共查询到17条相似文献,搜索用时 93 毫秒
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本文介绍了近红外光谱分析技术的特点以及该技术在石化领域的应用。以汽油调和为例,对在线近红外光谱分析技术在其中的应用前景进行了分析,在线近红外光谱分析技术可以实时测定汽油调和组分以及调和后的成品汽油的多种物化性质指标,如辛烷值、烯烃、芳烃、苯含量、馏程等,该技术的应用可为炼厂带来可观的经济效益和社会效益。 相似文献
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醚类和醇类化合物是目前汽油产品中常用的两类含氧添加剂.根据含氧添加剂的不同,可以对成品汽油进行分类.红外光谱是分析汽油中醚类和醇类化合物的有效手段,并能根据分析结果对汽油进行种类识别.本文提出采用介电谱技术对加有不同含氧化合物的汽油进行识别,获得了与红外光谱相一致的结果.研究表明,介电谱技术能够获得汽油不同组成、结构的信息,为汽油的快速分析测试提供了一种新的技术,也为应用介电谱技术预测不同组成特征汽油的质量指标奠定了基础. 相似文献
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目的 :研究烤烟香气风格中焦香、辛香、甜香等香韵的识别技术。方法:采用近红外光谱技术结合最小二乘支持向量机(LS-SVM)模式识别方法。烟叶粉末的近红外漫反射光谱经过波长范围选择和多种预处理优化后输入模型,使用k折交互验证和多层网格法优化LSSVM模型参数,建立三种香韵识别模型。结果:焦香、甜香、辛香的识别准确率CR分别为94.7%、88.9%、94.8%,ROC曲线下面积AUC分别为0.99、0.99、1.00。结论:说明使用近红外光谱技术结合LS-SVM方法可有效识别烤烟香气风格。 相似文献
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随着科学技术的快速发展,近红外光谱分析仪的应用越来越广泛:其非破坏待测物体的测量方法,倍受人柄关注。本论文主要研究开发基于近红外光谱技术的便携式快速分析仪器中单色光控制器。采用新型先进的分光技术—声光可调谐滤波器以及数字频率合成技术,设计出稳定、可靠、便携、方便的单色仪,为方便、快捷的近红外光谱分析仪提供有效的单色光源。 相似文献
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NIR汽油辛烷值测定仪中的支持向量机方法 总被引:1,自引:3,他引:1
提出了应用于近红外光谱汽油辛烷值测定仪的支持向量机方法 ,该方法具有强的泛化能力及全局最优解的特点 ,得到的数学模型其预测能力明显改善。实验表明该方法优越于目前在近红外光谱测定汽油辛烷值中常见的偏最小二乘和人工神经网络等方法 相似文献
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傅立叶变换近红外分析汽油辛烷值模型优化研究 总被引:2,自引:0,他引:2
利用傅立叶变换红外谱仪进行汽油样品辛烷值(RON)测定,采用仪器配备的软件进行模型优化,使用11种光谱预处理方法和不同的谱区组合,计算机自动处理优化过程并评价优化数据,50个汽油样品优化后得到最佳结果,光谱预处理方法为一阶导数,谱区范围为6100.4-4999.1cm^-1。得到的内部交互验证相关系数R2=99.05%和均方差RMSECV=0.167,优化后的结果说明,该方法完全能满足测试误差要求,从而为近红外模型优化提供参考。 相似文献
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近红外光谱分析技术快速测定油品的辛烷值 总被引:1,自引:0,他引:1
介绍了用近红外光谱(NIR)分析模型对催化汽油样品辛烷值进行快速测定的一种方法。实验结果证明:用NIR光谱分析技术的分析结果能够完全满足生产中的精度要求,近红外分析的结果与实验室常规分析结果之间的差别远优于GB的再现性要求。而且该方法除有测量速度快的优点之外,还具有分析成本低、无污染、操作简单方便等特点,在所建立的模型样品范围内,能对样品进行准确、经济的分析。 相似文献
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将近红外光谱测定汽油辛烷 值新技术用于炼厂控制分析,能显著节省分析时间和费用,及时和准确地为生产控制提供辛烷值数据,获得了良好的应用效果和经济效益。 相似文献
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Critical quality issues such as high porosity, cracks, and delamination are common in current selective laser melting (SLM) manufactured components. This study provides a flexible and integrated method for in situ process monitoring and melted state recognition during the SLM process, and it is useful for process optimization to decrease part quality issues. The part qualities are captured by images obtained from an off-axis setup with a near-infrared (NIR) camera. Plume and spatter signatures are closely related to the melted states and laser energy density, and they are employed for the SLM process monitoring in an adapted deep belief network (DBN) framework. The melted state recognition with the improved DBN and original NIR images requires little signal preprocessing, less parameter selection and feature extraction, obtaining the classification rate 83.40% for five melted states. Compared to the other methods of neural network (NN) and convolutional neural networks (CNN), the proposed DBN approach is identified to be accurate, convenient, and suitable for the SLM process monitoring and part quality recognition. 相似文献
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《Measurement》2016
In this research, an optical system based on fibre optic Vis/NIR spectroscopy combined with chemometrics methods and software as a graphical user interface (GUI) was developed and presented for fast and non-destructive detection and determination of pesticide residues in agricultural products (a case study on diazinon in intact cucumbers). Vis/NIR spectra of cucumber samples without and with different concentrations of diazinon residue were analyzed at the range of 450–1000 nm. Partial least squares (PLS) regression models were developed based on chemical reference measurements and the spectral information of the samples after performing different pre-processing methods. Moreover, partial least squares-discriminant analysis (PLS-DA) models were developed based on different spectral pre-processing techniques to classify cucumbers with contents of diazinon below and above the maximum residue limits (MRL) as safe and unsafe samples, respectively. Finally, user-friendly software as a GUI was created based on the best PLS and PLS-DA models developed for prediction of diazinon contents in the samples and for classification of intact cucumbers by the absence/presence of diazinon residues, respectively. Evaluation of the system and software designed based on the best developed PLS and PLS-DA models indicated good performance for measuring and detection of diazinon residue in cucumbers. It was concluded that the designed system and software based on Vis/NIR spectroscopy combined with chemometrics methods can be utilized for fast and non-destructive safety control of intact cucumbers by the absence/presence of diazinon residues. It can also be generalized for detection of other pesticide residues in agricultural products if developing their appropriate models is feasible. 相似文献