Disclosure of Invention
In order to solve the technical problem of low gas concentration detection accuracy in the existing flue gas measurement method, the invention aims to provide a high-precision flue gas measurement method, which adopts the following technical scheme:
a method for high-precision measurement of flue gas, comprising:
Introducing the flue gas to be detected into a sample cell of a DOAS (differential optical absorption spectroscopy) measuring system, and obtaining differential absorption spectrum data of the flue gas to be detected at room temperature by using the DOAS measuring system, wherein the flue gas to be detected comprises a plurality of different gases;
Screening differential absorption spectrum data corresponding to a region with the most concentrated smoke distribution concentration in a sample cell from the differential absorption spectrum data of the smoke to be detected at room temperature, and taking the differential absorption spectrum data as spectrum data to be processed;
Separating overlapped absorption peaks in the spectrum data to be processed based on the influence difference of temperature on absorption peaks of different gases so as to obtain absorption peak curves corresponding to all gases in the flue gas to be detected;
And obtaining the concentration of each gas in the flue gas to be detected according to the absorption peak curve corresponding to each gas.
Further, screening differential absorption spectrum data corresponding to a region with the most concentrated smoke distribution concentration in the sample cell from differential absorption spectrum data of smoke to be detected at room temperature, wherein the differential absorption spectrum data is used as the spectrum data to be processed and comprises the following steps:
introducing air into a sample cell of a DOAS (differential optical absorption spectroscopy) measuring system, and obtaining differential absorption spectrum data of the air at room temperature by using the DOAS measuring system;
Dividing a spectrometer scanning area in a sample cell of the DOAS measurement system into a plurality of subareas uniformly;
And determining the subarea with the strongest smoke distribution concentration in the sample cell based on the difference between the differential absorption spectrum data of the smoke to be detected at the room temperature and the differential absorption spectrum data of the air at the room temperature, and taking the differential absorption spectrum data corresponding to the subarea with the strongest smoke distribution concentration in the sample cell as the spectrum data to be processed.
Further, determining the sub-region with the strongest smoke distribution concentration in the sample cell based on the difference between the differential absorption spectrum data of the smoke to be detected at the room temperature and the differential absorption spectrum data of the air at the room temperature, which corresponds to each sub-region, comprises:
and calculating the difference between the differential absorption spectrum data of the smoke to be detected at the room temperature and the differential absorption spectrum data of the air at the room temperature, which correspond to each subarea, wherein the formula is as follows:
;
wherein,The difference between the differential absorption spectrum data of the smoke to be detected at the room temperature and the differential absorption spectrum data of the air at the room temperature corresponding to the kth sub-region; The peak value of the absorption peak of the smoke to be detected corresponding to the ith wavelength in the differential absorption spectrum data of the smoke to be detected at room temperature corresponding to the kth sub-region; The peak value of the absorption peak of the air corresponding to the ith wavelength in the differential absorption spectrum data of the air at room temperature corresponding to the kth sub-region; The number of the wavelengths; The representation takes absolute value;
and calculating the specific gravity of the smoke at room temperature corresponding to each subarea, wherein the formula is as follows:
;
wherein,The specific gravity of the smoke at room temperature corresponding to the kth sub-area is represented; the difference between the differential absorption spectrum data of the smoke to be detected at room temperature and the differential absorption spectrum data of the air at room temperature corresponding to the jth sub-region is represented, wherein m represents the number of the sub-regions; Representing a normalization function;
taking the subregion with the largest specific gravity of the smoke at room temperature as the subregion with the thickest smoke distribution concentration in the sample cell.
Further, based on the difference of the influence of the temperature on the absorption peaks of different gases, the overlapping absorption peaks in the to-be-processed spectrum data are separated to obtain absorption peak curves corresponding to each gas in the flue gas to be detected, including:
Acquiring differential absorption spectrum data of the smoke to be tested at different temperatures;
acquiring a temperature difference index of each absorption peak based on differential absorption spectrum data of the smoke to be detected at different temperatures;
Based on the temperature difference index of each absorption peak, a preset clustering algorithm is adopted to cluster the absorption peaks in the to-be-processed spectrum data, and the absorption peak in each cluster after the clustering is used as an absorption peak of one gas, so that the absorption peaks corresponding to different gases in the to-be-processed spectrum data are separated, and an absorption peak curve corresponding to each gas in the to-be-detected flue gas is obtained.
Further, based on differential absorption spectrum data of the flue gas to be detected at different temperatures, obtaining a temperature difference index of each absorption peak includes:
Acquiring peak values of each absorption peak at different temperatures based on differential absorption spectrum data of the flue gas to be detected at different temperatures;
for each absorption peak, obtaining a polynomial curve of the peak value along with the temperature change based on the peak value of the absorption peak at different temperatures;
For each absorption peak, calculating an original temperature difference index based on a polynomial curve of the peak value along with the temperature change and a maximum change value of the width of the absorption peak due to the temperature change;
and correcting the original temperature difference index of each absorption peak according to the influence degree of the temperature on the specific gravity of the flue gas in the subregion with the thickest flue gas distribution concentration in the sample cell, so as to obtain the temperature difference index of each absorption peak.
Further, the polynomial curve of the peak value of the absorption peak as a function of temperature is expressed as:
;
wherein,Represent the firstPeak values of the individual absorption peaks; Representing a temperature value;、、、 are fitting coefficients.
Further, for each absorption peak, calculating an original temperature difference index based on a polynomial curve whose peak value varies with temperature and a maximum variation value of the width of the absorption peak due to temperature variation, including:
Calculating a characteristic value of each absorption peak based on a polynomial curve of the peak value along with the temperature change;
for each absorption peak, calculating an original temperature difference index based on a characteristic value and a maximum variation value of the width of the absorption peak due to temperature variation, wherein the calculation formula of the original temperature difference index is as follows:
;
wherein,Represent the firstOriginal temperature difference index of each absorption peak; Represent the firstCharacteristic values of the individual absorption peaks; Represent the firstThe width of each absorption peak has a maximum variation value due to temperature variation.
Further, the characteristic value of the absorption peak is expressed as:
;
wherein,Represent the firstCharacteristic values of the individual absorption peaks.
Further, the temperature difference index of the absorption peak is expressed as:
;
wherein,Is the firstTemperature difference indicators for the individual absorption peaks; Is the firstOriginal temperature difference index of each absorption peak; the specific gravity of the flue gas at the t-th temperature value is the region with the thickest flue gas distribution concentration in the sample cell; C is the average value of the specific gravities of the flue gas in the sub-region with the thickest flue gas distribution concentration in the sample cell under c different temperature values; the representation takes absolute value.
Further, the value range of the temperature value is 20-100 ℃.
The invention has the following beneficial effects:
According to the high-precision flue gas measurement method, the region with the highest flue gas distribution concentration in the sample cell is determined according to the distribution condition of the flue gas to be measured in the sample cell, the differential absorption spectrum data corresponding to the flue gas in the region is used as the spectrum data to be treated, and further, overlapped absorption peaks in the spectrum data to be treated are separated according to the characteristic that absorption peaks of different gases change along with temperature, so that absorption peak curves corresponding to the gases are accurately obtained, and further, the concentration detection precision of different gases in the flue gas is improved.
Detailed Description
In order to further describe the technical means and effects adopted by the invention to achieve the preset aim, the following detailed description refers to specific implementation, structure, characteristics and effects of a flue gas high-precision measurement method according to the invention by combining the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The invention provides a smoke high-precision measurement method which is specifically described below with reference to the accompanying drawings.
A high-precision measurement method for flue gas is shown in figure 1, and the method comprises the following implementation steps:
S1, introducing smoke to be detected into a sample cell of a DOAS (differential optical absorption spectroscopy) measuring system, and obtaining differential absorption spectrum data of the smoke to be detected at room temperature by using the DOAS measuring system, wherein the smoke to be detected comprises a plurality of different gases;
The structure of the DOAS measurement system adopted in the embodiment is shown in fig. 2, which uses an L6565 deuterium lamp as a light source, and can provide 200 nm-400 nm band continuous spectrum, the incident light of the light source enters a sample cell after being collimated, and the emergent light enters a spectrometer by using an optical fiber coupling mode. The width of an incident slit of the spectrometer is 25 mu m, the reticle density of the grating is 1200/mm, the spectrum range is 200 nm-500 nm, and the resolution is 0.65nm. During the experiment, the pressure in the sample cell was kept constant. The flue gas to be detected is the flue gas discharged in the industrial production process, and mainly comprises sulfur dioxide, nitrogen oxides and other harmful gases.
S2, screening differential absorption spectrum data corresponding to a region with the highest smoke distribution concentration in the sample cell from differential absorption spectrum data of smoke to be detected at room temperature, and taking the differential absorption spectrum data as spectrum data to be processed;
It should be noted that, since the flue gas may contain carbon particles, sulfur oxides, nitrogen oxides, etc., and these substances generally have a density greater than that of air, after the flue gas is filled into the sample cell, the flue gas may be unevenly distributed in the whole sample cell, thereby causing different absorption peaks in different regions. Therefore, in order to realize the subsequent spectrum data processing, the distribution condition of the smoke needs to be determined first.
Specifically, in this embodiment, the implementation procedure of S2 is as follows:
S21, introducing air into a sample cell of a DOAS (differential optical absorption spectroscopy) measuring system, and obtaining differential absorption spectrum data of the air at room temperature by using the DOAS measuring system.
S22, uniformly dividing a spectrometer scanning area in a sample cell of the DOAS measurement system into a plurality of subareas.
S23, determining a subarea with the most concentrated smoke distribution concentration in the sample cell based on the difference between the differential absorption spectrum data of the smoke to be detected at the room temperature and the differential absorption spectrum data of the air at the room temperature, which correspond to each subarea, and taking the differential absorption spectrum data corresponding to the subarea with the most concentrated smoke distribution concentration in the sample cell as the spectrum data to be processed;
Further, determining the sub-region with the strongest smoke distribution concentration in the sample cell based on the difference between the differential absorption spectrum data of the smoke to be detected at the room temperature and the differential absorption spectrum data of the air at the room temperature, which corresponds to each sub-region, comprises:
S231, calculating the difference between the differential absorption spectrum data of the smoke to be detected at the room temperature and the differential absorption spectrum data of the air at the room temperature, which correspond to each subarea, wherein the formula is as follows:
;
wherein,The difference between the differential absorption spectrum data of the smoke to be detected at room temperature and the differential absorption spectrum data of the air at room temperature corresponding to the kth sub-region is larger, and the larger the difference value is, the larger the current smoke ratio is; The peak value of the absorption peak of the smoke to be detected corresponding to the ith wavelength in the differential absorption spectrum data of the smoke to be detected at room temperature corresponding to the kth sub-region; The peak value of the absorption peak of the air corresponding to the ith wavelength in the differential absorption spectrum data of the air at room temperature corresponding to the kth sub-region; The number of the wavelengths; The representation takes absolute value;
s232, calculating the specific gravity of the flue gas at room temperature corresponding to each subarea, wherein the formula is as follows:
;
wherein,The specific gravity of the smoke at room temperature corresponding to the kth sub-area is represented; the difference between the differential absorption spectrum data of the smoke to be detected at room temperature and the differential absorption spectrum data of the air at room temperature corresponding to the jth sub-region is represented, wherein m represents the number of the sub-regions; Representing a normalization function; The method is used for representing whether the current subarea is a region with larger smoke specific gravity or not, and the larger the value of the current subarea is, the more likely the corresponding subarea is the region with larger smoke specific gravity;
s233, taking the subregion with the largest specific gravity of the smoke at room temperature as the subregion with the thickest smoke distribution concentration in the sample cell.
S3, separating overlapped absorption peaks in the to-be-processed spectrum data based on the influence difference of temperature on absorption peaks of different gases so as to obtain absorption peak curves corresponding to all gases in the flue gas to be detected;
In addition, when the gas concentration is detected by the DOAS technology, the temperature affects the absorption peak of the gas, and as shown in FIG. 3, the change of the absorption peak and the peak of the SO2 (sulfur dioxide) gas at 3 different temperature points (50 ℃, 70 ℃ and 90 ℃) is shown. The law of the influence of temperature on the absorption peak of gas can be roughly expressed as that the absorption line peak of gas is reduced and the absorption characteristic tends to be smooth with the rise of temperature in a certain temperature range. But also different gases have different responses to temperature changes due to differences in molecular structure and energy levels. For example, gases having complex molecular structures or larger molecules may be more sensitive to temperature changes. Therefore, the absorption peaks of different gases can be distinguished by the change condition of the absorption peaks of the gases under different temperature changes.
Specifically, in this embodiment, the implementation procedure of S3 is as follows:
S31, obtaining differential absorption spectrum data of the smoke to be detected at different temperatures;
In the embodiment, the value range of the temperature value is 20-100 ℃;
s32, acquiring a temperature difference index of each absorption peak based on differential absorption spectrum data of the flue gas to be detected at different temperatures;
The temperature difference index of the absorption peak is calculated as follows:
s321, acquiring peak values of each absorption peak at different temperatures based on differential absorption spectrum data of the flue gas to be detected at different temperatures;
S322, for each absorption peak, obtaining a polynomial curve of the peak value along with the temperature change based on the peak value of the absorption peak at different temperatures;
in order to obtain a polynomial curve of the peak value of the absorption peak changing with temperature, a data coordinate system is first constructed with the temperature as the abscissa and the absorption peak value at each wavelength as the ordinate, the peak values of the absorption peaks obtained at different temperatures are represented in the coordinate system, and then a polynomial fitting method is used to fit a curve equation of the temperature and the absorption peak value by using the data coordinate system.
Specifically, in the present embodiment, the polynomial curve of the peak value of the absorption peak as a function of temperature is expressed as:
;
wherein,Represent the firstPeak values of the individual absorption peaks; Representing a temperature value;、、、 Are fitting coefficients;
S323, calculating an original temperature difference index of each absorption peak based on a polynomial curve of the peak value along with the temperature change and a maximum change value of the width of the absorption peak due to the temperature change, wherein the calculation process is as follows:
s3231, for each absorption peak, calculating a characteristic value based on a polynomial curve of the peak value along with the temperature, wherein the formula is as follows:
;
wherein,Represent the firstCharacteristic values of the individual absorption peaks;
In addition, it should be noted that, for the polynomial curve, the coefficient of the higher-order term represents the intensity of the curve change, so the coefficient of Xiang Jie may be integrated to represent the characteristic value of each absorption peak;
s3232, for each absorption peak, calculating an original temperature difference index based on a characteristic value and a maximum variation value of the width of the absorption peak due to temperature variation;
It should be noted that, since the temperature change may cause not only the peak value change but also the peak width change of the absorption peak, when calculating the original temperature difference index, the maximum change value of the width of the absorption peak due to the temperature change of the current absorption peak needs to be considered while the temperature change curve of the peak value of the absorption peak is considered. Based on this, in the present embodiment, the calculation formula of the original temperature difference index is:
;
wherein,Represent the firstOriginal temperature difference index of each absorption peak; Represent the firstThe width of each absorption peak has a maximum variation value due to temperature variation.
S324, correcting the original temperature difference index of each absorption peak according to the influence degree of the flue gas proportion of the most concentrated subregion of the flue gas distribution concentration in the sample pool by temperature to obtain the temperature difference index of each absorption peak;
wherein, the temperature difference index of the absorption peak is expressed as:
;
wherein,Is the firstTemperature difference indicators for the individual absorption peaks; Is the firstOriginal temperature difference index of each absorption peak; the specific gravity of the flue gas at the t-th temperature value is the region with the thickest flue gas distribution concentration in the sample cell; C is the average value of the specific gravities of the flue gas in the sub-region with the thickest flue gas distribution concentration in the sample cell under c different temperature values;
and the condition that the specific gravity of the flue gas in the subregion with the thickest flue gas distribution concentration in the sample cell is influenced by temperature is indicated.
S33, clustering the absorption peaks in the to-be-processed spectrum data by adopting a preset clustering algorithm based on the temperature difference index of each absorption peak, and taking the absorption peak in each cluster after clustering as an absorption peak of gas so as to separate the absorption peaks corresponding to different gases in the to-be-processed spectrum data and obtain absorption peak curves corresponding to each gas in the to-be-detected flue gas;
the clustering algorithm adopted in the embodiment is a spatial clustering DBSCAN clustering algorithm applied to noise based on density.
S4, according to the absorption peak curves corresponding to the gases, the concentration of the gases in the flue gas to be detected is obtained;
The method for obtaining the gas concentration according to the absorption peak curve corresponding to the gas is the prior art, and is widely applied at present, namely, the absorption contributions of different gases are distinguished and quantified according to the absorption peak of each gas by adopting a Multiple Linear Regression (MLR) method, a model for representing the relation between the absorption peak and the gas concentration is built based on standard gases with known concentrations, the model is trained, model parameters are optimized, the trained model is applied to the spectrum data of the current gas, and the concentration of the gas is predicted.
In summary, the embodiment firstly determines the region with the thickest smoke distribution concentration in the sample cell according to the distribution condition of the smoke to be detected in the sample cell, takes the differential absorption spectrum data corresponding to the smoke in the region as the spectrum data to be processed, and then separates overlapped absorption peaks in the spectrum data to be processed according to the different characteristics of the absorption peaks of different gases along with the temperature change so as to accurately acquire absorption peak curves corresponding to the gases, thereby effectively improving the concentration detection precision of different gases in the smoke.
The above description is merely a preferred embodiment of the present invention. The processes depicted in the accompanying drawings do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous. And while the preferred embodiments of the present invention have been described, it will be apparent to those skilled in the art that, once the basic inventive concepts of the present invention are known, several modifications and adaptations can be made without departing from the principles of the present invention, and such modifications and adaptations are intended to be within the scope of the invention.