種方便、快捷的質量檢測方法來指導生產(chǎn)。本文采用化學法測定木薯、谷朊粉、DDGS酒糟飼料樣品的化學成分,然后利用DA7200近紅外測定儀采集樣品近紅外光譜,通過偏最小二乘法(PLS)、多元散射校正(MSC)和導數(shù)處理等光譜預處理方式建立了木薯、谷朊粉、DDGS酒糟飼料的快速檢測模型,并經(jīng)驗證模型均符合標準要求,完全可以應用于木薯、谷朊粉、DDGS酒糟飼料的日常檢測。經(jīng)過乙醇公司長期實際生產(chǎn)運行驗證,該方法快速、準確、清潔、高效、無損和低成本,符合要求乙醇長期連續(xù)生產(chǎn)對原料、中間產(chǎn)品,產(chǎn)成品檢測的要求,可以有效地指導生產(chǎn)調整工作,為乙醇生產(chǎn)的質量控制帶來有效的保障。
[Abstract]:Due to the uniqueness of the production process and the complexity of the raw materials, some of the raw materials used by the company and the products produced by the company are not commonly used in the market, and the instrument manufacturers have not developed the relevant product models. Especially in cassava and gluten products, there is no near infrared model development report. Ethanol companies need a convenient, fast quality inspection method to guide production. In this paper, the chemical composition of cassava, gluten and DDGS distillery grains was determined by chemical method. Then the near infrared spectra of the samples were collected by DA7200 near infrared detector, and the partial least square method (PLS),) was used to determine the chemical composition of the samples. The rapid detection models of cassava, gluten and DDGS distillery grains were established by spectral pretreatment with multiple scattering correction (MSC) and derivative treatment. The model was verified to meet the standard requirements and could be applied to cassava and gluten meal, and the model could be used in cassava and gluten meal, and could be used in cassava and gluten meal. Routine detection of DDGS distiller's grains feed. This method is fast, accurate, clean, efficient, nondestructive and low cost, and meets the requirements of long-term continuous production of ethanol for raw materials, intermediate products and finished products, which has been verified by the long-term practical operation of ethanol company. It can effectively guide the production adjustment and bring effective guarantee for the quality control of ethanol production.
【學位授予單位】:浙江大學
【學位級別】:碩士
【學位授予年份】:2017
【分類號】:TQ223.122;O657.33
本文編號:2445595
[Abstract]:Due to the uniqueness of the production process and the complexity of the raw materials, some of the raw materials used by the company and the products produced by the company are not commonly used in the market, and the instrument manufacturers have not developed the relevant product models. Especially in cassava and gluten products, there is no near infrared model development report. Ethanol companies need a convenient, fast quality inspection method to guide production. In this paper, the chemical composition of cassava, gluten and DDGS distillery grains was determined by chemical method. Then the near infrared spectra of the samples were collected by DA7200 near infrared detector, and the partial least square method (PLS),) was used to determine the chemical composition of the samples. The rapid detection models of cassava, gluten and DDGS distillery grains were established by spectral pretreatment with multiple scattering correction (MSC) and derivative treatment. The model was verified to meet the standard requirements and could be applied to cassava and gluten meal, and the model could be used in cassava and gluten meal, and could be used in cassava and gluten meal. Routine detection of DDGS distiller's grains feed. This method is fast, accurate, clean, efficient, nondestructive and low cost, and meets the requirements of long-term continuous production of ethanol for raw materials, intermediate products and finished products, which has been verified by the long-term practical operation of ethanol company. It can effectively guide the production adjustment and bring effective guarantee for the quality control of ethanol production.
【學位授予單位】:浙江大學
【學位級別】:碩士
【學位授予年份】:2017
【分類號】:TQ223.122;O657.33
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