Method and system for detecting different components in a mixed gas

Abstract

This invention belongs to the field of gas detection technology and provides a method for detecting different components in a mixed gas. The method includes: passing a mixed gas sample into an adsorption tube and subjecting the adsorption tube to thermal desorption by heating; recording the dynamic response curve during the thermal desorption process in real time and extracting characteristic parameters from the dynamic response curve; linearly fitting the characteristic parameters to standard templates for different gases using the non-negative least squares method and calculating the fitting evaluation index; and determining each gas component in the mixed gas based on the fitting evaluation index and principal component analysis. The advantages of this invention are that it can distinguish different components based on multidimensional peak characteristics rather than a single response value, thereby solving the problems of significant cross-interference and insufficient selectivity in existing sensors, and achieving high-dimensional detection without relying on expensive mass spectrometers.

Description

Technical Field

[0001] This invention relates to the field of gas detection technology, and in particular to a method and system for detecting different components in a mixed gas. Background Technology

[0002] While existing sensors can effectively respond to volatile organic compounds (VOCs) in exhaled breath, they face serious selectivity limitations in complex backgrounds. The response signals of interfering gases such as VOCs overlap with those of the target components, resulting in significant cross-interference and making it difficult to meet clinical needs such as exhaled breath detection.

[0003] Traditional steady-state detection methods provide only a single concentration signal and cannot effectively distinguish between multiple components in a superimposed background. While existing thermal desorption techniques can enrich low-concentration volatile components, they generally suffer from unoptimized key parameters such as heating rate and carrier gas flow rate, limited characteristic parameters, and difficulties in quantitatively evaluating nonlinear interactions in mixed systems. This results in limited discriminative ability against complex exhalation backgrounds and prevents direct application to sensor selectivity enhancement. Therefore, there is an urgent need to develop a preprocessing method that can transform complex samples into time-resolved peak-shaped features, has high parameter dimensionality, and maintains good interpretability even in complex backgrounds. Summary of the Invention

[0004] The present invention aims to solve the above problems by optimizing desorption conditions, extracting multidimensional peak shape characteristic parameters, and combining non-negative least squares fitting (NNLS) and principal component analysis (PCA) to achieve component differentiation of VOCs in mixed gases (especially exhaled gas).

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A method for detecting different components in a gas mixture, comprising: The mixed gas sample is passed into the adsorption tube, and the adsorption tube is heated for thermal desorption. The dynamic response curve during the thermal desorption process is recorded in real time, and the characteristic parameters in the dynamic response curve are extracted. The characteristic parameters are used to characterize the peak shape characteristics of the main peak during the thermal desorption process. The non-negative least squares method was used to linearly fit the characteristic parameters to standard templates for different gases, and the fitting evaluation index was calculated. The gas components in the gas mixture were determined based on the fitting evaluation index and principal component analysis.

[0006] Furthermore, the adsorption tube is filled with Tenax adsorbent.

[0007] Furthermore, the characteristic parameters include at least one of peak temperature, peak area, peak width, skewness used to characterize peak asymmetry, and kurtosis.

[0008] Furthermore, the linear fitting is a non-negative least squares method with prior constraints, where the prior constraints are represented by a prior value, and the same prior value is applied to the fitting coefficients of each component.

[0009] Furthermore, the fitting evaluation index includes at least one of the following: coefficient of determination R², root mean square error, and residual area ratio.

[0010] The present invention also provides a detection system for different components in a mixed gas, comprising: The sample input unit includes a gas collection bag for supplying the gas of the sample to be tested; Background gas unit, which includes an inert gas source and is used to provide background gas as carrier gas; The thermal desorption unit includes an adsorption tube, the input end of which is connected to the sample input unit and the background gas unit respectively. The detection unit has its input end connected to the output end of the adsorption tube; it is configured to record the dynamic response curve during the thermal desorption process in real time, and to use the non-negative least squares method to linearly fit the characteristic parameters with standard templates of different gases, and to calculate the fitting evaluation index; and to determine the gas components in the mixed gas based on the fitting evaluation index and principal component analysis.

[0011] Furthermore, it also includes: a three-way valve having a first air inlet, a second air inlet, and a common air outlet; the first air inlet is connected to the gas collection bag, and the second air inlet is connected to the inert gas source; wherein, the three-way switching valve is used to selectively connect the gas collection bag or the inert gas source to the adsorption tube.

[0012] Furthermore, a vacuum pump is installed between the first air inlet and the gas collection bag, and the vacuum pump is configured to input the sample gas in the gas collection bag into the first air inlet; a flow meter is installed between the second air inlet and the inert gas source, and the flow meter is configured to calculate the gas flow rate input from the inert gas source into the second air inlet; the thermal desorption unit includes a temperature controller that is thermally connected to the adsorption tube, and the temperature controller is configured to programmatically heat up or cool down the adsorption tube.

[0013] Furthermore, the inert gas source is introduced into the adsorption tube at a flow rate of 30–100 sccm, and the temperature controller is configured with a programmed heating rate of 2–20 ℃ / min.

[0014] Furthermore, in the detection unit, a photoionization detector is used to record the dynamic response curve during the thermal desorption process in real time.

[0015] Compared with the prior art, the present invention has at least the following beneficial effects: (1) The single steady-state concentration signal of traditional sensors is transformed into a dynamic response curve, and multidimensional characteristic parameters are extracted from it. These characteristic parameters can effectively characterize the unique behavior of different chemical types of VOCs during the desorption process. This enables the differentiation of different components in mixed gases, especially in the background of exhaled gas with severe signal overlap, based on multidimensional peak characteristics rather than a single response value, thereby solving the problems of significant cross-interference and insufficient selectivity of existing sensors; (2) A simple and low-cost detection scheme is provided, which can achieve high-dimensional detection without relying on expensive mass spectrometers. Without significantly increasing the system cost and complexity, it greatly improves the ability of existing equipment to distinguish and detect complex gas mixtures; (3) The non-negative least squares method with prior constraints was innovatively used to linearly fit the mixed response curve with the standard templates of each single component, and the evaluation index was calculated. This method realizes the quantitative characterization and evaluation of nonlinear interactions in the mixed thermal desorption system, and provides a clear evaluation basis and optimization direction for subsequent modification of adsorbent materials and optimization of desorption procedures to suppress interference; (4) Even after introducing a complex expiratory matrix background, the first peak (main desorption peak) of the response curve of the target VOCs still maintains a clear peak shape, a concentrated peak width, and a good response to concentration changes. The method provided by this invention can stably extract multidimensional feature signals of target VOCs from real biological samples containing a large number of interfering components, ensuring the effectiveness and robustness of the method in real application scenarios. Attached Figure Description

[0016] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0017] Figure 1 This is a schematic diagram of the detection system provided in this embodiment; Figure 2 This is a flowchart of the detection method provided in this embodiment; Figure 3 This is a schematic diagram of the mixed response curves of six VOCs at different flow rates provided in this embodiment; Figure 4 This is a schematic diagram of the individual and mixed response curves of six VOCs at different heating rates provided in this embodiment; Figure 5 This is a schematic diagram of the PCA analysis scores for different heating rates provided in this embodiment; Figure 6 This is a schematic diagram showing the comparison of six VOCs superimposed and mixed at different heating rates provided in this embodiment; Figure 7 This is a schematic diagram of the fitting results under different heating rates provided in this embodiment; Figure 8 This is a schematic diagram of the response curves of six VOCs-exhalation mixture systems under the conditions of 5°C heating and 50 sccm flow rate provided in this embodiment; Figure 9 This is a schematic diagram showing the fitting results provided in this embodiment substituted into the VOCs-exhalation system. Detailed Implementation

[0018] The following are specific embodiments of the present invention, and the technical solutions of the present invention will be further described in conjunction with the accompanying drawings. However, the present invention is not limited to these embodiments.

[0019] like Figure 1 and Figure 2 As shown, this embodiment provides a detection system and detection method, which includes: The sample input unit includes a gas collection bag for supplying the gas for the sample to be tested. The background gas unit includes an inert gas source and is used to provide the background gas as a carrier gas. The thermal desorption unit includes an adsorption tube filled with Tenax adsorbent; the input end of the adsorption tube is connected to both the sample input unit and the background gas unit. The detection unit has its input end connected to the output end of the adsorption tube.

[0020] Preferably, the Tenax adsorbent is Tenax TA or its equivalent hydrophobic porous polymer adsorbent.

[0021] It also includes a three-way valve with a first air inlet, a second air inlet, and a common air outlet. The first air inlet is connected to the gas collection bag, and the second air inlet is connected to the inert gas source; wherein, the three-way switching valve is used to selectively connect the gas collection bag or the inert gas source to the adsorption tube.

[0022] Furthermore, a vacuum pump is installed between the first air inlet and the gas collection bag, and the vacuum pump is configured to input the sample gas from the gas collection bag into the first air inlet. A flow meter is installed between the second air inlet and the inert gas source, and the flow meter is configured to calculate the gas flow rate input from the inert gas source into the second air inlet. The thermal desorption unit includes a temperature controller thermally connected to the adsorption tube, and the temperature controller is configured to programmatically heat up or cool down the adsorption tube.

[0023] The detection system mainly consists of a gas collection bag, a three-way valve, a vacuum pump, a flow meter, an adsorption tube, and a temperature controller. During the experiment, the three-way valve switches between the sample enrichment path and the background gas path to achieve adsorption enrichment and desorption testing.

[0024] During the adsorption and enrichment stage, the collected gas samples are stored in a gas collection bag and connected to a vacuum pump. Gas sample collection can be carried out through a gas-liquid mixing system, with a total mixing volume of 2L. Calculations are made based on the standard that 1 ppb gas equals 1 nl / ml. The required concentration of liquid is collected from 2L of air and converted into gas using the gas-liquid mixing system.

[0025] By adjusting the three-way valve, the gas sample is introduced into the adsorption tube by a pump, and enrichment is carried out at a set flow rate for 20 minutes. During this process, the target component in the sample is adsorbed by the filling material inside the adsorption tube, thus achieving gas enrichment. The gas concentration used in the testing stages at different heating rates and flow rates was 500 ppb.

[0026] After adsorption, the three-way valve is readjusted to switch the gas path to an inert gas source, and nitrogen is introduced through a flow meter as the carrier gas to desorb the adsorption tube. The target components adsorbed on the material surface are gradually desorbed under the action of the carrier gas and enter the subsequent detection unit, and their dynamic response curves are recorded.

[0027] The detection unit is configured to record the dynamic response curve during the thermal desorption process in real time, and to use non-negative least squares method to linearly fit the characteristic parameters with standard templates of different gases and calculate the fitting evaluation index; and to determine the gas components in the mixed gas based on the fitting evaluation index and principal component analysis.

[0028] Characteristic parameters are used to characterize the peak shape of the main peak during thermal desorption, and preferably include at least one of peak temperature, peak area, peak width, skewness (used to characterize peak asymmetry), and kurtosis. The linear fitting is performed using a non-negative least squares method with prior constraints, where the prior constraints are represented by a prior value, and the same prior value is applied to the fitting coefficients of each component. Fit evaluation metrics include the coefficient of determination (R²), root mean square error (RMSE), and residual area ratio.

[0029] Preferably, in the detection unit, a photoionization detector is used to record the dynamic response curve during the thermal desorption process in real time.

[0030] Furthermore, six VOC gases—benzene, aniline, xylene, n-butanol, n-heptane, and n-pentanal—were selected for testing, covering different chemical types such as aromatic hydrocarbons, aromatic amines, alcohols, aldehydes, and alkanes. Moreover, studies on exhaled VOCs related to lung cancer have shown that these six gases may serve as potential biomarkers.

[0031] Under a constant heating rate of 10℃, the thermal desorption response curves of the mixed samples at five flow rates of 10, 30, 50, 60, and 100 sccm were examined. Figure 3 As shown, different flow rates have a significant impact on the bimodal structure of the mixed sample. At 10 sccm, both the first and second peaks are located in the high-temperature region. As the flow rate increases to 30 sccm and 50 sccm, the bimodal structure gradually becomes clearer, and the first peak is significantly enhanced. When the flow rate continues to increase to 100 sccm, the second peak disappears, indicating that excessively high flow rates are not conducive to the retention of the hysteresis desorption characteristics in the later stages.

[0032] Table 1 shows the peak temperature, peak area, peak width, skewness, and kurtosis of peaks 1 and 2 under different flow rates. As can be seen from the table, if the areas of peaks 1 and 2 are added together, the total areas are approximately 16.885, 30.583, 32.256, 10.668, and 7.382, respectively, with the largest total response at 50 sccm.

[0033] Table 1. Bimodal characteristic parameters at different flow velocities peak temperature 250.000 146.333 110.667 116.333 102.167 Peak area 8.088 22.783 30.154 8.303 7.382 Peak width 259.000 166.000 199.000 154.000 207.000 Skewness -0.081 0.037 -0.416 -0.487 -0.190 Kudo -1.515 -1.452 -1.089 -1.346 -1.369 Peak 2 10sccm 30sccm 50sccm 60sccm 100sccm peak temperature 250.000 186.167 151.000 157.667 none Peak area 8.797 7.800 2.102 2.365 none Peak width 211.000 176.000 185.000 171.000 none Skewness 0.891 -0.249 -0.105 0.073 none Kudo -0.646 -1.366 -1.550 -1.389 none From the peak temperatures, peak 1 gradually decreased from 250.0℃ at 10 sccm to 146.333℃, 110.667℃, 116.333℃, and 102.167℃ at 30, 50, 60, and 100 sccm, respectively; peak 2 decreased from 250.000℃ to 186.167℃, 151.000℃, and 157.667℃, respectively. This indicates that as the flow rate increases, the efficiency of sample transport from the adsorption tube to the detector improves, and the desorption characteristics shift forward overall. At 10 sccm, both peak temperatures reached 250℃, indicating that sample migration and desorption processes are slower at low flow rates, and the peak positions shift backward overall, which is not conducive to further analysis of peak temperature differences.

[0034] In terms of peak width, peak 1 is relatively narrow, with widths of 166 and 154 at 30 sccm and 60 sccm, respectively. Peak 2 fluctuates less within the 30-60 sccm range, ranging from 171 to 185, indicating that the bimodal morphology is relatively stable under moderate flow velocities. Skewness and kurtosis results show that the symmetry and sharpness of the bimodal peaks differ somewhat under different flow velocities, but their variation patterns are not as pronounced as those of peak area and peak temperature. Overall, skewness and kurtosis remain primarily auxiliary indicators in the analysis.

[0035] Based on the overall response intensity, main peak stability, and consistency with subsequent analyses of samples with complex backgrounds, the highest overall response and the largest first peak area were observed at 50 sccm, indicating that this flow rate can maintain a clear main desorption peak shape while ensuring a strong signal output. In contrast, at 10 sccm, the overall desorption shifted significantly, which was unfavorable for subsequent peak temperature comparisons; at 60 sccm and above, the peak shape in the later stages began to weaken significantly, indicating that high flow rates enhance the instability of the later desorption process. Therefore, flow rate changes have a more significant impact on the second peak, while the first peak maintained good response intensity and comparability under moderate flow rate conditions. Thus, 50 sccm is the preferred flow rate.

[0036] Under a flow rate of 50 sccm, such as Figure 4 The figure shows the thermal desorption response curves of six single-component and mixed VOC samples at different heating rates. As can be seen from the figure, the heating rate has a significant impact on both the peak position and shape of the response curves. With the heating rate increasing from 2℃ / min to 20℃ / min, the overall desorption process of the samples gradually changes from slow and dispersed to rapid and concentrated. The peak widths of most components decrease, and the peak positions of some samples shift to the higher temperature region. At 2℃ / min, the peak shapes of most samples broaden significantly, and some components exhibit strong tailing. At 20℃ / min, although the peak shapes are sharper, the peak positions of many samples are concentrated near the upper limit of the program, indicating that a high heating rate compresses the differences in desorption temperature ranges between different components.

[0037] Table 2 shows the peak temperature, peak area, peak width, skewness, and kurtosis of the six VOCs and their mixtures at different heating rates. As can be seen from the table, peak temperature, peak area, and peak width change significantly with the heating rate, while skewness and kurtosis are more used to describe peak shape differences.

[0038] Table 2 Characteristic parameters at different heating rates peak temperature 61.567 185.533 139.467 140.767 93.967 78.033 113.100 Peak area 1.019 26.033 0.411 1.928 4.322 11.708 3.476 Peak width 267.000 197.000 430.000 291.000 647.000 576.000 720.000 Skewness -0.322 0.044 -0.142 0.194 -0.207 0.077 -0.057 Kudo -1.220 -1.478 -1.361 -1.419 -1.316 -1.539 -1.437 5℃ mix benzene aniline xylene n-Butanol n-Heptane n-Pentanol peak temperature 146.333 140.833 146.000 149.667 127.167 150.833 147.750 Peak area 4.691 31.554 2.607 2.935 12.594 8.773 2.830 Peak width 291.000 284.000 266.000 278.000 323.000 261.000 344.000 Skewness 0.042 0.575 -0.231 -0.231 -0.051 1.015 -0.217 Kudo -1.200 -1.190 -1.350 -1.454 -1.437 -0.386 -1.379 10℃ mix benzene aniline xylene n-Butanol n-Heptane n-Pentanol peak temperature 168.167 178.667 149.667 214.500 195.167 208.167 194.000 Peak area 3.387 90.491 6.193 3.696 5.678 31.406 1.805 Peak width 200.000 185.000 517.000 178.000 234.000 316.000 310.000 Skewness 0.004 0.619 0.026 -0.367 0.276 0.177 -0.261 Kudo -1.423 -1.448 -1.180 -1.208 -1.344 -1.448 -1.253 20℃ mix benzene aniline xylene n-Butanol n-Heptane n-Pentanol peak temperature 250.000 250.000 250.000 250.000 250.000 250.000 250.000 Peak area 5.821 122.348 12.363 6.229 5.420 3.935 2.275 Peak width 129.000 143.000 130.000 152.000 263.000 128.000 270.000 Skewness 0.572 0.895 0.497 0.728 -0.288 0.593 0.020 Kudo -1.190 -0.698 -1.270 -0.724 -1.472 -1.022 -1.433 As can be seen from the peak temperatures of each sample in the table, the peak temperature distribution of each component is relatively low at 2℃ / min, with the peak temperature of the mixed sample being only 61.567℃, the peak temperatures of n-heptane and n-butanol being 78.033℃ and 93.967℃ respectively, while the peak temperature of benzene reaches 185.533℃; at 5℃ / min, the peak temperatures of most components are concentrated around 140~151℃; at 10℃ / min, the peak temperature distribution of each component extends to 149.667~214.500℃; at 20℃ / min, the peak temperatures of all six single-component samples reach 250℃, indicating that the peak temperature characteristics under this condition are saturated, which is not conducive to further distinguishing different components.

[0039] The changes in peak area for each component show that the peak area of ​​benzene increased from 26.033 at 2℃ / min to 90.491 at 10℃ / min, reaching 122.348 at 20℃ / min; the peak area of ​​aniline increased from 0.411 to 12.363; while the peak area of ​​n-heptane reached 31.406 at 10℃ / min, but decreased to 3.935 at 20℃ / min. These results indicate that although peak area can reflect the release intensity, the optimal desorption rhythm differs for different components, and therefore cannot be used as the sole basis for optimizing the heating rate.

[0040] The peak width results show that at 2℃ / min, most components have relatively large peak widths, with n-butanol, n-heptane, and n-pentanal reaching 647, 576, and 720 respectively, indicating a relatively dispersed desorption process. At 5℃ / min, the peak widths generally decrease to between 261 and 344. At 10℃ / min, the peak widths of most components continue to decrease, but aniline still reaches a peak width of 517, indicating that it still exhibits significant tailing under this condition. At 20℃ / min, the peak widths of most components further decrease, but at the same time, all peak temperatures reach their upper limits. This indicates that low heating rates tend to cause peak broadening, while excessively high heating rates, although narrowing the peak width, will result in a loss of peak temperature resolution.

[0041] Based on the skewness and kurtosis results, the skewness of each sample mainly ranges from -0.367 to 1.015, while the kurtosis mainly ranges from -1.539 to -0.386. Their variation patterns are not as intuitive as those of peak temperature, peak area, and peak width, but they can still help explain peak shape changes. For example, at 5℃ / min, the skewness of n-heptane is 1.015, indicating a significant high-temperature tailing; at 20℃ / min, the skewness of benzene reaches 0.895, indicating that the peak shape of some samples is more right-biased at high heating rates. Overall, skewness and kurtosis are more suitable as auxiliary criteria for peak shape judgment, used to supplement the explanation of peak symmetry and tailing changes.

[0042] The results above show that although bimodal structures may appear in gas samples during thermal desorption, the two peaks are not entirely equivalent in terms of stability and interpretability. The first peak is usually located in the lower temperature range, more closely resembling the main release process of the gas sample as it enters the heating stage after adsorption. Its peak position and shape are relatively more stable under different conditions, and it is also easier to compare and analyze with single-component templates. In contrast, the second peak appears more frequently in the higher temperature range and is easily affected by factors such as hysteresis desorption, re-adsorption, competition from background components, and mass transfer redistribution under high-temperature conditions. Its appearance and shape changes are more uncertain. Although the second peak can be observed under certain conditions, its intensity, peak position, and integrity are not always stable. Therefore, it is more suitable as an auxiliary phenomenon to explain multi-stage release behavior in complex backgrounds, rather than as the main subject of subsequent analysis.

[0043] like Figure 5 The figure shows the PCA score plots of gas characteristic parameters at different heating rates. As can be seen from the figure, the distributions of the six individual VOCs in the principal component space differ significantly at different heating rates, indicating that changes in the heating rate cause a shift in the overall distribution of thermal desorption characteristic parameters.

[0044] To evaluate the dispersion of the six VOCs, the average two-point distance (D) was used. avg ), minimum two-point distance (D) min ), the average distance from the centroid (D) c The three indicators were used for evaluation. The results show that the sample dispersion was best under the heating condition of 5℃ / min. The results are shown in Table 3. Table 3 Evaluation of PCA Results 2℃ / min 2.0539 0.3798 1.3630 Overall concentration 5℃ / min 3.0638 1.1101 2.0100 Dispersed and balanced 10℃ / min 3.0744 1.0277 2.0295 Scattered with neighboring 20℃ / min 3.2069 0.1129 2.0145 Local clustering is obvious like Figure 6 The figure shows a comparison between the superimposed peaks of each component and the mixed peak. The thermal desorption curves of the mixed sample at different heating rates are not entirely consistent with the superimposed curves of the individual components, indicating the existence of competitive adsorption and cooperative desorption behaviors in the mixed system. This result suggests that the selection of heating rates should not be based solely on the dispersion of individual components, but should also be comprehensively judged in conjunction with the interpretability of the overall peak shape of the mixed system.

[0045] To further determine the interpretability of the mixed peaks for single-component templates under different heating rates, non-negative least squares (NNLS) was used to fit and analyze the response curves. Let the response value of the mixed sample at the nth sampling point be y. n The response value of the i-th VOC under the same conditions is x. i,n Then the mixed peak fitting model can be expressed as: ; In the formula, To fit the obtained mixed peak response value, a i Let be the fitting coefficient of the i-th VOC to the mixed peak. Since the contribution of each component to the mixed peak should be positive, a non-negative constraint 'a' is applied to all coefficients. i ≥0.

[0046] To avoid the sparse solutions produced by conventional NNLS, which would compress some component coefficients to 0, a non-negative fitting model with prior constraints is further used for comparison, as shown below: ; The fitting coefficient results are shown in Table 4: Table 4 Fit coefficient results 2℃ 0.001000 0.009877 0.009409 0.009313 0.009575 0.009959 0.000205 5℃ 0.028487 0.001000 0.004450 0.037126 0.034822 0.009610 0.000114 10℃ 0.094673 0.001000 0.022534 0.028321 0.052420 0.024713 0.000352 20℃ 0.052727 0.007461 0.010512 0.007856 0.011181 0.013453 0.001164 The results of the fitting evaluation metrics are shown in Table 5: Table 5. Results of Fit Evaluation Indicators 2℃ -0.108988069 0.000975502 1.121494626 5℃ 0.964340765 0.000617638 0.232968065 10℃ 0.931784467 0.001037504 0.367556614 20℃ 0.965747518 0.001431567 0.28466165 Figure 7 The fitting results show that at a low heating rate of 2℃ / min, the mixed peak is difficult to reconstruct effectively from the six single-component responses through a simple non-negative linear combination, and the mixed system deviates significantly from the linear superposition relationship. At 5℃ / min, the mixed peak can be reconstructed to a high extent from the single-component template, and the fitting accuracy is better among the four heating rates. At 10℃ / min, the mixed peak can still be reconstructed well, and the residual area ratio is not too low. The goodness of fit is high at 20℃ / min, but its discrimination is more reflected in the overall matching after curve compression, and it cannot be used as the optimal condition due to peak temperature characteristic saturation.

[0047] Therefore, a heating rate of 5 °C / min produces the most discrete characteristics in the sample under all heating rate conditions, making it suitable for sample separation. Thus, 5 °C / min and a flow rate of 50 sccm are the preferred operating conditions.

[0048] In addition, such as Figure 8 As shown, the overall response after mixing with exhaled gas is significantly enhanced compared to the nitrogen background, indicating that the introduction of the exhaled gas background significantly alters the retention and release behavior of the sample in the adsorbent material. The curves exhibit multi-stage release characteristics, but combined with the aforementioned analysis results of different flow rates and heating rates, the description mainly focuses on the peak area, peak temperature, peak width, and related parameters of the first peak of the VOC-exhaled gas system to evaluate its feature extraction capability in complex backgrounds.

[0049] Table 6 Characteristic parameters of VOC-exhalation system peak temperature 209.2 149.8 225.5 193.8 231.5 234.0 222.7 215.7 228.2 181.5 Peak area 29.1 42.5 74.4 70.5 84.6 149.5 159.7 144.0 453.1 649.8 Peak width 169.0 165.0 167.0 165.0 188.0 179.0 158.0 164.0 171.0 224.0 Skewness -0.2 -0.1 0.8 0.0 0.5 0.3 -0.2 -0.2 -0.2 -0.3 Kudo -1.2 -1.4 -0.9 -1.3 -1.3 -1.4 -1.3 -1.1 -1.4 -1.4 Table 6 shows the peak temperature, peak area, peak width, skewness, and kurtosis of the first peak in the VOC-exhalation system. As the VOC-exhalation system concentration increases from 100 ppb to 1000 ppb, the peak area of ​​the first peak generally shows an increasing trend, indicating a good response to concentration changes. While the peak area fluctuates somewhat within the 300–800 ppb range, it still maintains an overall upward trend. The increase is more pronounced at 900 ppb and 1000 ppb, indicating a more significant enhancement in the first peak response at higher concentrations.

[0050] From the peak temperature variation, the first peak temperature ranges from 149.8 to 234.0℃, exhibiting a relatively wide overall fluctuation range, indicating that the first peak retains a fairly obvious temperature variation characteristic. Compared with the nitrogen background, this temperature range corresponds significantly to the dominant desorption range of the pure mixed peak under the 5℃ / min condition mentioned earlier, indicating that the first peak of the VOC-exhalation system inherits the same low-temperature release characteristics to some extent. Meanwhile, the peak temperature does not show a strictly monotonic pattern with concentration, suggesting that the introduction of the exhalation background further affects the retention and release behavior of multi-component VOCs in the adsorbent material, causing a certain degree of peak position adjustment at different concentrations.

[0051] The peak width results show that the first peak's width is mainly distributed between 158.0 and 224.0. Except for a slight increase in peak width at 1000 ppb, the overall variation in the first peak's width is relatively limited across other concentration ranges, indicating that the first peak maintains a relatively stable peak shape concentration even in complex expiratory backgrounds. Skewness is mainly distributed between -0.3 and 0.8, and kurtosis is mainly distributed between -1.4 and -0.9, indicating that the overall peak shape of the first peak is relatively flat. While there is some degree of high-temperature tailing under certain concentration conditions, no significant distortion is observed. This suggests that although the first peak is affected by the expiratory matrix in complex backgrounds, it still exhibits good peak shape stability and is more suitable as a subject for comparative analysis with pure VOC mixed templates.

[0052] The peak area, peak temperature, peak width, and peak shape parameters show that the first peak of the VOC-exhalation system maintains good peak concentration and repeatability even in complex expiratory backgrounds. Although the introduction of the expiratory matrix causes some disturbance to the peak position and shape, the overall variation pattern of the first peak is relatively clear, and it can well reflect the dominant desorption behavior of multi-component VOCs in complex backgrounds. Therefore, it is more suitable as the main characteristic peak for subsequent complex background differentiation analysis and selective improvement studies.

[0053] The fitting formula with prior constraints will be compared with the above experimental data. The results before and after the comparison are as follows: Figure 9 As shown, the calculated coefficient of determination R² = 0.8983 and root mean square coefficient RMSE = 0.4692. Therefore, this method can reconstruct the peak shape of the mixed gas signal relatively well based on the standard fitting equations of each component.

[0054] The specific embodiments described herein are merely illustrative of the spirit of the invention. Those skilled in the art to which this invention pertains may make various modifications or additions to the described specific embodiments or use similar methods to substitute them, without departing from the spirit of the invention or exceeding the scope defined by the appended claims.

[0055] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indication will also change accordingly.

[0056] Furthermore, in this invention, descriptions involving terms such as "first," "second," and "a" are for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0057] In this invention, unless otherwise explicitly specified and limited, the terms "connection," "fixed," etc., should be interpreted broadly. For example, "fixed" can mean a fixed connection, a detachable connection, or an integral part; it can mean a mechanical connection or an electrical connection; it can mean a direct connection or an indirect connection through an intermediate medium; it can mean the internal communication of two components or the interaction between two components, unless otherwise explicitly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0058] Furthermore, the technical solutions of the various embodiments of the present invention can be combined with each other, but only if they are feasible for those skilled in the art. If the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.

Claims

1. A method for detecting different components in a mixed gas, characterized in that, include: The mixed gas sample is passed into the adsorption tube, and the adsorption tube is heated for thermal desorption. The dynamic response curve during the thermal desorption process is recorded in real time, and the characteristic parameters in the dynamic response curve are extracted. The characteristic parameters are used to characterize the peak shape characteristics of the main peak during the thermal desorption process. The non-negative least squares method was used to linearly fit the characteristic parameters to standard templates for different gases, and the fitting evaluation index was calculated. The gas components in the mixed gas are determined based on the fitting evaluation index and principal component analysis.

2. The method for detecting different components in a mixed gas according to claim 1, characterized in that, The adsorption tube is filled with Tenax adsorbent.

3. The method for detecting different components in a mixed gas according to claim 1, characterized in that, The characteristic parameters include at least one of peak temperature, peak area, peak width, skewness used to characterize peak asymmetry, and kurtosis.

4. The method for detecting different components in a mixed gas according to claim 1, characterized in that, The linear fitting is a non-negative least squares method with prior constraints, whereby the prior constraints are represented by a prior value, and the same prior value is applied to the fitting coefficients of each component.

5. The method for detecting different components in a mixed gas according to claim 1, characterized in that, The fitting evaluation index includes at least one of the following: coefficient of determination R², root mean square error, and residual area ratio.

6. A detection system for different components in a mixed gas, characterized in that, include: The sample input unit includes a gas collection bag for supplying the gas of the sample to be tested; Background gas unit, which includes an inert gas source and is used to provide background gas as carrier gas; A thermal desorption unit includes an adsorption tube, the input end of which is connected to the sample input unit and the background gas unit respectively. A detection unit, wherein the input end of the detection unit is connected to the output end of the adsorption tube; It is configured to record the dynamic response curve during the thermal desorption process in real time, and to use non-negative least squares method to linearly fit the characteristic parameters with standard templates of different gases and calculate the fitting evaluation index; and to determine each gas component in the mixed gas based on the fitting evaluation index and principal component analysis.

7. The detection system for different components in a mixed gas according to claim 6, characterized in that, Also includes: A three-way valve has a first air inlet, a second air inlet, and a common air outlet. The first air inlet is connected to the gas collection bag, and the second air inlet is connected to the inert gas source; wherein, the three-way switching valve is used to selectively connect the gas collection bag or the inert gas source to the adsorption tube.

8. The detection system for different components in a mixed gas according to claim 7, characterized in that, A vacuum pump is provided between the first air inlet and the gas collection bag, and the vacuum pump is configured to input the sample gas in the gas collection bag into the first air inlet; a flow meter is provided between the second air inlet and the inert gas source, and the flow meter is configured to calculate the gas flow rate input from the inert gas source into the second air inlet; the thermal desorption unit includes a temperature controller thermally connected to the adsorption tube, and the temperature controller is configured to programmatically heat up or cool down the adsorption tube.

9. The detection system for different components in a mixed gas according to claim 8, characterized in that, The inert gas source is introduced into the adsorption tube at a flow rate of 30–100 sccm, and the temperature controller is configured with a programmed heating rate of 2–20 ℃ / min.

10. The detection system for different components in a mixed gas according to claim 6, characterized in that, In the detection unit, a photoionization detector is used to record the dynamic response curve during the thermal desorption process in real time.

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