JP2867474B2 - Gas detection method - Google Patents
Gas detection methodInfo
- Publication number
- JP2867474B2 JP2867474B2 JP26353489A JP26353489A JP2867474B2 JP 2867474 B2 JP2867474 B2 JP 2867474B2 JP 26353489 A JP26353489 A JP 26353489A JP 26353489 A JP26353489 A JP 26353489A JP 2867474 B2 JP2867474 B2 JP 2867474B2
- Authority
- JP
- Japan
- Prior art keywords
- gas
- fourier transform
- sensor
- gas sensor
- component
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
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- Investigating Or Analyzing Materials By The Use Of Fluid Adsorption Or Reactions (AREA)
- Investigating Or Analyzing Materials By The Use Of Electric Means (AREA)
Description
【発明の詳細な説明】 ［発明の利用分野］ この発明は，ガスセンサの非線形応答特性に着目した
ガス検出方法に関する。Description: FIELD OF THE INVENTION The present invention relates to a gas detection method focusing on a non-linear response characteristic of a gas sensor.
［従来技術］ 発明者はガスセンサの非線形応答特性，例えばガスセ
ンサの加熱温度やセンサに加える検出電圧等を周期的に
変化させた際のフーリエ変換の高調波成分での応答特
性，からガスを検出することを検討した。このような非
線形特性を表すものとしては，例えばガスセンサ出力を
フーリエ変換した際の高調波成分，あるいはガスセンサ
出力の温度に対するヒステリシスループを求めた際のル
ープの楕円形からのずれ等がある。[Prior Art] The inventor detects a gas from a nonlinear response characteristic of a gas sensor, for example, a response characteristic of a harmonic component of a Fourier transform when periodically changing a heating temperature of the gas sensor, a detection voltage applied to the sensor, and the like. Considered that. Such nonlinear characteristics include, for example, a harmonic component when the gas sensor output is Fourier-transformed or a deviation of the loop from the ellipse when a hysteresis loop with respect to the temperature of the gas sensor output is obtained.
ガスセンサの非線形特性を利用すると，多数の検出信
号が得られる。例えば刺激としてガスセンサの温度を周
波数ωで正弦波的に変化させることを考える。この場合
センサ温度Tsは， Ts＝T0＋Tb・sin（ωｔ） （１） に従って変化する。ここでT0は平均温度を表す定数,Tb
は温度の振幅である。この際、温度そのものでなくて
も、温度を制御するための電流量を正弦的に変化させて
もよい。その場合も、以下の議論は同様に成立する。こ
れに対して例えばセンサ抵抗Rsを出力とし，これをフー
リエ変換すると， となる。ここにR0は温度変化と無関係な定数部分,nは自
然数,Rnはフーリエ変換の実数部成分,Inはフーリエ変換
の虚数成分を意味する。式（２）のフーリエ変換の結果
は，単純に２つのベクトル，即ち実数部成分のベクトル
（R0,R1,R2,R3,…）と虚数部成分のベクトル，（I1,I2,
I3,…）で表現できる。ここで，例えばR3,I3までの成分
を考慮するとしても，含まれる信号はR0〜R3の４種と,I
1〜I3の３種の合計７種である。そしてこれは，例えば
単純に最高温度でのセンサ出力と最低温度でのセンサ出
力の２種のみを用いる場合に比べ，はるかに多数の信号
を含むものとなる。If the non-linear characteristics of the gas sensor are used, many detection signals can be obtained. For example, consider that the temperature of the gas sensor is sinusoidally changed at a frequency ω as a stimulus. In this case, the sensor temperature Ts changes according to Ts = T 0 + Tb · sin (ωt) (1) Where T 0 is a constant representing the average temperature, Tb
Is the temperature amplitude. At this time, instead of the temperature itself, the amount of current for controlling the temperature may be changed sinusoidally. In that case, the following discussion is similarly established. On the other hand, for example, when the sensor resistance Rs is output and this is Fourier-transformed, Becomes Here, R 0 is a constant part unrelated to a temperature change, n is a natural number, Rn is a real part component of Fourier transform, and In is an imaginary component of Fourier transform. The result of the Fourier transform of equation (2) is simply two vectors: a vector of real part components (R 0 , R 1 , R 2 , R 3 ,...) And a vector of imaginary part components, (I 1 , I 1 2 ,
I 3 , ...). Here, for example, even if the components up to R 3 and I 3 are considered, the contained signals are four types of R 0 to R 3 and I
It is the three of a total of seven of 1 ~I 3. This includes much more signals than, for example, simply using only two types of sensor outputs, the sensor output at the highest temperature and the sensor output at the lowest temperature.
フーリエ変換を用いると,1つのガスセンサから多数の
信号が得られる。これはガスセンサから引き出し得る信
号が増すことを意味する。そして多数の信号が得られれ
ば得られる程，検出の精度や確度が向上する。ガスセン
サから２つの信号を取り出す場合と，フーリエ変換によ
り例えば７つの信号を取り出す場合とを比べると，より
多くの信号が得られればそれだけガスの種類の同定やガ
ス濃度の検出が容易となる。例えば７つの信号があれば
それらの相対比較から，ガスの種類を定めることができ
る。また、７つの信号相互間の合理性検査等により,2種
以上のガスの弁別やガス濃度測定の精度を向上させるこ
とができる。即ちフーリエ変換によりガスセンサの非線
形特性を利用することは，ガス種の決定や濃度の測定を
容易にする。Using Fourier transform, many signals can be obtained from one gas sensor. This means that the signal that can be extracted from the gas sensor increases. The more signals are obtained, the more the detection accuracy and accuracy are improved. Comparing the case where two signals are extracted from the gas sensor and the case where seven signals are extracted by Fourier transform, for example, the more signals are obtained, the easier it is to identify the type of gas and detect the gas concentration. For example, if there are seven signals, the type of gas can be determined from their relative comparison. Further, the accuracy of discrimination of two or more kinds of gases and the measurement of gas concentration can be improved by a rationality test between the seven signals. That is, utilizing the non-linear characteristics of the gas sensor by Fourier transform facilitates determination of the gas type and measurement of the concentration.
このように，ガスセンサの非線形特性を利用すること
により，ガスセンサからより多くの信号を引き出し，よ
り正確なガスの検出を行うことができる。As described above, by utilizing the non-linear characteristics of the gas sensor, more signals can be extracted from the gas sensor, and more accurate gas detection can be performed.
［発明の目的］ この発明の目的は，従来無視されていたガスセンサの
非線形特性を利用し，センサからより多くの信号を引き
出しより正確なガスの検出を行う点にある。[Object of the Invention] An object of the present invention is to utilize the nonlinear characteristics of a gas sensor, which has been neglected in the past, to extract more signals from the sensor and detect gas more accurately.
［発明の構成］ この発明では，検出雰囲気中でガスセンサに周期的刺
激を加えながら，ガスセンサ出力をフーリエ変換し，フ
ーリエ変換の実数部並びに虚数部の各周波数成分の比較
からガスを検出する。According to the present invention, a gas sensor output is Fourier-transformed while a periodic stimulus is applied to the gas sensor in a detection atmosphere, and gas is detected by comparing each frequency component of a real part and an imaginary part of the Fourier transform.
ここに周期的な刺激としては，ガスセンサ温度を周期
的に変化させることの他に，センサに加える検出電圧を
周期的に変化させること等がある。また周期的な変化と
しては，例えば正弦波に沿ったものがフーリエ変換に適
しているが，これに限らず方形波等でも良い。Here, as the periodic stimulation, in addition to periodically changing the temperature of the gas sensor, there is a method of periodically changing the detection voltage applied to the sensor. Further, as the periodic change, for example, a wave along a sine wave is suitable for Fourier transform, but is not limited to this, and may be a square wave or the like.
［実施例］ 第１図に用いた測定回路を示す。図において,2は出願
人の商用ガスセンサ“TGS813"（“TGS813"は商品名）
で,4はSnO2系の金属酸化物半導体,6はヒータである。ガ
スセンサ２にはこれ以外に,Pt等の接触酸化触媒での燃
焼熱を用いた接触燃焼式ガスセンサ等も用い得る。Example A measuring circuit used in FIG. 1 is shown. In the figure, 2 is the applicant's commercial gas sensor "TGS813"("TGS813" is a trade name)
4 is a SnO2 based metal oxide semiconductor and 6 is a heater. In addition to this, a catalytic combustion type gas sensor using combustion heat of a catalytic oxidation catalyst such as Pt can be used as the gas sensor 2.
８は電池等の電源,10はファンクショジェネレータ
で，ここではヒータ６にサイン波の電圧を加えるために
用いる。12は負荷抵抗,14はセンサ出力を記憶するため
のメモリー,16はフーリエ変換回路,18はＸ・Ｙレコーダ
ーでヒータ電圧を横軸にセンサ出力（センサ抵抗Rs）を
縦軸にプロットさせ，温度変化に対するヒステリシスル
ープを描かせるために用いる。フーリエ変換回路16は必
ず用い,X・Ｙレコーダー18は無くても良い。20,22は、
ガス種とその濃度毎にフーリエ変換やヒステリシスルー
プを記憶させたROMで，マップとして用いる。24,26はパ
ターン認識回路で，マップ20,22に記憶させた標準出力
と，実測したフーリエ変換出力との類似度を判別し，ガ
スの種類や濃度を求めるために用いる。Reference numeral 8 denotes a power source such as a battery, and reference numeral 10 denotes a function generator, which is used to apply a sine wave voltage to the heater 6 here. 12 is a load resistance, 14 is a memory for storing the sensor output, 16 is a Fourier transform circuit, 18 is an XY recorder, and the heater voltage is plotted on the horizontal axis and the sensor output (sensor resistance Rs) is plotted on the vertical axis. Used to draw a hysteresis loop for changes. The Fourier transform circuit 16 is always used, and the X / Y recorder 18 may not be provided. 20,22 is
A ROM that stores a Fourier transform and a hysteresis loop for each gas type and its concentration, and is used as a map. Reference numerals 24 and 26 denote pattern recognition circuits that determine the similarity between the standard output stored in the maps 20 and 22 and the measured Fourier transform output, and are used to determine the type and concentration of gas.
測定ガスとして，空気（第２図），アンモニア（第３
図），ベンゼン（第４図），酢酸蒸気（第５図）,n−プ
ロパノール（第６図）を用いた。これらのガスは各100m
lの容器に，これらのガス成分を液体で各100μｌ加え，
気化させたものを用いた。なおアンモニアの場合は,6N
アンモニア水を100ml容器に100μｌ滴下して気化させ
た。センサ２は10秒以上の熱時定数を持ち，温度変化へ
の応答は遅い。そこでセンサ温度は100秒周期で変化さ
せた。また簡単のため，ヒータ電圧を元に，フーリエ変
換やヒステリシスループの作成を行った。なお各図の
（Ａ）はセンサ抵抗Rsの波形を，（Ｂ）はヒータ電圧に
対するヒステリシスループを表す。各図（Ｂ）の横軸
は，ヒータ電圧を表す。各図の（Ｃ），（Ｄ）はフーリ
エ変換を表し，（Ｃ）はフーリエ変換の実数部を，
（Ｄ）は虚数部を表す。図のR0はフーリエ変換の実数部
の定数成分を,R1はヒータ電圧に同期した実数成分を,R2
は実数部の２ω成分を,R3は実数部の３ω成分を,R4は実
数部の４ω成分を表す。記号Ｉは虚数成分を表し,I1は
ω成分を,I2は２ω成分を,I3は３ω成分を,I4は４ω成
分を表す。Air (Fig. 2) and ammonia (3rd
Figure), benzene (Figure 4), acetic acid vapor (Figure 5), and n-propanol (Figure 6). These gases are 100m each
Add 100 μl of each of these gas components as liquid to
The vaporized material was used. In the case of ammonia, 6N
Ammonia water was vaporized by dropping 100 μl into a 100 ml container. Sensor 2 has a thermal time constant of 10 seconds or more, and responds slowly to temperature changes. Therefore, the sensor temperature was changed every 100 seconds. For simplicity, a Fourier transform and a hysteresis loop were created based on the heater voltage. (A) of each figure shows a waveform of the sensor resistance Rs, and (B) shows a hysteresis loop with respect to the heater voltage. The horizontal axis in each figure (B) represents the heater voltage. (C) and (D) in each figure represent the Fourier transform, (C) represents the real part of the Fourier transform,
(D) represents an imaginary part. The R 0 is a constant component of the real part of the Fourier transform of FIG, R 1 is a real component synchronized with the heater voltage, R 2
Represents the 2ω component of the real part, R 3 represents the 3ω component of the real part, and R 4 represents the 4ω component of the real part. The symbol I represents an imaginary component, I 1 represents a ω component, I 2 represents a 2ω component, I 3 represents a 3ω component, and I 4 represents a 4ω component.
第３図（Ａ）のアンモニアの場合を除き，（Ａ）の応
答波形からはガス種毎の特徴は明らかではない。ところ
が（Ｂ）のヒステリシスループでは，ガス種毎の差が明
瞭となる。アンモニアでは，図の左上が鋭く尖り，中央
には平坦な肩が生じる。ベンゼンでは，ヒステリシスル
ープの上下の幅が0.3V程度で極めて広くなる。酢酸とｎ
−プロパノールとは，ヒステリシスループの幅や左上部
の相違から区別できる。Except for the case of ammonia in FIG. 3 (A), the characteristics of each gas type are not clear from the response waveform of (A). However, in the hysteresis loop of (B), the difference for each gas type becomes clear. For ammonia, the upper left of the figure is sharply pointed, with a flat shoulder in the center. In benzene, the width above and below the hysteresis loop is very wide at about 0.3V. Acetic acid and n
-Can be distinguished from propanol by the width of the hysteresis loop and the difference in the upper left.
フーリエ変換を用いると，ガス毎の差はより一層明瞭
となる。表1,表２にフーリエ変換の強度を示す。With the use of the Fourier transform, the differences between the gases become even clearer. Tables 1 and 2 show the intensity of the Fourier transform.
これらのフーリエ変換の高調波成分は，ガスの種類と
濃度毎に固有のものである。例えばアンモニアとベンゼ
ンとは,R1/R0やR2/R0,I2成分の符号や,I2/I1,I3/I1から
識別できる。フーリエ変換には元の非線形応答特性の情
報が完全に含まれており，フーリエ変換を行えば非線形
特性に関する情報を完全に数値化できる。そこでフーリ
エ変換を用いることにより，特にフーリエ変換成分の相
対比較を用いることによりガスの検出ができる。 The harmonic components of these Fourier transforms are unique for each type and concentration of gas. For example, ammonia and benzene, sign or R 1 / R 0 or R 2 / R 0, I 2 component, can be identified from the I 2 / I 1, I 3 / I 1. The Fourier transform completely contains the information of the original nonlinear response characteristic, and the Fourier transform can completely digitize the information about the nonlinear characteristic. Therefore, gas can be detected by using the Fourier transform, particularly by using the relative comparison of the Fourier transform components.
なおデータを省略するが，フーリエ変換に現れるガス
の種類毎の特徴は，ガス濃度によって強弱が変化する。
そこでこれらの特徴の強弱からガス濃度を求めることが
できる。Although the data is omitted, the characteristics of each gas type appearing in the Fourier transform vary depending on the gas concentration.
Therefore, the gas concentration can be obtained from the strength of these characteristics.
［発明の効果］ この発明では，周期的な刺激に対するガスセンサの非
線形応答へのフーリエ変換，特に温度変化への応答のフ
ーリエ変換を用いることにより,1つのガスセンサから多
数の信号を引き出し，ガスの弁別やガス濃度の測定の信
頼性を高める。[Effects of the Invention] In the present invention, by using a Fourier transform to a nonlinear response of a gas sensor to a periodic stimulus, in particular, a Fourier transform to a response to a temperature change, a large number of signals are extracted from one gas sensor to discriminate a gas. And reliability of measurement of gas concentration.
第１図は実施例の回路図， 第２図（Ａ）〜第６図（Ｂ）は，実施例の特性図であ
る。 図において,2……ガスセンサ， 10……ファンクションジェネレータ， 16……フーリエ変換回路， 18……Ｘ・Ｙレコーダ。FIG. 1 is a circuit diagram of the embodiment, and FIGS. 2 (A) to 6 (B) are characteristic diagrams of the embodiment. In the figure, 2 ... gas sensor, 10 ... function generator, 16 ... Fourier transform circuit, 18 ... XY recorder.
Claims (2)
加えながら，ガスセンサ出力をフーリエ変換し， フーリエ変換した出力の実数部並びに虚数部の各周波数
成分の比較からガスを検出するようにした，ガス検出方
法。A gas sensor output is subjected to a Fourier transform while a periodic stimulus is applied to the gas sensor in a detection atmosphere, and a gas is detected by comparing each frequency component of a real part and an imaginary part of the Fourier transformed output. Gas detection method.
周期的に変化させることであることを特徴とする、請求
項１のガス検出方法。2. The gas detecting method according to claim 1, wherein said periodic stimulus is to periodically change a heating temperature of a gas sensor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP26353489A JP2867474B2 (en) | 1989-10-09 | 1989-10-09 | Gas detection method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP26353489A JP2867474B2 (en) | 1989-10-09 | 1989-10-09 | Gas detection method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| JPH03123842A JPH03123842A (en) | 1991-05-27 |
| JP2867474B2 true JP2867474B2 (en) | 1999-03-08 |
Family
ID=17390876
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP26353489A Expired - Fee Related JP2867474B2 (en) | 1989-10-09 | 1989-10-09 | Gas detection method |
Country Status (1)
| Country | Link |
|---|---|
| JP (1) | JP2867474B2 (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7090764B2 (en) * | 2002-01-15 | 2006-08-15 | Agamatrix, Inc. | Method and apparatus for processing electrochemical signals |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE19743644C2 (en) * | 1997-10-02 | 1999-12-16 | Bosch Gmbh Robert | Method for operating a gas sensor |
| JP4755812B2 (en) * | 2004-05-21 | 2011-08-24 | ユーテック株式会社 | Measuring method of chemical substances |
| CN106092178B (en) * | 2016-08-26 | 2018-09-04 | 中煤科工集团重庆研究院有限公司 | Improve the data correcting method of measurement accuracy |
-
1989
- 1989-10-09 JP JP26353489A patent/JP2867474B2/en not_active Expired - Fee Related
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7090764B2 (en) * | 2002-01-15 | 2006-08-15 | Agamatrix, Inc. | Method and apparatus for processing electrochemical signals |
| US8303787B2 (en) | 2002-01-15 | 2012-11-06 | Agamatrix, Inc. | Method and apparatus for processing electrochemical signals |
Also Published As
| Publication number | Publication date |
|---|---|
| JPH03123842A (en) | 1991-05-27 |
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