JP3961915B2 - Odor measurement method - Google Patents

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JP3961915B2
JP3961915B2 JP2002261227A JP2002261227A JP3961915B2 JP 3961915 B2 JP3961915 B2 JP 3961915B2 JP 2002261227 A JP2002261227 A JP 2002261227A JP 2002261227 A JP2002261227 A JP 2002261227A JP 3961915 B2 JP3961915 B2 JP 3961915B2
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odor
sensor
value
threshold
concentration
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JP2004101272A (en
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啓 前田
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財団法人日本自動車研究所
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Description

【0001】
【発明の属する技術分野】
本発明はニオイ(臭い)の閾値が測定可能なニオイ測定方法に関する。
【0002】
【従来の技術】
ニオイの測定技術は食品・香料・環境評価・防災・その他、各種の分野で利用されている。燃料電池自動車などで水素を燃料として用いる場合も、燃料に臭気物質(強臭物質)を添加してガス漏れを検知するという安全対策上、ニオイの測定技術が有用なものになる。
【0003】
上記のような燃料への臭気物質の添加量は、ニオイの強さの尺度である閾値(検知閾値)を基準とする。この閾値は「ニオイあり」と感知できるニオイ物質の最小濃度である。
【0004】
閾値の測定についていうと、これはヒトによる官能試験であるから、ニオイに対する慣れや体調の変化などで不可避的に誤差が生じる。実際上も、測定機関で閾値が10倍から100倍も異なったりすることがある。このような事態を回避するというのが、ニオイの強さをセンサで定量的に測定するためのシステムである。
【0005】
上記におけるニオイのセンサとしては、金属酸化物の半導体センサがよく用いられる。このセンサは、ニオイ分子が通過するときにニオイ物質がセンサ表面で酸化還元し電気抵抗値が変化する。したがって、センサの電気抵抗値の変化を電気信号として取り出すことにより閾値を定量的に検知することができる。
【0006】
【発明が解決しようとする課題】
しかしながら上述したセンサも、これの感度が低いため閾値領域の測定が行えない。そのため特定の物質に高感度を示すセンサを用いたりしているが、これも特定の物質に対してのみ有効なものであるから測定対象が局限されてしまい汎用性がない。
【0007】
【発明の目的】
本発明はこのような技術的課題に鑑み、閾値領域のニオイを精度よく測定することのできる方法を提供しようとするものである。
【0008】
【課題を解決するための手段】
本発明の請求項1に係るニオイ測定方法は所期の目的を達成するために下記の課題解決手段を特徴とする。すなわち請求項1記載のニオイ測定方法は、ニオイ成分の捕捉で変化する電気抵抗値より臭気強度を定量的に検知することができるセンサを用い、かつ、そのセンサの有効範囲内で臭気物質濃度を変化させながら臭気物質の臭気強度を測定したとき臭気物質濃度の対数と測定臭気強度(センサ値)との関係が下記(2)式に示す直線関係になる場合において、このセンサ測定で臭気強度を測定することにより下記(2)式の定数〔k〕〔a〕を求めること、および、センサの有効範囲内でセンサ値と臭気強度とが比例関係にあるとみなして下記(3)式を導き出すとともに、下記(3)式に下記(2)式を代入して下記(4)式を導き出し、さらに、下記(4)式を変形して下記(5)式を導き出すとともに、ニオイ検知できるところの既知臭気物質濃度を下記(5)式の臭気物質濃度に代入することで導き出される下記(6)式に、上記定数〔k 〕〔a 〕を代入し演算処理して、閾値が未知である臭気物質の当該閾値〔Ca〕を求めることを特徴とする。
Is=〔k ×logC〕+〔a 〕………(2)
2)式中、Isはセンサ値、Cは臭気物質濃度である。
I=〔k ×Is〕+〔a 〕………(3)
(3)式中、Iは臭気強度、Isはセンサ値、k 、a は定数(センサの種類のみに依存するもので、閾値〔Ca〕での臭気強度の換算値は臭気物質の種類に関係なく一定)を示す。
I=〔k 〕×〔[k ×logC]+[a ]〕+〔a 〕………(4)
〔I−a 〕÷〔k 〕=〔k ×logC〕+〔a 〕〕………(5)
(5)式中、左辺の〔I−a 〕÷〔k 〕は臭気強度の関数(臭気強度の換算値)である。
〔1−a〕÷〔k〕=〔k×logCa〕+〔a〕=const………(6)
(6)式中constは閾値〔Ca〕での臭気強度の換算値である。
【0009】
本発明の請求項2に係るニオイ測定方法は所期の目的を達成するために下記の課題解決手段を特徴とする。すなわち請求項2記載のニオイ測定方法は、請求項1記載の手段を用いて複数の値(濃度)を求め棄却検定により複数の濃度データから異常値を棄却すること、および、複数の濃度データから95%以上の信頼区間での閾値を算出することを特徴とする。
【0010】
【発明の実施の形態】
本発明に係るニオイ測定方法の実施形態やこれに関連する事項を以下に説明する。
【0011】
悪臭防止法の基本的な尺度である「6段階臭気強度」は下記のとおりである。
臭気強度0=無臭
臭気強度1=やっと感知できるニオイ(検知閾値)
臭気強度2=何のニオイであるかわかる弱いニオイ(認知閾値)
臭気強度3=楽に感知できるニオイ
臭気強度4=強いニオイ
臭気強度5=強烈なニオイ
【0012】
臭気濃度とは、臭気を清浄な空気で希釈しニオイが感られなくなるときの希釈倍率をいう。たとえば1000倍に薄めてニオイが分からなくなったとき臭気濃度は1000となる。
【0013】
上記の例で臭気濃度1000を対数に変換すると「3」になる。この対数を10倍した数値が臭気指数である。上記の例のケースでは臭気指数が30となる。
【0014】
本発明方法で用いられるニオイ検知用のセンサが図1に例示されている。図1のセンサ11は周知のもので金属酸化物の半導体からなる。このセンサ11は既述のとおり、表面でニオイ成分の捕捉を捕捉したときに電気抵抗値が変化する。センサ11を内蔵するためのフローセル12は開閉弁付きのガス流入管13と開閉弁付きのガス流出管14とを備えている。センサ11はこのフローセル12内に配置される。フローセル12内のセンサ11はニオイ検知時の電気抵抗値の変化を電気信号として信号処理部15に送る。これを受けた信号処理部15は所定の信号処理をして「ニオイ成分あり」などと判定したりする。臭気物質をフローセル12内に送り込むためのキャリアガスとしては空気・酸素ガス・不活性ガスなど適当なものもが選択される。その一例として空気をあげることができる。
【0015】
臭気強度については下記(1)式のとおり臭気物質濃度の対数に比例するというウエーバー・フェヒナーの法則がある。これを図示したのが図2である。図2から理解できるように、ヒトの嗅覚によるときは、臭気物質濃度Cが半減しても臭気強度Iがほとんど低下せず(臭気濃度の変化をほとんど感じない)、臭気物質濃度Cの約97%減で臭気強度Iが半減する(臭気濃度が半減したと感じる)。さらに臭気物質濃度Cが約99%減にまで低下したとき臭気強度Iが1/3になる。これはヒトの嗅覚が実際の臭気濃度に一致しないということである。
I=〔k×logC〕+〔a〕……………(1)
(1)式中、Iは臭気強度、Cは臭気物質濃度、k、aは定数を示す。
【0016】
一方、下記(2)式のセンサ11によるときは臭気物質濃度Cが定量的に捕捉できるから、それに基づき臭気強度Iを正確に求めることができる。たとえば図1のキャリアガスが空気で臭気物質が硫化水素であるとする。このケースでキャリアガスに臭気物質が混入していないときは、図1(A)のごとくセンサ11の電気抵抗値が変化せずに初期電気抵抗値を維持する。けれどもキャリアガスに臭気物質が混入しているときは、図1(B)のごとくセンサ表面で臭気物質が捕捉されるために図1(C)のごとくセンサ11の電気抵抗値が変化し、その変化が電気信号として取り出される。これを信号処理部13で処理することで「ニオイ成分あり」という検知結果が出る。その際に臭気物質濃度を表示することもできる。
Is=〔k×logC〕+〔a〕……………(2)
(2)式中、Isはセンサ値、Cは臭気物質濃度、k、aは定数を示す。
【0017】
図3は上記のようにセンサ11で臭気強度(センサ値)を測定したときのセンサ値と臭気物質濃度との関係を示したものである。図3からも窺えるが、臭気物質濃度を変化させたときの臭気強度がセンサ11の有効測定範囲内で測定できることは自明である。したがって臭気物質濃度を変化させたときのセンサ値から(2)式のkやaを求めることができる。しかしニオイ検知できる最小濃度の臭気物質濃度などはセンサ11の有効測定範囲外にあるため感度不足で測定できない。すなわちニオイの閾値(閾値領域のニオイ)は直接測定できないのである。
【0018】
本発明方法は既述のセンサ11を用いてニオイを測定する。本発明方法は、また、前記(1)式における臭気強度Iと前記(2)式におけるセンサ値Isとの間に下記(3)式の関係が成立するとき、(3)式に(2)式を代入して下記(4)式を導き出し、さらに(4)式を変形して下記(5)式を導き出す。この場合において、有効測定範囲内でのセンサ11の測定値から算出した定数k、aはセンサ11の有効測定範囲に関係なく一定となり、(3)式の定数k、aも一定となる。したがって(5)式はセンサ11の有効測定範囲外であるところのニオイの閾値領域にも適用できるようになる。(5)式の左辺は臭気強度の関数(臭気強度の換算値)である。
I=〔k×Is〕+〔a〕……………(3)
(3)式中、Iは臭気強度、Isはセンサ値、k、aは定数を示す。
I=〔k〕×〔[k×logC]+[a]〕+〔a〕………(4)
〔I−a〕÷〔k〕=〔k×logC〕+〔a〕〕……………(5)
(5)式中、左辺の〔I−a〕÷〔k〕は臭気強度の関数(臭気強度の換算値)である。
【0019】
本発明方法において、閾値未知の臭気物質を測定対象としてこれの閾値を推定するときは以下のステップをとる。
【0020】
はじめのステップでは検知閾値が既知の物質を用いて既述の(6)式に検知閾値Caの実数を代入し、臭気強度の換算値を求める。(6)式で左辺の定数a、kはセンサ11の種類のみに依存する。したがって検知閾値での臭気強度の換算値は臭気物質にかかわらず一定となる。
【0021】
つぎのステップでは検知閾値が未知の物質について、これのセンサ値Isや臭気濃度logCをセンサ11の有効測定範囲内で測定し、これらの測定値からk、aを求める。このk、aを下記(7)式に代入し演算処理することで検知閾値が得られる。
logCa=〔const−a〕÷〔k〕………(7)
【0022】
図4は、臭気物質(強臭物質や付臭剤ともいう)として都市ガスに添加されているジメチルスルフィド(DMS)、ターシャリーブチルメルカプタン(TBM)、テトラヒドロチオフェン(THT)について、これらのセンサ値Isや臭気濃度logCをセンサ11の有効測定範囲内で測定し、その濃度曲線から閾値を外挿した図である。以下(7)式から検知閾値を算出する場合の一連のステップについて、これの具体的な実施例を図5に基づき説明する。
【0023】
図5を参照して、はじめは前述したようにセンサ値と臭気物質濃度の対数の関係式を算出する。具体的には、閾値既知の臭気物質の濃度曲線から(3)式のk、aを算出する。ついで(4)式にしたがい既知の検知閾値まで外挿するとともに(6)式の検知閾値での臭気強度の換算値を求める。この後は、検知閾値が未知の物質の臭気物質に対して、臭気濃度とセンサ値との関係式を実験により求め、(7)式のa、kと先の臭気強度の換算値を代入すれば検知閾値Caが求まる。この結果に基づきセンサ値と検知閾値との対応表を作成すればよい。
【0024】
上記における(7)式は(6)式の変形であるから、(6)式にa、kの数値を代入して演算処理することでも検知閾値Caが求まる。
【0025】
上記の各演算処理については、四則演算機能のある電子回路を備えた電子計算機たとえばコンピュータなどを用い、これに所定の数値を入力して行う。
【0026】
検知閾値が未知である臭気物質の当該閾値は上記のようにして求めることができる。もちろんこの場合の検知閾値は一種類のセンサでも求まるが、これについて、複数のセンサを用いて複数の検知閾値を算出する場合は統計処理を行うことが可能になる。ちなみに前記(3)式は理論的なセンサでの関係式であり、実際のセンサは臭気物質の種類などで臭気強度の換算値が異常を示すことがある。しかも実験式からデータを外挿するため誤差が拡大するおそれがある。これら異常値を示すデータを棄却するための棄却検定を行い、かつ、複数のデータから区間推定を行えば、データがより一層信頼性の高いものになる。以下これを実施するときの具体例について、図6を参照して説明する。
【0027】
図6を参照して、はじめはセンサ値と臭気物質濃度の対数の実験式を算出する。つぎにセンサ値と検知閾値との対応表から検知閾値(濃度)を算出する。これは閾値でのセンサ値を示す濃度を計算するというものである。これにて対応表の数個分のデータが出る。表1に示されたものは、外挿により算出した検知閾値濃度での臭気濃度の換算値である。つづいて対応表の数個分の濃度データから異常値を棄却する。これは一例としてグラブスの棄却検定で行う。表2はこの棄却検定の結果を示している。ここで棄却されるのは数値が以上に突出した「データ36」である。この後は信頼区間を推定する。具体的にはt検定で信頼区間を推定する。表3は、「TBM」「THT」の臭気強度の換算値から算出した「DMS」の検知閾値濃度の対数および95%信頼区間での閾値を示している。表3で明らかなように、文献値に示された閾値はセンサから算出したところの95%信頼区間内となる。これはすなわち、センサによる閾値算出ができるということである。
【0028】
【表1】

Figure 0003961915
【0029】
【表2】
Figure 0003961915
【0030】
【表3】
Figure 0003961915
【0031】
以上に述べた本発明の各方法により、広範囲にわたる臭気物質の閾値測定が実現できることになる。
【0032】
【発明の効果】
本発明の請求項1に記載された方法は、一方の臭気物質(閾値既知)から求めた閾値でのセンサ値を他方の臭気物質(閾値未知)に適用させて閾値の測定を可能にしたものであるから、閾値領域のニオイ検知を行う上で有用な手段となる。
【0033】
本発明の請求項2に記載された方法は、複数のセンサ値に基づく統計的処理で閾値の精度を向上させたものであるから、センサ感度のレベルにある臭気物質について閾値を測定することができる。
【図面の簡単な説明】
【図1】本発明方法で用いられるニオイ検知用センサの一例を略示した説明図である。
【図2】ウエーバー・フェヒナーの法則に基づく臭気強度と臭気物質濃度対数との比例関係を示した図である。
【図3】ニオイ検知用センサにおける有効範囲と閾値測定域との関係を示した図である。
【図4】本発明方法において検知閾値濃度で算出した臭気濃度の換算値を例示した図である。
【図5】本発明方法においてセンサ値と閾値との対応を求めるときのステップを例示した説明図である。
【図6】本発明方法においてセンサ値と閾値との対応から閾値を求めるときのステップを例示した説明図である。
【符号の説明】
11 センサ
12 フローセル
13 ガス流入管
14 ガス流出管
15 信号処理部[0001]
BACKGROUND OF THE INVENTION
The present invention relates to an odor measuring method capable of measuring an odor (odor) threshold.
[0002]
[Prior art]
The odor measurement technology is used in various fields such as food, fragrance, environmental assessment, disaster prevention, and others. Even when hydrogen is used as a fuel in a fuel cell vehicle or the like, an odor measurement technique is useful for safety measures in which an odorous substance (strong odorous substance) is added to the fuel to detect a gas leak.
[0003]
The amount of odorous substance added to the fuel as described above is based on a threshold (detection threshold) that is a measure of odor intensity. This threshold is the minimum concentration of an odor substance that can be perceived as “with odor”.
[0004]
As for the measurement of the threshold, since this is a sensory test by humans, errors inevitably occur due to habituation to odors and changes in physical condition. In practice, the threshold may vary from 10 to 100 times at the measuring institution. Avoiding such a situation is a system for quantitatively measuring the odor intensity with a sensor.
[0005]
As the odor sensor, a metal oxide semiconductor sensor is often used. In this sensor, when the odorant molecule passes, the odorant substance is oxidized and reduced on the sensor surface, and the electric resistance value changes. Therefore, the threshold value can be quantitatively detected by taking out the change in the electric resistance value of the sensor as an electric signal.
[0006]
[Problems to be solved by the invention]
However, the above-described sensor cannot measure the threshold region because of its low sensitivity. For this reason, a sensor showing high sensitivity for a specific substance is used. However, since this is also effective only for a specific substance, the measurement target is limited and there is no versatility.
[0007]
OBJECT OF THE INVENTION
In view of such a technical problem, the present invention intends to provide a method capable of accurately measuring the odor of the threshold region.
[0008]
[Means for Solving the Problems]
The odor measuring method according to claim 1 of the present invention is characterized by the following problem solving means in order to achieve an intended purpose. That is, the odor measuring method according to claim 1 uses a sensor capable of quantitatively detecting the odor intensity from the electric resistance value that changes by capturing the odor component , and the odor substance concentration within the effective range of the sensor. When the odor intensity of the odor substance is measured while changing the relationship between the logarithm of the odor substance concentration and the measured odor intensity (sensor value) is a linear relationship shown in the following equation (2), the odor intensity is measured by this sensor measurement. The constant [k s ] [a s ] of the following formula (2) is obtained by measuring, and the sensor value and the odor intensity are considered to be in a proportional relationship within the effective range of the sensor, and the following formula (3) In addition, the following equation (2) is substituted into the following equation (3) to derive the following equation (4). Further, the following equation (4) is modified to derive the following equation (5) and odor detection can be performed. By the way Substituting the above constant [k s ] [a s ] into the following equation (6) derived by substituting the known odor substance concentration into the odor substance concentration of the following equation (5) , the threshold value is unknown The threshold value [Ca] of the odorous substance is obtained .
Is = [k s × log C] + [a s ] (2)
( 2) In the formula, Is is a sensor value, and C is an odor substance concentration.
I = [k 2 × Is] + [a 2 ] (3)
(3) In the formula, I is the odor intensity, Is is the sensor value, k 2 and a 2 are constants (which depend only on the type of sensor, and the converted value of the odor intensity at the threshold [Ca] is the type of odor substance. Constant).
I = [k 2 ] × [[k s × log C] + [a s ]] + [a 2 ] (4)
[I−a 2 ] ÷ [k 2 ] = [k s × log C] + [a s ]] (5)
In formula (5), [I−a 2 ] ÷ [k 2 ] on the left side is a function of odor intensity (converted value of odor intensity).
[1-a 2 ] ÷ [k 2 ] = [k s × log Ca] + [a s ] = const (6)
In the formula (6) , const is a converted value of odor intensity at the threshold [Ca] .
[0009]
The odor measuring method according to claim 2 of the present invention is characterized by the following problem solving means in order to achieve the intended purpose. That odor measuring method of claim 2, wherein a plurality of threshold values (concentration) determined using the means according to claim 1, rejecting outliers from the plurality of density data by rejection test it, and a plurality of concentration A threshold value in a confidence interval of 95% or more is calculated from the data.
[0010]
DETAILED DESCRIPTION OF THE INVENTION
Embodiments of the odor measurement method according to the present invention and matters related thereto will be described below.
[0011]
The “six-level odor intensity”, which is a basic measure of the malodor control method, is as follows.
Odor intensity 0 = Odorless odor intensity 1 = Smell that can be finally detected (detection threshold)
Odor intensity 2 = weak odor that shows what odor (cognitive threshold)
Odor intensity 3 = Easy to detect odor intensity 4 = Strong odor intensity 5 = Intense odor
Odor concentration refers to the dilution factor when odor is diluted with clean air and no odor is felt. For example, the odor concentration becomes 1000 when the odor is lost after being diluted 1000 times.
[0013]
In the above example, when the odor concentration 1000 is converted into a logarithm, “3” is obtained. A numerical value obtained by multiplying the logarithm by 10 is an odor index. In the case of the above example, the odor index is 30.
[0014]
An odor detection sensor used in the method of the present invention is illustrated in FIG. The sensor 11 in FIG. 1 is a well-known sensor and is made of a metal oxide semiconductor. As described above, the electrical resistance value of the sensor 11 changes when the capture of the odor component is captured on the surface. The flow cell 12 for incorporating the sensor 11 includes a gas inflow pipe 13 with an on-off valve and a gas outflow pipe 14 with an on-off valve. The sensor 11 is disposed in the flow cell 12. The sensor 11 in the flow cell 12 sends a change in electric resistance value at the time of odor detection to the signal processing unit 15 as an electric signal. Upon receiving this, the signal processing unit 15 performs predetermined signal processing and determines that “there is an odor component” or the like. As the carrier gas for sending the odorous substance into the flow cell 12, an appropriate gas such as air, oxygen gas or inert gas is selected. One example is air.
[0015]
There is a Weber-Fechner law that the odor intensity is proportional to the logarithm of the odor substance concentration as shown in the following equation (1). This is illustrated in FIG. As can be understood from FIG. 2, when the human olfactory sense is used, the odor intensity I hardly decreases even if the odor substance concentration C is halved (almost no change in odor concentration), and the odor substance concentration C is about 97. % Reduction in odor intensity I is halved (I feel the odor concentration is halved). Further, when the odor substance concentration C is reduced to about 99%, the odor intensity I becomes 1/3. This means that the human sense of smell does not match the actual odor concentration.
I = [k 1 × log C] + [a 1 ] (1)
In the formula (1), I is the odor intensity, C is the odor substance concentration, and k 1 and a 1 are constants.
[0016]
On the other hand, when the sensor 11 of the following formula (2) is used, the odor substance concentration C can be captured quantitatively, and the odor intensity I can be accurately obtained based on the odor substance concentration C. For example, assume that the carrier gas in FIG. 1 is air and the odorous substance is hydrogen sulfide. In this case, when no odorous substance is mixed in the carrier gas, the initial electric resistance value is maintained without changing the electric resistance value of the sensor 11 as shown in FIG. However, when odorous substances are mixed in the carrier gas, the odorous substances are trapped on the sensor surface as shown in FIG. 1 (B), so that the electric resistance value of the sensor 11 changes as shown in FIG. The change is extracted as an electrical signal. When this is processed by the signal processing unit 13, a detection result “There is an odor component” is obtained. At that time, the odor substance concentration can also be displayed.
Is = [k s × log C] + [a s ] (2)
(2) where, Is represents the sensor value, C is the odorant concentration, k s, a a s are constants.
[0017]
FIG. 3 shows the relationship between the sensor value and the odor substance concentration when the odor intensity (sensor value) is measured by the sensor 11 as described above. As can be seen from FIG. 3, it is obvious that the odor intensity when the odor substance concentration is changed can be measured within the effective measurement range of the sensor 11. Therefore it is possible to determine the k s and a s from the sensor value (2) when changing the odorant concentration. However, the minimum concentration of odor substance that can detect odors is outside the effective measurement range of the sensor 11 and cannot be measured due to insufficient sensitivity. That is, the odor threshold (the odor of the threshold area) cannot be measured directly.
[0018]
The method of the present invention measures odor using the sensor 11 described above. In the method of the present invention, when the relationship of the following expression (3) is established between the odor intensity I in the expression (1) and the sensor value Is in the expression (2), the expression (3) The following equation (4) is derived by substituting the equation, and the following equation (5) is derived by further modifying the equation (4). In this case, the constants k s and a s calculated from the measured values of the sensor 11 within the effective measurement range are constant regardless of the effective measurement range of the sensor 11, and the constants k 2 and a 2 in the equation (3) are also constant. It becomes. Therefore, the equation (5) can be applied to an odor threshold region outside the effective measurement range of the sensor 11. The left side of equation (5) is a function of odor intensity (converted value of odor intensity).
I = [k 2 × Is] + [a 2 ] (3)
(3) where, I is the odor intensity, Is the sensor value, k 2, a 2 denotes a constant.
I = [k 2 ] × [[k s × log C] + [a s ]] + [a 2 ] (4)
[I−a 2 ] ÷ [k 2 ] = [k s × log C] + [a s ]] (5)
In formula (5), [I−a 2 ] ÷ [k 2 ] on the left side is a function of odor intensity (converted value of odor intensity).
[0019]
In the method of the present invention, the following steps are taken when estimating a threshold value of an odor substance having an unknown threshold value as a measurement target.
[0020]
In the first step, a substance having a known detection threshold is used and the real number of the detection threshold Ca is substituted into the above-described equation (6) to obtain a converted value of odor intensity. The constants a 2 and k 2 on the left side in equation (6) depend only on the type of sensor 11. Therefore, the converted value of the odor intensity at the detection threshold is constant regardless of the odor substance.
[0021]
An unknown substance detection threshold in the next step, this sensor value Is and odor concentration logC measured within the effective measurement range of the sensor 11, obtains the k s, a s from these measurements. A detection threshold value is obtained by substituting k s and a s into the following equation (7) and performing arithmetic processing.
logCa = [const-a s] ÷ [k s] ......... (7)
[0022]
FIG. 4 shows sensor values of dimethyl sulfide (DMS), tertiary butyl mercaptan (TBM), and tetrahydrothiophene (THT) added to city gas as odor substances (also called strong odor substances and odorants). It is the figure which measured Is and odor density | concentration logC within the effective measurement range of the sensor 11, and extrapolated the threshold value from the density | concentration curve. Hereinafter, a specific example of a series of steps for calculating the detection threshold from the equation (7) will be described with reference to FIG.
[0023]
Referring to FIG. 5, first, as described above, a relational expression of the logarithm of the sensor value and the odorous substance concentration is calculated. Specifically, k 2 and a 2 in equation (3) are calculated from the concentration curve of the odorous substance whose threshold is known. Then, according to the equation (4), extrapolation is performed up to a known detection threshold value, and the converted value of the odor intensity at the detection threshold value of the equation (6) is obtained. Thereafter, with respect to the detection threshold odorants unknown substances, obtained by experiments the relation expression between odor concentration and the sensor value, the corresponding value of a s, k s in the previous odor intensity of (7) If it is substituted, the detection threshold value Ca is obtained. A correspondence table between sensor values and detection threshold values may be created based on this result.
[0024]
Since the expression (7) in the above is a modification of the expression (6), the detection threshold value Ca can also be obtained by substituting the numerical values of a s and k s into the expression (6).
[0025]
Each of the above arithmetic processes is performed by inputting a predetermined numerical value into an electronic computer such as a computer provided with an electronic circuit having four arithmetic functions.
[0026]
The threshold value of the odorous substance whose detection threshold value is unknown can be obtained as described above. Of course, the detection threshold value in this case can be obtained even with one type of sensor. However, when a plurality of detection threshold values are calculated using a plurality of sensors, statistical processing can be performed. Incidentally, the formula (3) is a relational expression in a theoretical sensor, and an actual sensor may show an abnormal odor intensity conversion value depending on the type of odor substance. In addition, there is a risk that the error may increase because the data is extrapolated from the empirical formula. If a rejection test for rejecting data indicating these abnormal values is performed and interval estimation is performed from a plurality of data, the data becomes even more reliable. Hereinafter, a specific example for carrying out this will be described with reference to FIG.
[0027]
Referring to FIG. 6, first, an empirical formula of the logarithm of the sensor value and the odor substance concentration is calculated. Next, a detection threshold value (concentration) is calculated from a correspondence table between sensor values and detection threshold values. This is to calculate the density indicating the sensor value at the threshold. As a result, data for several items in the correspondence table appears. What is shown in Table 1 is a conversion value of the odor concentration at the detection threshold concentration calculated by extrapolation. Next, outliers are rejected from the concentration data for several items in the correspondence table. This is done, for example, by Grubbs' rejection test. Table 2 shows the results of this rejection test. What is rejected here is “data 36” whose numerical values are more prominent. After this, the confidence interval is estimated. Specifically, the confidence interval is estimated by t-test. Table 3 shows the logarithm of the detection threshold concentration of “DMS” calculated from the converted values of the odor intensity of “TBM” and “THT”, and the threshold value in the 95% confidence interval. As is clear from Table 3, the threshold value indicated in the literature value is within the 95% confidence interval calculated from the sensor. This means that the threshold value can be calculated by the sensor.
[0028]
[Table 1]
Figure 0003961915
[0029]
[Table 2]
Figure 0003961915
[0030]
[Table 3]
Figure 0003961915
[0031]
By the above-described methods of the present invention, a wide range of odorous substance threshold measurement can be realized.
[0032]
【The invention's effect】
The method described in claim 1 of the present invention enables measurement of a threshold value by applying a sensor value at a threshold value obtained from one odorous substance (threshold known) to the other odorous substance (threshold unknown). Therefore, this is a useful means for performing odor detection in the threshold region.
[0033]
Since the method described in claim 2 of the present invention improves the accuracy of the threshold value by statistical processing based on a plurality of sensor values, it is possible to measure the threshold value for an odor substance at the sensor sensitivity level. it can.
[Brief description of the drawings]
FIG. 1 is an explanatory diagram schematically showing an example of an odor detection sensor used in the method of the present invention.
FIG. 2 is a diagram showing a proportional relationship between odor intensity and odorous substance concentration logarithm based on Weber-Fechner's law.
FIG. 3 is a diagram showing a relationship between an effective range and a threshold measurement range in the odor detection sensor.
FIG. 4 is a diagram exemplifying a converted value of odor concentration calculated by a detection threshold concentration in the method of the present invention.
FIG. 5 is an explanatory diagram exemplifying steps when obtaining a correspondence between a sensor value and a threshold in the method of the present invention.
FIG. 6 is an explanatory diagram exemplifying steps when a threshold value is obtained from a correspondence between a sensor value and a threshold value in the method of the present invention.
[Explanation of symbols]
11 Sensor 12 Flow cell 13 Gas inflow pipe 14 Gas outflow pipe 15 Signal processor

Claims (2)

ニオイ成分の捕捉で変化する電気抵抗値より臭気強度を定量的に検知することができるセンサを用い、かつ、そのセンサの有効範囲内で臭気物質濃度を変化させながら臭気物質の臭気強度を測定したとき臭気物質濃度の対数と測定臭気強度(センサ値)との関係が下記(2)式に示す直線関係になる場合において、このセンサ測定で臭気強度を測定することにより下記(2)式の定数〔k〕〔a〕を求めること、および、センサの有効範囲内でセンサ値と臭気強度とが比例関係にあるとみなして下記(3)式を導き出すとともに、下記(3)式に下記(2)式を代入して下記(4)式を導き出し、さらに、下記(4)式を変形して下記(5)式を導き出すとともに、ニオイ検知できるところの既知臭気物質濃度を下記(5)式の臭気物質濃度に代入することで導き出される下記(6)式に、上記定数〔k 〕〔a 〕を代入し演算処理して閾値が未知である臭気物質の当該閾値〔Ca〕を求めることを特徴とするニオイ測定方法。
Is=〔k ×logC〕+〔a 〕………(2)
2)式中、Isはセンサ値、Cは臭気物質濃度である。
I=〔k ×Is〕+〔a 〕………(3)
(3)式中、Iは臭気強度、Isはセンサ値、k 、a は定数(センサの種類のみに依存するもので、閾値〔Ca〕での臭気強度の換算値は臭気物質の種類に関係なく一定)を示す。
I=〔k 〕×〔[k ×logC]+[a ]〕+〔a 〕………(4)
〔I−a 〕÷〔k 〕=〔k ×logC〕+〔a 〕〕………(5)
(5)式中、左辺の〔I−a 〕÷〔k 〕は臭気強度の関数(臭気強度の換算値)である。
〔1−a〕÷〔k〕=〔k×logCa〕+〔a〕=const………(6)
(6)式中constは閾値〔Ca〕での臭気強度の換算値である。
Using a sensor that can quantitatively detect the odor intensity from the electrical resistance value that changes due to the capture of odorous components, the odor intensity of the odor substance was measured while changing the odor substance concentration within the effective range of the sensor. When the relationship between the logarithm of the odor substance concentration and the measured odor intensity (sensor value) is a linear relationship shown in the following equation (2), the odor intensity is measured by this sensor measurement, and the constant of the following equation (2) [K s ] [a s ] is obtained, and the sensor value and the odor intensity are considered to be in a proportional relationship within the effective range of the sensor, and the following expression (3) is derived. Substituting the equation (2) to derive the following equation (4), and further modifying the following equation (4) to derive the following equation (5), and the known odor substance concentration at which odor detection is possible is as follows (5) Odor of formula The following (6) derived by substituting the quality concentration, that threshold by calculating process by substituting the constant [k s] [a s] is determined the threshold [Ca] odorant unknown Characteristic odor measurement method.
Is = [k s × log C] + [a s ] (2)
( 2) In the formula, Is is a sensor value, and C is an odor substance concentration.
I = [k 2 × Is] + [a 2 ] (3)
(3) In the formula, I is the odor intensity, Is is the sensor value, k 2 and a 2 are constants (which depend only on the type of sensor, and the converted value of the odor intensity at the threshold [Ca] is the type of odor substance. Constant).
I = [k 2 ] × [[k s × log C] + [a s ]] + [a 2 ] (4)
[I−a 2 ] ÷ [k 2 ] = [k s × log C] + [a s ]] (5)
In formula (5), [I−a 2 ] ÷ [k 2 ] on the left side is a function of odor intensity (converted value of odor intensity).
[1-a 2 ] ÷ [k 2 ] = [k s × log Ca] + [a s ] = const (6)
In the formula (6) , const is a converted value of odor intensity at the threshold [Ca] .
請求項1記載の手段を用いて複数の値(濃度)を求め棄却検定により複数の濃度データから異常値を棄却すること、および、複数の濃度データから95%以上の信頼区間での閾値を算出することを特徴とするニオイ測定方法。Determined plurality of threshold values (concentration) using means according to claim 1, wherein, to reject outliers from the plurality of density data by rejection test, and the threshold value of a plurality of the density data of more than 95% confidence interval The odor measuring method characterized by calculating.
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