【摘要】：近紅外光譜分析技術(shù)的廣泛應(yīng)用推動(dòng)了成品油性質(zhì)檢測(cè)技術(shù)的快速發(fā)展,建立一個(gè)預(yù)測(cè)精度高、可靠性高、穩(wěn)定性好的檢測(cè)模型是近紅外檢測(cè)技術(shù)的首要目標(biāo)。為實(shí)現(xiàn)這一目標(biāo),本文設(shè)計(jì)了基于近紅外光譜的成品油性質(zhì)檢測(cè)算法,針對(duì)模型的預(yù)測(cè)精度和結(jié)果可靠性問(wèn)題進(jìn)行深入研究。本文的第一章綜述了課題研究背景,以及成品油性質(zhì)檢測(cè)的研究現(xiàn)狀;第二章首先介紹偏最小二乘法的基本原理,給出了基于偏最小二乘法的成品油性質(zhì)檢測(cè)方法流程,主要包括采集近紅外光譜、選擇特征譜段、光譜預(yù)處理、選擇相似樣本、建立偏最小二乘模型、性質(zhì)預(yù)測(cè)和結(jié)果分析七個(gè)部分;最后對(duì)檢測(cè)過(guò)程中存在的問(wèn)題進(jìn)行分析。第三章設(shè)計(jì)了基于主成分分析以及性質(zhì)間相關(guān)性分析的校正集異常樣本剔除方法,分析異常樣本對(duì)模型預(yù)測(cè)精度的影響,介紹主成分分析的基本原理,給出校正集異常樣本剔除方法的詳細(xì)步驟,并以某煉化企業(yè)93#汽油研究法辛烷值的檢測(cè)為案例,對(duì)樣本的異常原因做出了詳細(xì)分析。第四章首先分析成品油性質(zhì)檢測(cè)精度的影響因素,包括溫度和噪聲干擾等;設(shè)計(jì)了基于光譜溫度修正的檢測(cè)精度提升方法,介紹基于分段直接標(biāo)準(zhǔn)化算法的光譜轉(zhuǎn)移函數(shù)構(gòu)造過(guò)程,以某煉化企業(yè)95#汽油研究法辛烷值的檢測(cè)為案例,給出詳盡分析;另外,設(shè)計(jì)了基于離散小波變換和快速傅里葉變換算法的檢測(cè)精度提升方法,介紹離散小波變換和快速傅里葉變換的基本原理,給出基于離散小波變換和快速傅里葉變換算法成品油性質(zhì)檢測(cè)方法的詳細(xì)步驟,并給出了某煉化企業(yè)95#汽油研究法辛烷值的檢測(cè)案例及分析。第五章設(shè)計(jì)了基于樣本分布集中度和模型預(yù)測(cè)能力的成品油性質(zhì)檢測(cè)結(jié)果可信度評(píng)價(jià)方法,介紹常用檢測(cè)模型的評(píng)價(jià)指標(biāo),給出成品油性質(zhì)檢測(cè)結(jié)果可信度評(píng)價(jià)方法的詳細(xì)步驟,并以某煉化企業(yè)95#汽油研究法辛烷值的檢測(cè)為案例,做出詳細(xì)分析。根據(jù)實(shí)驗(yàn)結(jié)果分析,本文設(shè)計(jì)的基于近紅外光譜的成品油性質(zhì)檢測(cè)算法,能夠滿(mǎn)足模型預(yù)測(cè)精度高、結(jié)果可靠性高的要求,為煉化企業(yè)提升了經(jīng)濟(jì)效益。
[Abstract]:The wide application of Near-infrared spectroscopy (NIR) technology has promoted the rapid development of oil quality detection technology. It is the primary goal of NIR detection technology to establish a detection model with high prediction accuracy, high reliability and good stability. In order to achieve this goal, an algorithm based on near infrared spectroscopy (NIR) is designed to detect the properties of oil products. The prediction accuracy and reliability of the model are studied in detail. The first chapter of this paper summarizes the research background of the subject, and the research status of oil quality testing. In the second chapter, the basic principle of partial least square method is introduced, and the method flow of oil quality detection based on partial least square method is presented, which mainly includes collecting near infrared spectrum, selecting characteristic spectrum, spectrum pretreatment, selecting similar samples. The partial least square model is established, the property prediction and the result analysis are seven parts. Finally, the existing problems in the detection process are analyzed. In the third chapter, we design a method of eliminating abnormal samples based on principal component analysis and property correlation analysis, analyze the influence of abnormal samples on the prediction accuracy of the model, and introduce the basic principle of principal component analysis. This paper gives the detailed steps of the method of eliminating abnormal samples in correction set, and takes the detection of octane number of gasoline research method of 93# in a refinery enterprise as an example, and makes a detailed analysis of the abnormal reason of the sample. In the fourth chapter, the factors affecting the precision of oil quality detection, including temperature and noise interference, are analyzed. The method of improving the detection precision based on spectral temperature correction is designed, and the construction process of spectral transfer function based on subsection direct standardization algorithm is introduced. Taking the detection of octane number of 9 gasoline research method in a refinery enterprise as an example, the detailed analysis is given. In addition, the detection accuracy enhancement method based on discrete wavelet transform and fast Fourier transform is designed, and the basic principles of discrete wavelet transform and fast Fourier transform are introduced. Based on discrete wavelet transform (DWT) and fast Fourier transform (FFT), this paper presents the detailed steps of testing the properties of refined oil products, and gives a case study and analysis of the octane number of 9 gasoline research method in a refinery enterprise. In chapter 5, the reliability evaluation method based on sample distribution concentration and model prediction ability is designed, and the evaluation indexes of common test models are introduced. The detailed steps of the reliability evaluation method for the testing results of the oil product properties are given, and taking the detection of the octane number of the 9 gasoline research method in a refinery enterprise as an example, the detailed analysis is made. According to the analysis of the experimental results, the proposed algorithm based on near infrared spectroscopy can meet the requirements of high prediction accuracy and high reliability of the model, and improve the economic benefit for the refinery and chemical enterprises.
【學(xué)位授予單位】：東南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：O657.33;TE622

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本文編號(hào)：2350084