CN114858742A - Hydrogen sulfide gas detection method - Google Patents
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- 239000007789 gas Substances 0.000 title claims abstract description 87
- RWSOTUBLDIXVET-UHFFFAOYSA-N Dihydrogen sulfide Chemical compound S RWSOTUBLDIXVET-UHFFFAOYSA-N 0.000 title claims abstract description 44
- 229910000037 hydrogen sulfide Inorganic materials 0.000 title claims abstract description 44
- 238000001514 detection method Methods 0.000 title claims abstract description 36
- 230000003595 spectral effect Effects 0.000 claims abstract description 135
- 239000013307 optical fiber Substances 0.000 claims abstract description 10
- 238000001228 spectrum Methods 0.000 claims description 40
- 238000000034 method Methods 0.000 claims description 15
- 230000005284 excitation Effects 0.000 claims description 11
- 238000007789 sealing Methods 0.000 claims description 6
- 238000005311 autocorrelation function Methods 0.000 claims description 3
- 230000004888 barrier function Effects 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 claims description 3
- 238000007599 discharging Methods 0.000 claims description 3
- 230000035939 shock Effects 0.000 claims description 3
- 238000004458 analytical method Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000002329 infrared spectrum Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- NINIDFKCEFEMDL-UHFFFAOYSA-N Sulfur Chemical compound [S] NINIDFKCEFEMDL-UHFFFAOYSA-N 0.000 description 1
- 230000002378 acidificating effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000003795 desorption Methods 0.000 description 1
- 150000002484 inorganic compounds Chemical class 0.000 description 1
- 229910010272 inorganic material Inorganic materials 0.000 description 1
- 238000002336 sorption--desorption measurement Methods 0.000 description 1
- 229910052717 sulfur Inorganic materials 0.000 description 1
- 239000011593 sulfur Substances 0.000 description 1
- 231100000331 toxic Toxicity 0.000 description 1
- 230000002588 toxic effect Effects 0.000 description 1
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Abstract
The invention discloses a hydrogen sulfide gas detection method. It comprises the following steps: introducing gas to be detected into a sample chamber, emitting infrared light by an infrared light source, and detecting the spectral data of the infrared light passing through the gas to be detected and the spectral data of the infrared light passing through a reference optical fiber; calculating a difference value between the two spectral data to obtain a spectral data set L3, and calculating an intensity wave ratio data set T; inputting data in the intensity wave-number ratio data set T into a nonlinear resonance model, and drawing a characteristic signal-to-noise ratio curve; calculating the area of an envelope region corresponding to each wave trough except the last wave trough on the characteristic signal-to-noise ratio curve; marking out points formed by the number of each trough and the corresponding area of the envelope area in a second rectangular coordinate system, linearly fitting to obtain a formula y which is kx + D, judging whether the gas to be detected is hydrogen sulfide gas or not according to k, and calculating the concentration of the hydrogen sulfide gas according to D. The invention can quickly and accurately detect the hydrogen sulfide gas and the concentration thereof, and has good stability.
Description
Technical Field
The invention relates to the technical field of gas detection, in particular to a method for detecting hydrogen sulfide gas.
Background
The hydrogen sulfide is an inorganic compound, is a flammable acidic gas under the standard condition, is colorless, has odor of a rotten egg at low concentration, has sulfur smell at extremely low concentration, and is extremely toxic. At present, a gas sensing element is generally made of a high-sensitivity gas sensitive material to detect hydrogen sulfide gas, but the gas sensitive material generally needs an adsorption-desorption process, and if desorption is not complete, the sensing element cannot be restored to an initial state, that is, a detection signal cannot be restored to a baseline position, so that detection repeatability is not good enough, and the accuracy of detecting hydrogen sulfide gas is affected.
Disclosure of Invention
In order to solve the technical problems, the invention provides a method for detecting hydrogen sulfide gas, which can quickly and accurately detect the hydrogen sulfide gas and the concentration thereof, and has good detection repeatability and good stability.
In order to solve the problems, the invention adopts the following technical scheme:
the invention discloses a method for detecting hydrogen sulfide gas, which is characterized by comprising the following steps:
s1: introducing gas to be detected into a sample chamber, so that the sample chamber is filled with the gas to be detected and the air pressure in the sample chamber reaches 2 atmospheric pressures;
s2: the method comprises the steps that an infrared light source is started to emit infrared light, the infrared light is detected by a first infrared detection module after passing through gas to be detected, the first infrared detection module sends a detected spectrum data set D1 to a central processing unit, the spectrum data set D1 comprises n spectrum data, the infrared light is detected by a second infrared detection module after passing through a reference optical fiber, the second infrared detection module sends a detected spectrum data set D2 to the central processing unit, the spectrum data set D2 comprises n spectrum data, and each spectrum data is composed of wave number sp and corresponding spectrum intensity wn;
s3: the central processing unit arranges the spectral data in the spectral data set D1 from big to small according to wave number to obtain a spectral data set L1, arranges the spectral data in the spectral data set D2 from big to small according to wave number to obtain a spectral data set L2, and subtracts the spectral intensity of the corresponding spectral data in the spectral data set L2 from the spectral intensity of the spectral data in the spectral data set L1 to obtain a spectral data set L3;
s4: the central processing unit calculates an intensity wave ratio tr corresponding to each spectral data in the spectral data set L3 to obtain an intensity wave ratio data set T, T ═ { tr (1), tr (2) … tr (n) }, tr (i) is the ith spectral data G in the spectral data set L3 3 (i) The corresponding intensity wave ratio is that i is more than or equal to 1 and less than or equal to n;
s5: the central processing unit inputs data in the intensity wave-number ratio data set T into a nonlinear resonance model, a characteristic signal-to-noise ratio SNR is obtained by calculation of the nonlinear resonance model, a first rectangular coordinate system is established by the central processing unit with the excitation noise intensity as an X axis and the signal-to-noise ratio as a Y axis, and a characteristic signal-to-noise ratio curve is drawn in the first rectangular coordinate system;
s6: drawing an auxiliary line vertically connected with the Y axis from the point with the maximum signal-to-noise ratio value on the characteristic signal-to-noise ratio curve to the Y axis;
numbering the wave troughs on the characteristic signal-to-noise ratio curve from left to right to be 1 and 2 … … m, wherein m is the number of the wave troughs on the characteristic signal-to-noise ratio curve, selecting the first m-1 wave troughs on the characteristic signal-to-noise ratio curve, taking each wave trough as a starting point, making a first connecting line which penetrates through the left adjacent wave crest and making a second connecting line which penetrates through the right adjacent wave crest, wherein the first connecting line and the second connecting line are intersected with an auxiliary line, and the first connecting line, the second connecting line and the auxiliary line which take each wave trough as the starting point enclose an enveloping area corresponding to each wave trough, and calculating the area of the enveloping area corresponding to each wave trough;
s7: central processing unitEstablishing a second rectangular coordinate system by taking the trough number as an x axis and the area of the envelope region as a y axis, marking a point formed by each trough number and the corresponding area of the envelope region in the second rectangular coordinate system, and performing linear fitting to obtain a formula y as kx + D, wherein if g1 is not less than k is not less than g2, the gas to be detected is hydrogen sulfide gas, and the concentration of the hydrogen sulfide gas is hydrogen sulfide gas
In the scheme, gas to be detected with 2 atmospheres is filled into a sample chamber, then an infrared light source is started to emit light, a first infrared detection module detects spectrum data of infrared light passing through the gas to be detected, a second infrared detection module detects spectrum data of the infrared light passing through a reference optical fiber, the first infrared detection module and the second infrared detection module subtract the spectrum data to obtain a spectrum data set L3 reflecting the gas to be detected, then an intensity wave number ratio tr corresponding to each spectrum data in a spectrum data set L3 is calculated to obtain an intensity wave number ratio data set T, data in the intensity wave number ratio data set T are input into a nonlinear resonance model, a characteristic signal-to-noise ratio SNR is calculated by using the nonlinear resonance model, a central processing unit establishes a first rectangular coordinate system by taking excitation noise intensity as an X axis and signal-to-noise ratio as a Y axis, a characteristic curve signal-to-noise ratio is drawn in the first rectangular coordinate system, an envelope area corresponding to each wave trough is drawn according to the wave peak of the characteristic signal-to-noise ratio curve, calculating the area of the envelope region corresponding to each wave trough, linearly fitting points formed by the number of each wave trough and the area of the envelope region corresponding to the number of each wave trough in a second rectangular coordinate system to obtain a formula y which is kx + D, and if g1 is not less than k is not less than g2, indicating that the gas to be detected is hydrogen sulfide gas and the concentration of the hydrogen sulfide gas is hydrogen sulfide gas
If k < g1 or k > g2, it indicates that the gas to be measured is not hydrogen sulfide gas.
The scheme adopts a continuous 'wave trough + adjacent wave crest' to determine an envelope region, calculates the area of the envelope region, linearly fits a vector formed by the area of the envelope region, judges whether the gas to be detected is hydrogen sulfide gas or not according to the slope of a linear fitting straight line, calculates the concentration of the hydrogen sulfide gas according to intercept, and has better stability than an infrared spectrum direct analysis method. The scheme can quickly and accurately detect the hydrogen sulfide gas and the concentration thereof, and has good detection repeatability and good stability.
Preferably, the step S1 includes the steps of: and (3) introducing the gas to be detected into the sample chamber, completely discharging the air in the sample chamber, sealing the air outlet, continuously introducing the gas to be detected into the sample chamber, stopping introducing the gas to be detected into the sample chamber when the air pressure in the sample chamber reaches 2 atmospheric pressures, and sealing the air inlet.
Preferably, the step S3 includes the steps of:
s31: the central processing unit arranges the spectral data in the spectral data set D1 from large to small according to wave number to obtain a spectral data set L1, L1 ═ { G { 1 (1)、G 1 (2)…G 1 (n) }, i-th spectral data G in spectral data set L1 1 (i)＝(wn 1 (i)、sp 1 (i))，1≤i≤n，sp 1 (i) As spectral data G 1 (i) Spectral intensity of middle (Wn) 1 (i) As spectral data G 1 (i) Wave number of (1);
s32: the central processing unit arranges the spectral data in the spectral data set D2 from large to small according to wave number to obtain a spectral data set L2, L2 ═ { G { 2 (1)、G 2 (2)…G 2 (n) }, i-th spectral data G in the set of spectral data L2 2 (i)＝(wn 2 (i)、sp 2 (i))，sp 2 (i) As spectral data G 2 (i) Spectral intensity of middle (Wn) 2 (i) As spectral data G 2 (i) Wave number of (1);
s33: the central processing unit subtracts the spectral intensity of the corresponding spectral data in the spectral data set L2 from the spectral intensity of the spectral data in the spectral data set L1 to obtain a spectral data set L3, where L3 ═ G 3 (1)、G 3 (2)…G 3 (n) }, i-th spectral data G in the set of spectral data L3 3 (i)＝(wn 3 (i)、sp 3 (i))，
Wherein wn 3 (i)＝wn 2 (i)-wn 1 (i)，sp 3 (i)＝sp 1 (i)＝sp 2 (i)，sp 3 (i) As spectral data G 3 (i) Spectral intensity of middle (Wn) 3 (i) As spectral data G 3 (i) Wave number of (2).
Preferably, the step S5 includes the steps of:
the central processing unit inputs the data in the intensity-wavenumber ratio data set T into a nonlinear resonance model:
where x is the position of the virtual particle in the nonlinear resonance model, V (x) is the nonlinear symmetric potential function, A is the input signal strength, f 0 In order to modulate the frequency of the signal,
for the initial phase, D is the excitation noise intensity, a and b are both coefficients, and ξ (i) is the ith white Gaussian noise whose autocorrelation function is: e [ xi (i) xi (0)]2D δ (i), δ (i) being the shock function;
when D ═ D 1 Then the nonlinear resonance model generates resonance to obtain the characteristic signal-to-noise ratio SNR,
wherein, V 0 Is the barrier height;
the central processing unit establishes a first rectangular coordinate system by taking the excitation noise intensity as an X axis and the signal-to-noise ratio value as a Y axis, and draws a characteristic signal-to-noise ratio curve in the first rectangular coordinate system.
Preferably, the ith spectral data G in the set of spectral data L3 in the step S4 3 (i) The corresponding intensity wave ratio tr (i) is calculated as follows:
The invention has the beneficial effects that: the method can quickly and accurately detect the hydrogen sulfide gas and the concentration thereof, and has good detection repeatability and good stability.
Drawings
FIG. 1 is a flow chart of an embodiment;
FIG. 2 is a schematic diagram of a characteristic signal-to-noise ratio curve;
FIG. 3 is a schematic of a linear fit;
FIG. 4 is a schematic diagram of the structure of the sample chamber.
In the figure: 1. the device comprises a sample chamber, 2, an air inlet, 3, an air outlet, 4, an infrared light source, 5, an infrared detection device, 6 and a reference optical fiber.
Detailed Description
The technical scheme of the invention is further specifically described by the following embodiments and the accompanying drawings.
Example (b): as shown in fig. 1, the method for detecting hydrogen sulfide gas in this embodiment includes the following steps:
s1: introducing gas to be detected into the sample chamber, completely discharging air in the sample chamber, sealing the air outlet, continuously introducing the gas to be detected into the sample chamber, stopping introducing the gas to be detected into the sample chamber when the air pressure in the sample chamber reaches 2 atmospheric pressures, and sealing the air inlet;
s2: the method comprises the steps that an infrared light source is started to emit infrared light, the infrared light is detected by a first infrared detection module after passing through gas to be detected, the first infrared detection module sends a detected spectrum data set D1 to a central processing unit, the spectrum data set D1 comprises n spectrum data, the infrared light is detected by a second infrared detection module after passing through a reference optical fiber, the second infrared detection module sends a detected spectrum data set D2 to the central processing unit, the spectrum data set D2 comprises n spectrum data, and each spectrum data is composed of wave number sp and corresponding spectrum intensity wn;
s3: the central processing unit arranges the spectral data in the spectral data set D1 from large to small according to wave number to obtain a spectral data set L1, L1 ═ { G { 1 (1)、G 1 (2)…G 1 (n) }, i-th spectral data G in the set of spectral data L1 1 (i)＝(wn 1 (i)、sp 1 (i))，1≤i≤n，sp 1 (i) As spectral data G 1 (i) Spectral intensity of (1), wn 1 (i) As spectral data G 1 (i) Wave number of (1);
the central processing unit arranges the spectral data in the spectral data set D2 from large to small according to wave number to obtain a spectral data set L2, L2 ═ { G { 2 (1)、G 2 (2)…G 2 (n) }, i-th spectral data G in the set of spectral data L2 2 (i)＝(wn 2 (i)、sp 2 (i))，sp 2 (i) As spectral data G 2 (i) Spectral intensity of middle (Wn) 2 (i) As spectral data G 2 (i) Wave number of (1);
the central processing unit subtracts the spectral intensity of the corresponding spectral data in the spectral data set L2 from the spectral intensity of the spectral data in the spectral data set L1 to obtain a spectral data set L3, where L3 ═ G 3 (1)、G 3 (2)…G 3 (n) }, i-th spectral data G in the set of spectral data L3 3 (i)＝(wn 3 (i)、sp 3 (i))，
Wherein wn 3 (i)＝wn 2 (i)-wn 1 (i)，sp 3 (i)＝sp 1 (i)＝sp 2 (i)，sp 3 (i) As spectral data G 3 (i) Spectral intensity of middle (Wn) 3 (i) As spectral data G 3 (i) Wave number of (1);
s4: the central processing unit calculates an intensity wave ratio tr corresponding to each spectral data in the spectral data set L3 to obtain an intensity wave ratio data set T, T ═ tr (1), tr (2) … tr (n) }, tr(i) For the ith spectral data G in the spectral data set L3 3 (i) The ratio of the corresponding intensity wave numbers to the corresponding intensity wave numbers,
s5: the central processing unit inputs data in the intensity wave-number ratio data set T into a nonlinear resonance model, a characteristic signal-to-noise ratio SNR is obtained by calculation of the nonlinear resonance model, a first rectangular coordinate system is established by the central processing unit with the excitation noise intensity as an X axis and the signal-to-noise ratio as a Y axis, and a characteristic signal-to-noise ratio curve is drawn in the first rectangular coordinate system;
s6: drawing an auxiliary line vertically connected with the Y axis from the point with the maximum signal-to-noise ratio value on the characteristic signal-to-noise ratio curve to the Y axis;
numbering the wave troughs on the characteristic signal-to-noise ratio curve from left to right to be 1 and 2 … … m, wherein m is the number of the wave troughs on the characteristic signal-to-noise ratio curve, selecting the first m-1 wave troughs on the characteristic signal-to-noise ratio curve, taking each wave trough as a starting point, making a first connecting line which penetrates through the left adjacent wave crest and making a second connecting line which penetrates through the right adjacent wave crest, wherein the first connecting line and the second connecting line are intersected with an auxiliary line, and the first connecting line, the second connecting line and the auxiliary line which take each wave trough as the starting point enclose an enveloping area corresponding to each wave trough, and calculating the area of the enveloping area corresponding to each wave trough;
s7: the central processing unit establishes a second rectangular coordinate system by taking the trough number as an x axis and the area of the envelope region as a y axis, points formed by each trough number and the corresponding area of the envelope region are marked in the second rectangular coordinate system, linear fitting is carried out to obtain a formula y which is kx + D, if k is more than or equal to 2.4 and less than or equal to 2.7, the gas to be detected is hydrogen sulfide gas, and the concentration of the hydrogen sulfide gas is hydrogen sulfide gas
If k is less than 2.4 or k is more than 2.7, the gas to be measured is not hydrogen sulfide gas.
Step S5 includes the following steps:
the central processing unit inputs the data in the intensity-wavenumber ratio data set T into a nonlinear resonance model:
where x is the position of the virtual particle in the nonlinear resonance model, V (x) is the nonlinear symmetric potential function, A is the input signal strength, f 0 In order to modulate the frequency of the signal,
for the initial phase, D is the excitation noise intensity, a and b are both coefficients, and ξ (i) is the ith white Gaussian noise whose autocorrelation function is: e [ xi (i) xi (0)]2D δ (i), δ (i) being the shock function;
when D ═ D 1 Then the nonlinear resonance model generates resonance to obtain the characteristic signal-to-noise ratio SNR,
wherein, V 0 Is the barrier height;
the central processing unit establishes a first rectangular coordinate system by taking the excitation noise intensity as an X axis and the signal-to-noise ratio value as a Y axis, and draws a characteristic signal-to-noise ratio curve in the first rectangular coordinate system.
As shown in fig. 4, the sample chamber 1 is provided with an air inlet 2 and an air outlet 3, the left side and the right side of the sample chamber 1 are symmetrically provided with an infrared light source 4 and an infrared detection device 5, the infrared detection device 5 comprises a first infrared detection module and a second infrared detection module, a reference optical fiber 6 is further arranged in the sample chamber 1, two ends of the reference optical fiber 6 are respectively connected with the infrared light source 4 and the second infrared detection module, the first infrared detection module is used for detecting infrared light passing through a gas to be detected, and the second infrared detection module is used for detecting infrared light passing through the reference optical fiber.
In the scheme, gas to be detected with 2 atmospheres is filled into a sample chamber, then an infrared light source is started to emit light, a first infrared detection module detects spectrum data of infrared light passing through the gas to be detected, a second infrared detection module detects spectrum data of infrared light passing through a reference optical fiber, the spectrum data and the spectrum data are subtracted to obtain a spectrum data set L3 reflecting the gas to be detected, then an intensity wave ratio tr corresponding to each spectrum data in a spectrum data set L3 is calculated to obtain an intensity wave ratio data set T, data in the intensity wave ratio data set T are input into a nonlinear resonance model, a characteristic signal-to-noise ratio SNR is calculated by using the nonlinear resonance model, a central processing unit establishes a first rectangular coordinate system by taking excitation noise intensity as an X axis and a signal-to-noise ratio as a Y axis, a characteristic curve signal-to-noise ratio is drawn in the first rectangular coordinate system, an envelope area corresponding to each wave trough is drawn according to wave crest and trough of the characteristic signal-to-noise ratio curve, calculating the area of the envelope region corresponding to each wave trough, linearly fitting points formed by the number of each wave trough and the area of the envelope region corresponding to the number of each wave trough in a second rectangular coordinate system to obtain a formula y which is kx + D, and if k is more than or equal to 2.4 and less than or equal to 2.7, indicating that the gas to be detected is hydrogen sulfide gas and the concentration of the hydrogen sulfide gas is hydrogen sulfide gas
If k is less than 2.4 or k is more than 2.7, the gas to be measured is not hydrogen sulfide gas.
In this embodiment, after detecting a kind of gas to be measured, points formed by each valley number and the corresponding area of the envelope region are marked in the second rectangular coordinate system, as shown in fig. 3, the linear fitting obtains a formula y of 2.55x +26.08, and since k is 2.55, the gas to be measured is a hydrogen sulfide gas, and the concentration of the hydrogen sulfide gas is 5.139 ppm.
After a characteristic signal-to-noise ratio curve is drawn in the first rectangular coordinate system, an envelope region corresponding to each trough is drawn, and the following example is performed:
fig. 2 is a characteristic snr curve drawn by the cpu in the first rectangular coordinate system when detecting a gas to be detected, where a trough numbered 1 on the characteristic snr curve in fig. 2 is a point o, an adjacent peak on the left side thereof is a point p, an adjacent peak on the right side thereof is a point q, a first connection line passing through the point p is made with the point o as a starting point, a second connection line passing through the point q is made with the point o as a starting point, the first connection line intersects the auxiliary line at a point m, the second connection line intersects the auxiliary line at a point n, and an envelope region corresponding to the trough numbered 1 is a triangle omn. And sequentially drawing the envelope area corresponding to each trough from left to right according to the method until the last trough.
The scheme adopts a continuous 'wave trough + adjacent wave crest' to determine an envelope region, calculates the area of the envelope region, linearly fits a vector formed by the area of the envelope region, judges whether the gas to be detected is hydrogen sulfide gas or not according to the slope of a linear fitting straight line, calculates the concentration of the hydrogen sulfide gas according to intercept, and has better stability than an infrared spectrum direct analysis method. The scheme can quickly and accurately detect the hydrogen sulfide gas and the concentration thereof, and has good detection repeatability and good stability.
Claims (5)
1. A method for detecting hydrogen sulfide gas is characterized by comprising the following steps:
s1: introducing gas to be detected into a sample chamber, so that the sample chamber is filled with the gas to be detected and the air pressure in the sample chamber reaches 2 atmospheric pressures;
s2: the method comprises the steps that an infrared light source is started to emit infrared light, the infrared light is detected by a first infrared detection module after passing through gas to be detected, the first infrared detection module sends a detected spectrum data set D1 to a central processing unit, the spectrum data set D1 comprises n spectrum data, the infrared light is detected by a second infrared detection module after passing through a reference optical fiber, the second infrared detection module sends a detected spectrum data set D2 to the central processing unit, the spectrum data set D2 comprises n spectrum data, and each spectrum data is composed of wave number sp and corresponding spectrum intensity wn;
s3: the central processing unit arranges the spectral data in the spectral data set D1 from big to small according to wave number to obtain a spectral data set L1, arranges the spectral data in the spectral data set D2 from big to small according to wave number to obtain a spectral data set L2, and subtracts the spectral intensity of the corresponding spectral data in the spectral data set L2 from the spectral intensity of the spectral data in the spectral data set L1 to obtain a spectral data set L3;
s4: the central processing unit calculates an intensity wave ratio tr corresponding to each spectral data in the spectral data set L3 to obtain an intensity wave ratio data set T, T ═ { tr (1), tr (2) … tr (n) }, tr (i) is the ith spectral data G in the spectral data set L3 3 (i) The corresponding intensity wave ratio is that i is more than or equal to 1 and less than or equal to n;
s5: the central processing unit inputs data in the intensity wave-number ratio data set T into a nonlinear resonance model, a characteristic signal-to-noise ratio SNR is obtained by calculation of the nonlinear resonance model, a first rectangular coordinate system is established by the central processing unit with the excitation noise intensity as an X axis and the signal-to-noise ratio as a Y axis, and a characteristic signal-to-noise ratio curve is drawn in the first rectangular coordinate system;
s6: drawing an auxiliary line vertically connected with the Y axis from the point with the maximum signal-to-noise ratio value on the characteristic signal-to-noise ratio curve to the Y axis;
numbering the wave troughs on the characteristic signal-to-noise ratio curve from left to right to be 1 and 2 … … m, wherein m is the number of the wave troughs on the characteristic signal-to-noise ratio curve, selecting the first m-1 wave troughs on the characteristic signal-to-noise ratio curve, taking each wave trough as a starting point, making a first connecting line which penetrates through the left adjacent wave crest and making a second connecting line which penetrates through the right adjacent wave crest, wherein the first connecting line and the second connecting line are intersected with an auxiliary line, and the first connecting line, the second connecting line and the auxiliary line which take each wave trough as the starting point enclose an enveloping area corresponding to each wave trough, and calculating the area of the enveloping area corresponding to each wave trough;
s7: the central processing unit establishes a second rectangular coordinate system by taking the wave trough number as an x axis and the area of the envelope region as a y axis, marks points formed by each wave trough number and the corresponding area of the envelope region in the second rectangular coordinate system, and obtains a formula y through linear fittingkx + D, if k is more than or equal to g1 and less than or equal to g2, the gas to be detected is hydrogen sulfide gas, and the concentration of the hydrogen sulfide gas is
2. The method for detecting hydrogen sulfide gas according to claim 1, wherein the step S1 includes the steps of: and (3) introducing the gas to be detected into the sample chamber, completely discharging the air in the sample chamber, sealing the air outlet, continuously introducing the gas to be detected into the sample chamber, stopping introducing the gas to be detected into the sample chamber when the air pressure in the sample chamber reaches 2 atmospheric pressures, and sealing the air inlet.
3. The method for detecting hydrogen sulfide gas according to claim 1, wherein the step S3 includes the steps of:
s31: the central processing unit arranges the spectrum data in the spectrum data set D1 according to wave number from large to small to obtain a spectrum data set L1, wherein L1 is { G ═ G 1 (1)、G 1 (2)…G 1 (n) }, i-th spectral data G in the set of spectral data L1 1 (i)＝(wn 1 (i)、sp 1 (i))，1≤i≤n，sp 1 (i) As spectral data G 1 (i) Spectral intensity of middle (Wn) 1 (i) As spectral data G 1 (i) Wave number of (1);
s32: the central processing unit arranges the spectral data in the spectral data set D2 from large to small according to wave number to obtain a spectral data set L2, L2 ═ { G { 2 (1)、G 2 (2)…G 2 (n) }, i-th spectral data G in spectral data set L2 2 (i)＝(wn 2 (i)、sp 2 (i))，sp 2 (i) As spectral data G 2 (i) Spectral intensity of middle (Wn) 2 (i) As spectral data G 2 (i) Wave number of (1);
s33: the central processing unit subtracts the spectral intensity of the corresponding spectral data in the spectral data set L2 from the spectral intensity of the spectral data in the spectral data set L1 to obtain a spectral data set L3, where L3 ═ G 3 (1)、G 3 (2)…G 3 (n) }, i-th spectral data G in the set of spectral data L3 3 (i)＝(wn 3 (i)、sp 3 (i))，
Wherein wn 3 (i)＝wn 2 (i)-wn 1 (i)，sp 3 (i)＝sp 1 (i)＝sp 2 (i)，sp 3 (i) As spectral data G 3 (i) Spectral intensity of middle (Wn) 3 (i) As spectral data G 3 (i) Wave number of (2).
4. The method for detecting hydrogen sulfide gas according to claim 1, wherein the step S5 includes the steps of:
the central processing unit inputs the data in the intensity-wavenumber ratio data set T into a nonlinear resonance model:
where x is the position of the virtual particle in the nonlinear resonance model, V (x) is the nonlinear symmetric potential function, A is the input signal strength, f 0 In order to modulate the frequency of the signal,
for the initial phase, D is the excitation noise intensity, a and b are both coefficients, and ξ (i) is the ith white Gaussian noise whose autocorrelation function is: e [ xi (i) xi (0)]2D δ (i), δ (i) being the shock function; when D ═ D 1 Then the nonlinear resonance model generates resonance to obtain the characteristic signal-to-noise ratio SNR,
wherein, V 0 Is the barrier height;
the central processing unit establishes a first rectangular coordinate system by taking the excitation noise intensity as an X axis and the signal-to-noise ratio value as a Y axis, and draws a characteristic signal-to-noise ratio curve in the first rectangular coordinate system.
5. The method of claim 1, wherein the ith spectral data G in the set of spectral data L3 in the step S4 is the same as the ith spectral data G in the set of spectral data L3 3 (i) The corresponding intensity wave ratio tr (i) is calculated as follows:
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| CN116399824A (en) * | 2023-05-08 | 2023-07-07 | 浙江大学 | H (H) 2 Method and system for measuring gas concentration in mixed flue gas of S and NO |
| CN116559105A (en) * | 2023-07-06 | 2023-08-08 | 国科大杭州高等研究院 | Linearization readout circuit system based on gas infrared spectrum detection technology |
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| CN116399824A (en) * | 2023-05-08 | 2023-07-07 | 浙江大学 | H (H) 2 Method and system for measuring gas concentration in mixed flue gas of S and NO |
| CN116399824B (en) * | 2023-05-08 | 2023-09-22 | 浙江大学 | H (H) 2 Method and system for measuring gas concentration in mixed flue gas of S and NO |
| CN116559105A (en) * | 2023-07-06 | 2023-08-08 | 国科大杭州高等研究院 | Linearization readout circuit system based on gas infrared spectrum detection technology |
| CN116559105B (en) * | 2023-07-06 | 2023-11-14 | 国科大杭州高等研究院 | Linearization readout circuit system based on gas infrared spectrum detection technology |
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