JP4026794B2

JP4026794B2 - Analysis method of physical properties of hydrocarbons by near infrared spectroscopy

Info

Publication number: JP4026794B2
Application number: JP24961398A
Authority: JP
Inventors: 潔池田
Original assignee: Petroleum Energy Center PEC; Idemitsu Kosan Co Ltd
Current assignee: Idemitsu Kosan Co Ltd; Japan Petroleum Energy Center JPEC
Priority date: 1998-09-03
Filing date: 1998-09-03
Publication date: 2007-12-26
Anticipated expiration: 2018-09-03
Also published as: JP2000074828A

Description

【０００１】
【発明の属する技術分野】
本発明はガソリン等の製品およびガソリン基材等の原料で代表される炭化水素類の物性値、例えばオクタン価、密度、蒸気圧等を近赤外分析法によって分析する方法に関する。
【０００２】
【従来の技術】
近赤外分光法による物性値分析は、標準試料群の基準物性値とそれらの近赤外スペクトルにおける吸収値あるいはその数学的変換値との関係に基づいて作成される物性推算式（物性値検量線）を用いて行われるので、未知分析試料が上記標準試料群と組成・構造範囲を異にする場合には、作成した物性推算式（物性値検量線）の適用範囲外となり、得られる分析値が実際と大きくずれる結果となる。
他方、近年ガソリン等の製品およびそれに用いられるガソリン基材等の原料は多種多様となり、かつ物性値に対する要求精度も高まっている。この為、近赤外分光法における物性推算式（物性値検量線）の実用範囲は狭いものとなり、未知分析試料が適用範囲外のものとなる可能性が高まっている。
【０００３】
また、未知分析試料が予め作成した近赤外分光法による物性推算式（物性値検量線）の適用範囲に含まれるか否かの判断をする手段がなく、得られた分析値が正しいか否かの判断が不可能である。従って、未知分析試料が作成した物性推算式（物性値検量線）の適用範囲に含まれるか否かの判断をする手段が望まれている。
【０００４】
また、基本となる物性値推算式（物性値検量線）の適用範囲を拡大すべく、標準試料群と組成・構造範囲を異にする試料のデータを必要に応じて後から追加することにより物性値推算式（物性値検量線）の修正を行おうとすると、結果的に修正前の物性推算式（物性値検量線）に比べて推算精度が低下するという問題点が生じる。
従って、基本となる物性値推算式（物性値検量線）の精度低下をまねくことなく、標準試料群と組成・構造範囲を異にする試料についても精度よく物性値を推算する方法が望まれている。
【０００５】
【発明が解決しようとする課題】
本発明は、近赤外スペクトル法によるガソリン等の燃料油およびその基材の物性値分析における、物性推算式（物性値検量線）の適用範囲の適否判断および適用範囲の拡大または分析精度の向上を可能とする、炭化水素の物性値の分析方法を提供することにある。
【０００６】
【課題を解決するための手段】
燃料油（ガソリン、軽油、重油等）等の分析試料の近赤外スペクトルにおける吸収値あるいはその数学的変換値から当該燃料油等の物性値（オクタン価、密度、蒸気圧等）を算出する物性推算式（物性値検量線）を用いる分析法において、予め上記物性推算式（物性値検量線）の適用範囲を水素種（芳香族水素、オレフィン水素、ベンジル位水素、メチン水素、メチレン水素、メチル水素等）別にその含有割合について設定し、未知分析試料についての近赤外スペクトルにおける吸収値あるいはその数学的変換値から各水素種別含有割合を算出するために予め作成された水素種別含有割合推算式（水素分布検量線）を用いて得られる水素種別含有割合分析値と、上に設定された水素種別の含有割合としての適用範囲とを比較して、上記物性値推算式（物性値検量線）の適用範囲内外を判別し、上記判別の結果が上記適用範囲内である場合には上記物性値推算式（物性値検量線）を用いて物性値を算出し、また上記判別の結果が上記適用範囲外である場合には上記物性値推算式（物性値検量線）と下記物性値補正式とを用いて物性値を算出する。
【０００７】
物性値補正式
補正物性値
＝物性値推算値（要補正物性値推算値）＋水素種別含有割合による物性値補正値（補正項値）
水素種別含有割合による物性値補正値（補正項値）
＝Σ（各水素種別含有割合×各水素種含有割合と物性値補正値の回帰係数）＋定数項
即ち、上記判別の結果が上記適用範囲（水素種別含有割合範囲として予め設定される）外の場合には、上記物性値推算式（物性値検量線）によって導かられる未補正の「物性値推算値」を第１次の物性値推算値とし、これに「水素種別割合による物性値補正値（第１次の物性値の補正項値である）」を加算（代数的加算）して目的とする「補正物性値（上記の補正項によって補正された物性値である）」を得るようにする。
【０００８】
以上のように分析試料の近赤外スペクトルの測定結果から水素種別含有割合を分析することにより未知分析試料があらかじめ作成しておいた物性値推算式（物性値検量線）が前提とした組成・構造範囲に属するか否かを判別し、上記物性値推算式（物性値検量線）の適用範囲であるか否かの判別が可能となる。また、上記物性値補正式を用いることにより、物性値推算式の適用範囲が拡大され、また精度の向上がなされる。
【０００９】
よって本発明の近赤外スペクトル法による炭化水素の物性値の分析方法においては、以下のステップが設けられる：
（Ａ）物性値推算式あるいは検量線を用意するステップ；
（Ｂ）水素種別含有割合推算式あるいは検量線を用意するステップ；
（Ｃ）上記物性値推算式あるいは検量線の適用範囲を示す水素種別含有割合あるいはその推算値を適用範囲として設定するステップ；
（Ｄ）上記適用範囲外の標準とする試料について、基準物性値と上記物性値推算式あるいは検量線によって得られる推定値との間の誤差値と水素種別含有割合とを統計学的に処理して得られる誤差値推算式あるいは検量線を物性値補正値（補正項値）推算式あるいは検量線として用意するステップ；
（Ｅ）未知試料の近赤外スペクトルを測定し、得られた近赤外スペクトル吸収値あるいはその数学的変換値及び上記水素種別含有割合推算式あるいは検量線を用いて水素種別含有割合を推算し、得られた推算結果と上記適用範囲とを比較して、上記適用範囲の内外について判別するステップ；
（Ｆ）上記判別によって上記適用範囲内と判別された場合に、上記物性値推算式あるいは検量線によって目的とする物性値を推算するステップ；及び
（Ｇ）上記判別によって上記適用範囲外と判別された場合に、上記物性値推算式あるいは検量線により要補正物性値を推算し；
また、上記物性値補正値（補正項値）推算式あるいは検量線により物性値補正値（補正項値）を推算し；
次いで上記要補正物性値（要補正物性値推算値）と上記物性値補正値（補正項値）の代数和として目的とする補正された物性値を推算するステップ。
【００１０】
以上のようなステップを設けることによって、上記適用範囲内の未知試料についての分析精度をより高くし、上記適用範囲外の未知試料についての分析精度も上記物性値補正値（補正項値）の採用によってより高くし、また結果的に実用的分析可能範囲を拡大する。
【００１１】
【発明の実施の形態】
本発明による具体化された近赤外スペクトル法による炭化水素の物性値の分析方法においては、上記分析方法が、以下のステップを含むものである。
（Ａ）標準とする試料について、基準とする分析方法によって得られる基準物性値と、近赤外スペクトル吸収値あるいはその数学的変換値とを多変量解析手法（例えば部分二乗回帰分析法）で処理して物性値推算式あるいは検量線を用意するステップ；
（Ｂ）標準とする試料について基準とする分析法によって得られる水素種別含有割合と、近赤外スペクトル吸収値あるいはその数学的変換値とを多変量解析手法（例えば部分二乗回帰分析法）で処理して水素種別含有割合推算式乃至検量線を用意するステップ；
（Ｃ）上記ステップＡにおいて標準とする試料について、水素種別含有割合あるいは上記ステップＢの水素種別含有割合推算式あるいは検量線による水素種別含有割合推算値を、上記ステップＡの物性値推算式あるいは検量線の適用範囲として設定するステップ；
（Ｄ）水素種別含有割合が上記ステップＣの適用範囲外である標準とする試料についての、水素種別含有割合と基準物性値と物性値推算結果との誤差を多変量解析手法（例えば部分二乗回帰分析法）で処理して物性値補正値（補正項値）推算式あるいは検量線を用意するステップ；
（Ｅ）未知試料についての近赤外スペクトルを測定し、得られた近赤外スペクトル吸収値あるいはその数学的変換値及び上記ステップＢの水素種別含有割合推算式あるいは検量線を用いて水素種別含有割合を推算し、得られた推算結果と上記ステップＣの適用範囲とを比較して、上記適用範囲の内外について判別するステップ；
（Ｆ）上記ステップＥにおいて、上記適用範囲内と判別された場合に、上記未知試料についての近赤外スペクトル吸収値あるいはその数学的変換値及び上記ステップＡの物性値推算式あるいは検量線を用いて目的とする物性値を推算するステップ；
（Ｇ）上記ステップＥにおいて、上記適用範囲外と判別された場合に、上記未知試料についての近赤外スペクトル吸収値あるいはその数学的変換値と上記ステップＡの物性値推算式を用いて要補正物性値を推算し；
また、上記未知試料の上記水素種別含有割合及び上記ステップＤの物性値補正値（補正項値）推算式あるいは検量線を用いて物性値補正値（補正項値）を推算し；
次いで上記要補正物性値と上記物性値補正値（補正項値）の代数和として目的とする補正された物性値を推算するステップを含む近赤外スペクトル法による炭化水素の物性値の分析方法。
【００１２】
【実施例】
（１）水素種別含有割合推算式（水素分布検量線）の作成と評価
（１−ａ）分析試料の調整
種々のガソリン基材（直留系、分解系、改質系、アルキレート系等）、ガソリン製品を任意の広範囲な割合で混合して水素分布検量線作成試料３０種および検量線評価試料２０種を作成した。
【００１３】
（１−ｂ）水素種別含有割合の基準値の測定
作成した水素分布検量線作成試料（３０種）および検量線評価試料（２０種）について、それぞれ水素核磁気共鳴法（１Ｈ−ＮＭＲ法）によって芳香族水素、オレフィン水素、ベンジル位水素、メチン水素、メチレン水素、メチル水素を吸収位置および積分比に基づいて定量し、水素種別含有割合の実測値を得た。
【００１４】
ＮＭＲ測定条件
装置：９０ＭＨｚ−ＦＴＮＭＲ（日立Ｒ１９００）
試料：試料１０Ｖｏｌ％ｉｎ重クロロホルム、ＴＭＳ０．０３％入り
測定条件：３５℃、３２回積算
図１に水素核磁気共鳴法（１Ｈ−ＮＭＲ法）の測定結果の例を示す。
表１に各水素種の分類および上記検量線作成試料の各水素種含有割合の範囲を示す。
【００１５】
【表１】

（１−ｃ）水素種別含有割合推算式（水素分布検量線）の作成と評価
上記水素分布検量線作成試料（３０種）および検量線評価試料（２０種）について近赤外スペクトルを測定した。標準検量線作成試料群について水素種別含有割合実測値との相関を多変量解析手法を用いて解析して水素種別含有割合推算式（水素分布検量線）を作成した。このときの多重相関係数および推算式の標準誤差を表２に示す。
【００１６】
検量線評価試料について、上記で作成した水素種別含有割合推算式（水素分布検量線）を用いて水素種別含有割合を算出し、水素種別含有割合実測値と比較した。予測値の誤差を表２に示す。また、図２および図３に芳香族水素およびメチル水素についてＮＭＲによる実測値と、近赤外スペクトルからの推算値との相関を示す。
いづれの水素種についても含有割合の推算値と実測値は優れた相関を示すことが判明した。
【００１７】
近赤外スペクトル測定条件
装置：回折格子式（ＵＯＰ-Ｇuided Ｗave ＩnＳite ＩＶ）
波長範囲：１０００〜２１００ｎｍ、１ｎｍ毎、２０１点
セル：１ｃｍギャップ、プローブ式
温度：１５℃
スペクトル処理
ベースライン位置補正、スムージング
統計解析
手法：ＰＬＳ（部分二乗回帰分析）
波長：１１００〜１５００ｎｍ、２ｎｍ毎
【表２】

（２）物性値推算式（物性値検量線）の作成
（２−ａ）分析試料の調整
通常生産されるガソリン製品の基材構成および混合割合を超えない範囲で各種基材（直留系、分解系、改質系、アルキレート系等）を混合し、物性値検量線作成試料５０種および検量線評価試料２０種を作成した。
（２−ｂ）ＲＯＮ、ＤＥＮＳおよびＲＶＰの基準値の測定
作成した物性値検量線作成試料（５０種）および検量線評価試料（２０種）について、それぞれ目的とする物性値であるリサーチオクタン価（ＲＯＮ）、密度（ＤＥＮＳ）およびリード法蒸気圧（ＲＶＰ）をＪＩＳ試験法に従って測定し、表３に示される範囲の各物性値の実測値を得た。
【００１８】
【表３】

（２−ｃ）物性値推算式（物性値検量線）の作成
上記物性値検量線作成試料（５０種）および検量線評価試料（２０種）について近赤外スペクトルを測定した。物性値検量線作成試料群についてリサーチオクタン価（ＲＯＮ）、密度（ＤＥＮＳ）およびリード法蒸気圧（ＲＶＰ）の実測値との相関を多変量解析手法を用いて解析し、物性値推算式（水素分布検量線）を作成した。このときの多重相関係数および推算式の標準誤差を表４に示す。
【００１９】
検量線評価試料について、上記で作成した物性値推算式（物性値検量線）を用いて各物性値を算出し、各物性値の実測値と比較した。予測値の誤差を表４に示す。
いづれの物性値についても含有割合の予測値と実測値は優れた相関を示すことが判明した。
【００２０】
近赤外スペクトル測定条件
装置：回折格子式（ＵＯＰ-Ｇuided Ｗave ＩnＳite ＩＶ）
波長範囲：１０００〜２１００ｎｍ、１ｎｍ毎
セル：１ｃｍギャップ、プローブ式
温度：１５℃
スペクトル処理
ベースライン位置補正、スムージング
統計解析
手法：ＰＬＳ（部分二乗回帰分析）
波長：１１００〜１５００ｎｍ、２ｎｍ、２０１点
【表４】

（２−ｄ）物性値推算式（物性値検量線）の適用範囲の設定
物性値検量線作成試料について、（１−ｃ）で作成した水素種別含有割合推算式（水素分布検量線）を用いて水素種別含有割合を算出し、算出した含有量の範囲から上記物性値推算式の適用範囲を決定した。結果を表５に示す。
【００２１】
【表５】

（３）水素種別含有割合による物性値補正式の作成
（３−ａ）分析試料の調整
通常生産されるガソリン製品の基材構成および混合割合より広い範囲で各種基材（直留系、分解系、改質系、アルキレート系等）を混合し、物性値補正式作成用試料約３０種を作成した。
（３−ｂ）ＲＯＮ、ＤＥＮＳおよびＲＶＰの基準値の測定並びに水素種別割合の測定
作成した物性値補正式作成用試料について、それぞれ目的とする物性値であるリサーチオクタン価（ＲＯＮ）、密度（ＤＥＮＳ）およびリード法蒸気圧（ＲＶＰ）をＪＩＳ試験法に従って測定し、各物性値の実測値を得た。また、上記（１−ｃ）で作成した水素種別含有割合推算式（水素分布検量線）を用いて水素種別含有割合を算出した。結果を表６に示す。水素種含有割合が物性値検量線作成試料にくらべ広範囲にわたっていることがわかる。
【００２２】
【表６】

（３−ｃ）物性値検量線による推算値の推算誤差の算出
上記（３−ａ）で作成した物性値補正式作成試料（３０種）について近赤外スペクトルを測定し、上記（２−ｃ）で作成した物性値推算式（物性値検量線）を用いてリサーチオクタン価（ＲＯＮ）、密度（ＤＥＮＳ）およびリード法蒸気圧（ＲＶＰ）を推算した。得られた積算値と上記（３−ｂ）で測定した物性値の実測値との差を推算誤差とした。物性値推算式作成試料と組成・構造が異なるため、推算誤差が大きいことがわかる。
【００２３】
（３−ｄ）水素種別含有割合による物性値補正値（補正項値）推算式の作成
（３−ｂ）で推算した各水素種別含有割合と、上記（２−ｄ）で定めた物性値推算式（物性値検量線）の適用範囲とを比較し、適用範囲外にある試料を選別した。選別した試料について、（３−ｃ）で算出した各物性値の推算誤差と、（３−ｂ）で推算した各水素種別含有割合との関係を多変量解析手法ＰＬＳ（部分二乗回帰分析）を用いて解析し、物性値推算式（物性値検量線）の推算誤差即ち補正項値を予測する回帰式を作成した。
【００２４】
水素種別含有割合による物性値補正値（補正項値）
＝Σ（各水素種別含有割合×各水素種含有割合と物性値補正値との回帰係数）＋定数項
各水素種含有割合に対する回帰係数及び定数項を表７に示す。
【００２５】
【表７】

得られた回帰式によって次式に示すように物性値の推算値に補正を加えた。
補正物性値
＝物性値推算値＋水素種別含有割合による物性値補正値（補正項値）
補正前後での物性値の推算値と実測値との相関および推算誤差を図４、図５および図６ならびに表８に示す。
【００２６】
【表８】

リサーチオクタン価（ＲＯＮ）、密度（ＤＥＮＳ）およびリード法蒸気圧（ＲＶＰ）いづれも上記補正式を用いることによって推算誤差が減少できることが示された。
【００２７】
（４）市販ガソリン試料による検証
市販ガソリン試料数種を用いて本手法によってオクタン価（ＲＯＮ）の推算を行い、実測値との比較を行った。結果を表９に示す。本手法により、未知試料が物性値検量線の適用範囲内であるか否かを判断し、適用範囲外の試料については補正式を用いることにより推算誤差を減少することが示されれた。
【００２８】
【表９】

【００２９】
【発明の効果】
近赤外分光法による燃料油等の物性値分析法において、物性推算式（物性値検量線）の適用についての判断が試料の化学的な構造・組成範囲の側面から明確になされ、適用範囲の拡大や、あるいは分析精度の向上が可能となる。
【図面の簡単な説明】
【図１】水素核蒸気共鳴法（１Ｈ−ＮＭＲ法）の測定結果を示す図である。
【図２】芳香族水素についての実測値と推算値との相関を示す図である。
【図３】メチル水素についての実測値と推算値との相関を示す図である。
【図４】リサーチオクタン価（ＲＯＮ）の実測値と推算値との相関および推算誤差を示す図である。
【図５】密度の実測値と推算値との相関および推算誤差を示す図である。
【図６】蒸気圧の実測値と推算値との相関および推算誤差を示す図である。[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a method for analyzing the physical properties of hydrocarbons represented by products such as gasoline and raw materials such as gasoline base materials, such as octane number, density, vapor pressure, etc., by near infrared analysis.
[0002]
[Prior art]
Physical property value analysis by near-infrared spectroscopy is a physical property estimation formula created based on the relationship between the standard physical property values of a standard sample group and their absorption values in the near-infrared spectrum or their mathematical transformation values (physical property value calibration). Therefore, if the unknown analysis sample has a composition / structure range different from that of the standard sample group, it will be out of the applicable range of the physical property estimation formula (physical property value calibration curve) As a result, the value deviates greatly from the actual value.
On the other hand, in recent years, products such as gasoline and raw materials such as gasoline base materials used therefor have become diverse, and the required accuracy for physical property values has also increased. For this reason, the practical range of the physical property estimation formula (physical property value calibration curve) in the near-infrared spectroscopy is narrow, and the possibility that the unknown analysis sample is out of the applicable range is increasing.
[0003]
In addition, there is no means to judge whether the unknown analysis sample is included in the application range of the physical property estimation formula (physical property value calibration curve) prepared in advance by near-infrared spectroscopy, and whether the obtained analytical value is correct It is impossible to judge. Therefore, a means for determining whether or not the unknown analysis sample is included in the applicable range of the physical property estimation formula (physical property value calibration curve) created is desired.
[0004]
In addition, in order to expand the application range of the basic physical property value estimation formula (physical property value calibration curve), data on samples with different composition and structure ranges from the standard sample group will be added later as necessary. When trying to correct the value estimation formula (physical property value calibration curve), there arises a problem that the estimation accuracy is lower than the physical property estimation formula (physical property value calibration curve) before the correction.
Therefore, there is a demand for a method for accurately estimating physical property values for samples having a composition / structure range different from that of the standard sample group without lowering the accuracy of the basic physical property value estimation formula (physical property value calibration curve). Yes.
[0005]
[Problems to be solved by the invention]
The present invention relates to the determination of the appropriateness of the application range of physical property estimation formulas (physical property value calibration curve) and the expansion of the application range or the improvement of analysis accuracy in the physical property value analysis of fuel oil such as gasoline and its base material by near infrared spectrum method. An object of the present invention is to provide a method for analyzing the physical properties of hydrocarbons.
[0006]
[Means for Solving the Problems]
Physical property estimation to calculate physical properties of the fuel oil (octane number, density, vapor pressure, etc.) from the absorption value in the near-infrared spectrum of the analytical sample such as fuel oil (gasoline, light oil, heavy oil, etc.) In the analytical method using the formula (physical property value calibration curve), the applicable range of the above physical property estimation formula (physical property value calibration curve) is preliminarily defined as hydrogen species (aromatic hydrogen, olefin hydrogen, benzylic hydrogen, methine hydrogen, methylene hydrogen, methyl hydrogen). Etc.) Set separately for the content ratio, and formula for estimating the hydrogen type content ratio created in advance in order to calculate each hydrogen type content ratio from the absorption value in the near-infrared spectrum of the unknown analysis sample or its mathematical conversion value ( The hydrogen property content analysis value obtained using the hydrogen distribution calibration curve) and the applicable range as the content rate of the hydrogen type set above are compared. Determine whether the formula (physical property value calibration curve) is within or outside the applicable range, and if the result of the discrimination is within the applicable range, calculate the physical property value using the physical property value estimation formula (physical property value calibration curve), and If the determination result is out of the applicable range, the physical property value is calculated using the physical property value estimation formula (physical property value calibration curve) and the following physical property value correction formula.
[0007]
Physical property value correction formula Corrected physical property value = Physical property value estimated value (required physical property value estimate value) + Physical property value corrected value based on hydrogen type content ratio (correction term value)
Physical property value correction value (correction term value) according to the hydrogen content
= Σ (each hydrogen type content ratio × each hydrogen species content ratio and the regression coefficient of the physical property value correction value) + constant term, that is, the result of the determination is outside the above-mentioned applicable range (preset as the hydrogen type content ratio range) In this case, the uncorrected “property value estimated value” derived by the above physical property value estimation formula (physical property value calibration curve) is used as the primary physical property value estimated value, The correction term value of the first-order physical property value) is added (algebraic addition) to obtain the desired “corrected physical property value (the physical property value corrected by the above correction term)”. .
[0008]
As described above, by analyzing the content of the hydrogen type from the near-infrared spectrum measurement result of the analytical sample, the composition and the assumption based on the physical property value estimation formula (physical property value calibration curve) prepared in advance by the unknown analytical sample It is possible to determine whether or not it belongs to the structure range, and whether or not it is within the applicable range of the physical property value estimation formula (physical property value calibration curve). Further, by using the physical property value correction formula, the application range of the physical property value estimation formula is expanded, and the accuracy is improved.
[0009]
Therefore, in the method for analyzing physical properties of hydrocarbons according to the near infrared spectrum method of the present invention, the following steps are provided:
(A) a step of preparing a physical property value estimation formula or a calibration curve;
(B) Step of preparing a hydrogen type content rate estimation formula or a calibration curve;
(C) a step of setting, as an application range, a hydrogen type content ratio or an estimated value indicating the application range of the physical property value estimation formula or the calibration curve;
(D) Statistically processing the error value between the reference physical property value and the estimated value obtained from the physical property value estimation formula or the calibration curve and the hydrogen type content ratio for the standard sample outside the applicable range. A step of preparing an error value estimation formula or calibration curve obtained as a physical property value correction value (correction term value) estimation formula or calibration curve;
(E) Measure the near-infrared spectrum of the unknown sample, and estimate the hydrogen type content ratio using the obtained near-infrared spectrum absorption value or its mathematical conversion value and the above hydrogen type content ratio estimation formula or calibration curve. Comparing the obtained estimation result with the application range to determine whether the application range is inside or outside;
(F) a step of estimating a target physical property value by the physical property value estimation formula or a calibration curve when determined to be within the applicable range by the determination; and If necessary, use the physical property value estimation formula or calibration curve to estimate the physical property value that needs correction;
Further, the physical property value correction value (correction term value) is estimated by the above physical property value correction value (correction term value) estimation formula or a calibration curve;
Then, a target corrected physical property value is estimated as an algebraic sum of the physical property value required correction (estimated physical property value required) and the physical property value correction value (correction term value).
[0010]
By providing the steps as described above, the analysis accuracy for unknown samples within the above-mentioned application range is further increased, and the analysis accuracy for unknown samples outside the above-mentioned application range is also adopted by the above physical property value correction values (correction term values). To increase the range of practical analysis.
[0011]
DETAILED DESCRIPTION OF THE INVENTION
In the method for analyzing the physical property values of hydrocarbons by the near-infrared spectrum method according to the present invention, the analysis method includes the following steps.
(A) The standard physical property value obtained by the standard analysis method and the near-infrared spectrum absorption value or its mathematical transformation value are processed by a multivariate analysis method (for example, partial square regression analysis method) for the standard sample. And preparing a physical property value estimation formula or calibration curve;
(B) Processing by using a multivariate analysis method (for example, partial square regression analysis) the hydrogen type content ratio obtained by the standard analysis method for the standard sample and the near infrared spectrum absorption value or its mathematical transformation value And preparing a hydrogen type content ratio estimation formula or a calibration curve;
(C) For the sample used as a standard in Step A, the hydrogen type content ratio, the hydrogen type content ratio estimation formula in Step B or the hydrogen type content ratio estimation value from the calibration curve, the physical property value estimation formula or calibration in Step A above. Setting as the line coverage;
(D) A multivariate analysis method (for example, partial square regression) is used to calculate an error between a hydrogen type content ratio, a standard physical property value, and a physical property value estimation result for a standard sample whose hydrogen type content rate is outside the scope of application of Step C above. Analytical method) to prepare a physical property value correction value (correction term value) estimation formula or calibration curve;
(E) Measure the near-infrared spectrum of an unknown sample, and use the obtained near-infrared spectrum absorption value or its mathematical conversion value, and the hydrogen type content ratio estimation formula or calibration curve in Step B above to contain the hydrogen type A step of estimating the ratio, comparing the obtained estimation result with the application range of Step C, and determining whether the application range is inside or outside;
(F) When it is determined in step E that it is within the applicable range, the near-infrared spectrum absorption value or the mathematical conversion value of the unknown sample and the physical property value estimation formula or calibration curve of step A are used. Estimating the target physical property value;
(G) If it is determined in step E that it is out of the applicable range, correction is necessary using the near-infrared spectrum absorption value or the mathematical conversion value of the unknown sample and the physical property value estimation formula in step A above. Estimate physical properties;
Further, the physical property value correction value (correction term value) is estimated using the hydrogen type content ratio of the unknown sample and the physical property value correction value (correction term value) estimation formula or calibration curve in Step D;
Next, a method for analyzing a physical property value of a hydrocarbon by a near-infrared spectrum method including a step of estimating a target corrected physical property value as an algebraic sum of the physical property value to be corrected and the physical property value correction value (correction term value).
[0012]
【Example】
(1) Preparation and evaluation of hydrogen type content rate estimation formula (hydrogen distribution calibration curve) (1-a) Adjustment of analytical sample Various gasoline base materials (straight-running system, cracking system, reforming system, alkylate system, etc.) Then, 30 kinds of hydrogen distribution calibration curve preparation samples and 20 kinds of calibration curve evaluation samples were prepared by mixing gasoline products at an arbitrary wide range of ratios.
[0013]
(1-b) Measurement of reference value of hydrogen content ratio The hydrogen distribution calibration curve preparation sample (30 types) and the calibration curve evaluation sample (20 types) were prepared by the hydrogen nuclear magnetic resonance method (1H-NMR method), respectively. Aromatic hydrogen, olefin hydrogen, benzylic hydrogen, methine hydrogen, methylene hydrogen, and methyl hydrogen were quantified based on the absorption position and integral ratio, and the actual value of the hydrogen content was obtained.
[0014]
NMR measurement condition apparatus: 90 MHz-FTNMR (Hitachi R1900)
Sample: Sample 10 vol% in deuterated chloroform, TMS 0.03% contained Measurement conditions: 35 ° C., 32 times integration FIG. 1 shows an example of the measurement result of the hydrogen nuclear magnetic resonance method (1H-NMR method).
Table 1 shows the classification of each hydrogen species and the range of each hydrogen species content ratio in the calibration curve preparation sample.
[0015]
[Table 1]

(1-c) Preparation and Evaluation of Hydrogen Type Content Ratio Estimation Formula (Hydrogen Distribution Calibration Curve) Near-infrared spectra were measured for the hydrogen distribution calibration curve preparation sample (30 types) and the calibration curve evaluation sample (20 types). A standard calibration curve preparation sample group was analyzed using a multivariate analysis method for the correlation with the hydrogen type content ratio actual measurement value, and a hydrogen type content ratio estimation formula (hydrogen distribution calibration curve) was prepared. Table 2 shows the multiple correlation coefficient and the standard error of the estimation formula.
[0016]
For the calibration curve evaluation sample, the hydrogen type content rate was calculated using the hydrogen type content rate estimation formula (hydrogen distribution calibration curve) created above, and compared with the hydrogen type content rate measured value. Table 2 shows the error of the predicted value. 2 and 3 show the correlation between the measured values by NMR and the estimated values from the near-infrared spectrum for aromatic hydrogen and methyl hydrogen.
It was found that the estimated value of the content ratio and the measured value showed an excellent correlation for any hydrogen species.
[0017]
Near-infrared spectrum measurement condition equipment: Diffraction grating type (UOP-Guided Wave Insite IV)
Wavelength range: 1000-2100 nm, every 1 nm, 201 point cell: 1 cm gap, probe temperature: 15 ° C.
Spectral processing baseline position correction, smoothing statistical analysis method: PLS (partial square regression analysis)
Wavelength: 1100 to 1500 nm, every 2 nm [Table 2]

(2) Creation of physical property value estimation formula (physical property value calibration curve) (2-a) Preparation of analysis sample Various base materials (straight-running system, Decomposition system, modification system, alkylate system, etc.) were mixed to prepare 50 physical property value calibration curve creation samples and 20 calibration curve evaluation samples.
(2-b) Measurement of standard values of RON, DENS and RVP Physical property value calibration curve creation sample (50 types) and calibration curve evaluation sample (20 types) ), Density (DENS), and Reed vapor pressure (RVP) were measured according to JIS test methods, and actual measured values of physical properties in the ranges shown in Table 3 were obtained.
[0018]
[Table 3]

(2-c) Creation of physical property value estimation formula (physical property value calibration curve) Near-infrared spectra were measured for the physical property value calibration curve creation sample (50 types) and the calibration curve evaluation sample (20 types). Analyze the correlation between measured octane number (RON), density (DENS), and Reed method vapor pressure (RVP) using the multivariate analysis method for sample groups of physical property value calibration curves. Calibration curve). Table 4 shows the multiple correlation coefficient and the standard error of the estimation formula.
[0019]
With respect to the calibration curve evaluation sample, each physical property value was calculated using the physical property value estimation formula (physical property value calibration curve) created above, and compared with the actual measurement value of each physical property value. Table 4 shows the error of the predicted value.
It was found that the predicted value of the content ratio and the actually measured value showed an excellent correlation for any physical property value.
[0020]
Near-infrared spectrum measurement condition equipment: Diffraction grating type (UOP-Guided Wave Insite IV)
Wavelength range: 1000-2100 nm, 1 nm per cell: 1 cm gap, probe temperature: 15 ° C.
Spectral processing baseline position correction, smoothing statistical analysis method: PLS (partial square regression analysis)
Wavelength: 1100-1500 nm, 2 nm, 201 points

(2-d) Applicable range of physical property value estimation formula (physical property value calibration curve) Physical property value calibration curve creation sample Using the hydrogen type content ratio estimation formula (hydrogen distribution calibration curve) created in (1-c) The hydrogen type content ratio was calculated, and the application range of the physical property value estimation formula was determined from the calculated content range. The results are shown in Table 5.
[0021]
[Table 5]

(3) Preparation of property value correction formula based on hydrogen type content ratio (3-a) Preparation of analysis sample Various base materials (straight-running system, decomposition system) in a wider range than the base material composition and mixing ratio of gasoline products normally produced About 30 kinds of samples for preparing physical property value correction formulas.
(3-b) Measurement of standard values of RON, DENS and RVP, and measurement of the proportion of hydrogen type. For the physical property value correction formula creation sample created, the research octane number (RON) and density (DENS) are the target physical property values, respectively. And the Reed method vapor pressure (RVP) was measured according to the JIS test method, and the measured value of each physical property value was obtained. Further, the hydrogen type content rate was calculated using the hydrogen type content rate estimation formula (hydrogen distribution calibration curve) created in (1-c) above. The results are shown in Table 6. It can be seen that the hydrogen species content ratio is wider than that of the physical property value calibration curve preparation sample.
[0022]
[Table 6]

(3-c) Calculation of estimation error of estimated value by physical property value calibration curve The near-infrared spectrum was measured for the physical property value correction formula creation sample (30 types) created in the above (3-a), and the above (2-c The research octane number (RON), density (DENS), and Reed vapor pressure (RVP) were estimated using the physical property value estimation formula (physical property value calibration curve) created in (1). The difference between the obtained integrated value and the actual value of the physical property value measured in (3-b) above was taken as the estimation error. It can be seen that the estimation error is large because the composition and structure are different from those of the physical property value estimation formula preparation sample.
[0023]
(3-d) Physical property value correction value (correction term value) calculation formula based on hydrogen type content ratio Each hydrogen type content ratio estimated in (3-b) and the physical property value estimation defined in (2-d) above Comparison was made with the application range of the formula (physical property value calibration curve), and samples outside the application range were selected. For the selected sample, the multivariate analysis method PLS (partial square regression analysis) is used to calculate the relationship between the estimation error of each physical property value calculated in (3-c) and the content ratio of each hydrogen type calculated in (3-b). A regression equation was created to predict the estimation error of the physical property value estimation formula (physical property value calibration curve), that is, the correction term value.
[0024]
Physical property value correction value (correction term value) according to the hydrogen content
= Σ (regression coefficient of each hydrogen type content ratio × respective hydrogen species content ratio and physical property value correction value) + constant term Table 7 shows the regression coefficient and constant term for each hydrogen species content ratio.
[0025]
[Table 7]

Based on the obtained regression equation, the estimated physical property values were corrected as shown in the following equation.
Corrected physical property value = Physical property value estimated value + Physical property value correction value based on hydrogen type content ratio (correction term value)
The correlation between the estimated value of the physical property value before and after correction and the actual measurement value and the estimation error are shown in FIGS.
[0026]
[Table 8]

The research octane number (RON), density (DENS), and Reed vapor pressure (RVP) all showed that the estimation error can be reduced by using the above correction formula.
[0027]
(4) Verification with commercial gasoline samples The octane number (RON) was estimated by this method using several types of commercial gasoline samples, and compared with actual measured values. The results are shown in Table 9. Using this method, it was shown whether unknown samples are within the applicable range of the physical property value calibration curve, and the estimation error is reduced by using the correction formula for samples outside the applicable range.
[0028]
[Table 9]

[0029]
【The invention's effect】
In the analysis of physical properties of fuel oils, etc. by near-infrared spectroscopy, the judgment on the application of the physical property estimation formula (physical property calibration curve) is made clearly from the aspect of the chemical structure / composition range of the sample. It is possible to enlarge or improve the analysis accuracy.
[Brief description of the drawings]
FIG. 1 is a diagram showing measurement results of a hydrogen nuclear vapor resonance method (1H-NMR method).
FIG. 2 is a diagram showing a correlation between measured values and estimated values for aromatic hydrogen.
FIG. 3 is a diagram showing a correlation between measured values and estimated values for methyl hydrogen.
FIG. 4 is a diagram showing a correlation between an actually measured value and an estimated value of a research octane number (RON) and an estimation error.
FIG. 5 is a diagram showing a correlation between an actually measured value of density and an estimated value, and an estimation error.
FIG. 6 is a diagram showing a correlation between an actually measured value and an estimated value of vapor pressure and an estimation error.

Claims

In the method for analyzing the physical property values of hydrocarbons by the near infrared spectrum method, the above method is:
(A) a step of preparing a physical property value estimation formula or a calibration curve;
(B) Step of preparing a hydrogen type content rate estimation formula or a calibration curve;
(C) a step of setting, as an application range, a hydrogen type content ratio or an estimated value indicating the application range of the physical property value estimation formula or the calibration curve;
(D) Statistically processing the error value between the reference physical property value and the estimated value obtained from the physical property value estimation formula or the calibration curve and the hydrogen type content ratio for the standard sample outside the applicable range. A step of preparing an error value estimation formula or calibration curve obtained as a physical property value correction value (correction term value) estimation formula or calibration curve;
(E) Measure the near-infrared spectrum of an unknown sample, and estimate the hydrogen type content ratio using the obtained near-infrared spectrum absorption value or its mathematical conversion value and the above hydrogen type content ratio estimation formula or calibration curve. Comparing the obtained estimation result with the application range to determine whether the application range is inside or outside;
(F) a step of estimating a target physical property value by the physical property value estimation formula or a calibration curve when determined to be within the applicable range by the determination; If necessary, use the physical property value estimation formula or calibration curve to estimate the physical property value that needs correction;
Further, the physical property value correction value (correction term value) is estimated by the above physical property value correction value (correction term value) estimation formula or a calibration curve;
Next, the physical property of the hydrocarbon by the near-infrared spectrum method, comprising the step of estimating the target corrected physical property value as an algebraic sum of the physical property value to be corrected and the physical property value correction value (correction term value) How to analyze the value.

In the method for analyzing the physical property values of hydrocarbons by the near-infrared spectrum method, the above analysis method comprises:
(A) A standard property value obtained by a standard analysis method and a near-infrared spectrum absorption value or its mathematical transformation value are processed by a multivariate analysis method for a standard sample, and a physical property value estimation formula or calibration Preparing a line;
(B) Hydrogen type content ratio obtained by the standard analysis method for the standard sample and the near infrared spectrum absorption value or its mathematical conversion value are processed by a multivariate analysis method to estimate the hydrogen type content ratio Or preparing a calibration curve;
(C) For the sample used as a standard in Step A, the hydrogen type content ratio, the hydrogen type content ratio estimation formula in Step B or the hydrogen type content ratio estimation value from the calibration curve, the physical property value estimation formula or calibration in Step A above. Setting as the coverage of the line;
(D) The physical property is obtained by processing an error between the hydrogen type content rate, the standard physical property value, and the physical property value estimation result for the standard sample whose hydrogen type content rate is outside the scope of the above step C by the multivariate analysis method. A step of preparing a value correction value (correction term value) estimation formula or a calibration curve;
(E) Measure the near-infrared spectrum of an unknown sample, and use the obtained near-infrared spectrum absorption value or its mathematical conversion value, and the hydrogen type content ratio estimation formula or calibration curve in Step B above to contain the hydrogen type A step of estimating the ratio, comparing the obtained estimation result with the application range of Step C, and determining whether the application range is inside or outside;
(F) When it is determined in step E that it is within the applicable range, the near-infrared spectrum absorption value or the mathematical conversion value of the unknown sample and the physical property value estimation formula or calibration curve of step A are used. Estimating the desired physical property value;
(G) If it is determined in step E that it is out of the applicable range, correction is necessary using the near-infrared spectrum absorption value or the mathematical conversion value of the unknown sample and the physical property value estimation formula in step A above. Estimate physical properties;
Further, the physical property value correction value (correction term value) is estimated using the hydrogen type content ratio of the unknown sample and the physical property value correction value (correction term value) estimation formula or calibration curve in Step D;
2. The near-infrared spectrum according to claim 1, further comprising a step of estimating a target corrected physical property value as an algebraic sum of the physical property value to be corrected and the physical property value correction value (correction term value). Method for analyzing the physical properties of hydrocarbons by the method.

Carbonization by the near-infrared spectrum method according to claim 1 or 2, wherein the hydrogen content or estimated value thereof is obtained for each of aromatic hydrogen, olefin hydrogen, benzylic hydrogen, methine hydrogen, methylene hydrogen, and methyl hydrogen. Analysis method of physical properties of hydrogen.

The said hydrocarbon is fuel oil, The analysis method of the physical property value of hydrocarbon by the near-infrared spectrum method in any one of Claims 1-3.