Waste gas detection method and device based on gas chromatography

Abstract

The invention discloses an exhaust gas detection method and device based on gas chromatography, and relates to the technical field of exhaust gas detection. The difference between a current chromatographic response signal and a reference signal is recorded and compared in real time in each detection process, and a matching degree index is calculated; the method can be used for effectively identifying and compensating the phenomena of'concentration jump 'and'residue trailing' caused by nonlinear adsorption and desorption in a chromatographic system. Through reverse intervention operation, such as increasing the channel temperature and increasing the carrier gas flow velocity, fitting correction is carried out on the signal, the method can eliminate the influence of historical residues, a misleading detection result is avoided, and the accuracy and reliability of detection are remarkably improved. The method effectively solves the problems of false alarm, missing alarm and wrong regulation and control decision caused by a chromatographic memory effect in the prior art, and ensures accurate monitoring of pollutant concentration and more reasonable regulation and control decision.

Description

Technical Field

[0001] This invention relates to the field of exhaust gas detection technology, specifically to an exhaust gas detection method and apparatus based on gas chromatography. Background Technology

[0002] In environmental monitoring and industrial emission control, gas chromatography-based waste gas detection methods have become a core means of identifying and quantifying pollutants such as volatile organic compounds (VOCs). This method typically involves collecting waste gas samples, pre-treating them (e.g., filtration, drying, enrichment), and then injecting them into a gas chromatograph. A carrier gas carries the sample into the chromatographic column to achieve component separation. Finally, qualitative and quantitative analysis results are output using devices such as flame ionization detectors (FID) and thermal conductivity detectors (TCD). Benefiting from its high selectivity, high sensitivity, and good linear response, this technology is widely used in various fields such as stationary pollution source emissions, indoor air quality assessment, and emergency environmental event response, demonstrating significant advantages in monitoring accuracy and method stability.

[0003] However, in long-term practical applications, existing gas chromatography-based waste gas detection methods have a subtle yet far-reaching problem when dealing with certain polar organic components (such as aldehydes and phenols): because these substances are prone to nonlinear adsorption and slow desorption within the sampling pipe or the inner wall of the chromatographic system, this often leads to concentration jumps or residual tailing phenomena in the detection data. Even if the concentration of the target component in the actual sample has changed, the system may still remember the previous pollution state and continue to output misleading detection results. This problem, known as the chromatographic memory effect, not only seriously interferes with the accurate judgment of pollution fluctuations but may also lead to false alarms, missed alarms, or incorrect control decisions, urgently requiring the development of effective identification and compensation mechanisms to address it. Summary of the Invention

[0004] The purpose of this invention is to solve the problem mentioned in the background art that existing gas chromatography-based waste gas detection methods, when processing polar organic components, are prone to concentration jumps or residual tailing phenomena due to their nonlinear adsorption and slow desorption on the inner wall of the system, resulting in misleading detection results, thereby interfering with the true judgment of pollution fluctuations and potentially causing false alarms, omissions, or incorrect decisions. Therefore, this invention proposes a gas chromatography-based waste gas detection method and device.

[0005] A first aspect of this invention provides a method for detecting exhaust gas based on gas chromatography, the method comprising: S1: Inject standard gas samples of each target pollutant into the gas chromatograph and record the chromatographic response signals of the target pollutants at different concentrations as the reference chromatographic response signals. S2: After each round of exhaust gas sample is injected into the gas chromatograph, the chromatographic response signal is recorded as the current chromatographic response signal; S3: Calculate a matching index to reflect the degree of residual risk based on the reference chromatographic response signal and the current chromatographic response signal; S4: If the matching degree index is higher than the preset threshold, a reverse intervention operation is performed to fit and correct the chromatographic response signal; the reverse intervention operation includes increasing the channel temperature and increasing the carrier gas flow rate; S5: Output the detection result of the current sample based on the corrected chromatographic response signal, and use it as the final detection output of the current sample.

[0006] Optionally, the step of calculating the matching index reflecting the degree of relevance to residual risk based on the reference chromatographic response signal and the current chromatographic response signal is as follows: The dynamic trajectory deformation matching index and signal complexity matching index are calculated based on the reference chromatographic response signal and the current chromatographic response signal. The residual risk index is obtained by adding the dynamic trajectory deformation matching index and the signal complexity matching index, and is used as an indicator to reflect the degree of matching of residual risk.

[0007] Optionally, the calculation steps for the dynamic trajectory deformation matching index are as follows: After each round of exhaust gas sample is injected into the gas chromatograph, the time-amplitude sequence of the current chromatographic response signal is recorded; The signal after the autonomous peak in the current chromatographic response signal is taken as the falling phase signal; for the time-amplitude sequence corresponding to the falling phase signal, the amplitude difference and time difference between each time point and its previous time point are calculated, and the amplitude difference is divided by the time difference to obtain the local slope of each time point; The quadratic polynomial fitting method is used to fit the signal during the descent phase to obtain the fitting curve. For each time point, the deviation between the fitted curve and the actual signal at each time point is used to obtain the nonlinear factor of the signal at the corresponding time point. The Jacobian transform is used to calculate the derivative of the amplitude and time change of the signal during the descent phase at each time point, so as to obtain the Jacobian transform value at each time point. The local slope, nonlinear factor and Jacobian transform metric at each time point are added together to obtain the deformation metric at the corresponding time point. The deformation metrics at all time points in the descent phase signal are added together to obtain the deformation value of the current sample, which is recorded as the first deformation value. The deformation value of the reference chromatographic response signal is calculated as the second deformation value. The first deformation value is divided by the second deformation value to obtain the dynamic trajectory deformation matching index.

[0008] Optionally, the calculation steps for the signal complexity matching index are as follows: The signal following the autonomous peak in the current chromatographic response signal is taken as the descending phase signal. For the time-amplitude sequence corresponding to the falling phase signal, the signal values ​​of the continuous sampling points in the falling phase are symbolized. For the signal values ​​of two adjacent sampling points, if the value of the later sampling point is greater than the value of the earlier sampling point, it is marked as rising; if the two values ​​are equal, it is marked as stationary; if the later point is less than the earlier point, it is marked as falling. This generates a set of change direction sequences containing only the three types of symbols: rising, falling, and stationary. Multiple continuous sliding subsequences are constructed in the sequence of changing directions with a fixed length as the unit, forming multiple local change pattern units of the same length; the number of all different change pattern units is counted, and the occurrence frequency of each type of pattern unit in the whole sequence is calculated respectively; Multiply the frequency of occurrence of each pattern by its own logarithm and then sum them to obtain the distribution uncertainty value of each change pattern; use the negative value of the distribution uncertainty value as the uncertainty value; The uncertainty value is used as the numerator, the logarithm of the number of local change patterns that actually appear in the current sample is used as the denominator, and the result of the division is used as the complexity concentration value. The complexity concentration value of the current sample is compared with the complexity concentration value of the corresponding target pollutant recorded in the baseline behavior database. The absolute value of the difference between the two is calculated, and the difference is subtracted from the result. The resulting value is the signal complexity matching index.

[0009] Optionally, if the matching degree index is higher than a preset threshold, a reverse intervention operation is performed to correct the chromatographic response signal; the reverse intervention operation includes the steps of increasing the channel temperature and increasing the carrier gas flow rate: The residual risk index is compared with the preset residual risk index threshold. If the residual risk index is not less than the preset residual risk index threshold, the reverse intervention mode is entered. In reverse intervention mode, the temperature of the chromatographic channel is automatically increased to the preset temperature rise value; and the carrier gas flow rate is increased, with the increase range being 1.2 to 2 times the set value. After the reverse intervention operation is completed, the chromatographic response signal is fitted and corrected.

[0010] A second aspect of this invention provides a gas chromatography-based waste gas detection device, the device comprising: Reference module: Injects standard gas samples of each target pollutant into the gas chromatograph and records the chromatographic response signals of the target pollutants at different concentrations as reference chromatographic response signals; Current module: After each round of exhaust gas sample is injected into the gas chromatograph, the chromatographic response signal is recorded as the current chromatographic response signal; Calculation module: Calculates a matching index reflecting the degree of relevance to residual risk based on the reference chromatographic response signal and the current chromatographic response signal; Intervention module: If the matching degree index is higher than the preset threshold, a reverse intervention operation is performed to fit and correct the chromatographic response signal; the reverse intervention operation includes increasing the channel temperature and increasing the carrier gas flow rate; Detection module: Outputs the detection result of the current sample based on the corrected chromatographic response signal, and serves as the final detection output for the current sample.

[0011] Optionally, the computing module includes: Residual Risk Module: Based on the reference chromatographic response signal and the current chromatographic response signal, the dynamic trajectory deformation matching index and the signal complexity matching index are calculated. The dynamic trajectory deformation matching index and the signal complexity matching index are added together to obtain the residual risk index, which is used as an indicator to reflect the degree of matching of residual risk.

[0012] Optionally, the residual risk module includes: Acquisition module: After each round of exhaust gas sample is injected into the gas chromatograph, the time-amplitude sequence of the current chromatographic response signal is recorded; Local slope module: The signal after the autonomous peak in the current chromatographic response signal is taken as the falling phase signal; for the time-amplitude sequence corresponding to the falling phase signal, the amplitude difference and time difference between each time point and its previous time point are calculated, and the amplitude difference is divided by the time difference to obtain the local slope of each time point; Nonlinear module: A quadratic polynomial fitting method is used to fit the signal during the descent phase to obtain a fitting curve. For each time point, the deviation between the fitted curve and the actual signal at each time point is used to obtain the nonlinear factor of the signal at the corresponding time point. Transformation module: Uses Jacobian transform to calculate the derivative of the amplitude and time change of the signal during the descent phase at each time point, and obtains the Jacobian transform quantity at each time point; First Deformation Value Module: The local slope, nonlinear factor and Jacobian transform metric at each time point are added together to obtain the deformation metric at the corresponding time point. The deformation metrics at all time points in the falling phase signal are added together to obtain the deformation value of the current sample, which is recorded as the first deformation value. Dynamic trajectory deformation matching module: Calculates the deformation value of the reference chromatographic response signal as the second deformation value, and divides the first deformation value by the second deformation value to obtain the dynamic trajectory deformation matching index.

[0013] Optionally, the residual risk module further includes: Falling phase signal module: The signal after the autonomous peak in the current chromatographic response signal is used as the falling phase signal; Change direction module: For the time-amplitude sequence corresponding to the falling phase signal, the signal values ​​of the continuous sampling points in the falling phase are symbolized. For the signal values ​​of two adjacent sampling points, if the value of the later sampling point is greater than the value of the earlier sampling point, it is marked as rising; if the two values ​​are equal, it is marked as stationary; if the later point is less than the earlier point, it is marked as falling. This generates a set of change direction sequences containing only the three types of symbols: rising, falling, and stationary. Frequency module: Construct multiple continuous sliding subsequences in the sequence of changes in direction with a fixed length, forming multiple local change pattern units of the same length; count the number of all different change pattern units, and calculate the frequency of each type of pattern unit in the whole sequence; Uncertainty Value Module: Multiply the frequency of occurrence of each type of pattern by its own logarithm and then sum them to obtain the distribution uncertainty value of each change pattern; use the negative value of the distribution uncertainty value as the uncertainty value; Complexity Concentration Value Module: The uncertainty value is used as the numerator, the logarithm of the number of local change patterns that actually appear in the current sample is used as the denominator, and the result of the division is used as the complexity concentration value. Signal Complexity Matching Index Module: Compares the complexity concentration value of the current sample with the complexity concentration value recorded in the baseline behavior database for the corresponding target pollutant, calculates the absolute value of the difference between the two, and subtracts the absolute value of the difference from the value of 1. The resulting value is the signal complexity matching index.

[0014] Optionally, the intervention module includes: Comparison module: Compares the residual risk index with the preset residual risk index threshold. If the residual risk index is not less than the preset residual risk index threshold, it enters the reverse intervention mode. Intervention Operation Module: In reverse intervention mode, it automatically raises the temperature of the chromatographic channel to the preset temperature rise value; and increases the carrier gas flow rate, with the increase range being 1.2 to 2 times the set value; Correction module: After the reverse intervention operation is completed, the chromatographic response signal is fitted and corrected.

[0015] The beneficial effects of this invention are: This invention proposes a gas chromatography-based method and apparatus for waste gas detection. By recording and comparing the difference between the current chromatographic response signal and the reference signal in real time during each detection process, and calculating the matching degree index, this method can effectively identify and compensate for the "concentration jump" and "residual tailing" phenomena caused by nonlinear adsorption and desorption in the chromatographic system. Through reverse intervention operations (such as increasing the channel temperature and carrier gas flow rate) to fit and correct the signal, the method can eliminate the influence of historical residues, avoid misleading detection results, and significantly improve the accuracy and reliability of detection. This method effectively solves the problems of false alarms, missed alarms, and erroneous control decisions caused by chromatographic memory effects in existing technologies, ensuring accurate monitoring of pollutant concentrations and more reasonable control decisions. Attached Figure Description

[0016] Figure 1 This is a flowchart of a gas chromatography-based waste gas detection method provided in an embodiment of the present invention. Detailed Implementation

[0017] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0018] This invention provides a gas chromatography-based method for detecting exhaust gases. See also... Figure 1 , Figure 1 A flowchart illustrating a gas chromatography-based method for detecting exhaust gas is provided in this embodiment of the invention. The method includes the following steps: S1: Inject standard gas samples of each target pollutant into the gas chromatograph and record the chromatographic response signals of the target pollutants at different concentrations as the reference chromatographic response signals. S2: After each round of exhaust gas sample is injected into the gas chromatograph, the chromatographic response signal is recorded as the current chromatographic response signal; S3: Calculate a matching index to reflect the degree of residual risk based on the reference chromatographic response signal and the current chromatographic response signal; S4: If the matching degree index is higher than the preset threshold, a reverse intervention operation is performed to fit and correct the chromatographic response signal; the reverse intervention operation includes increasing the channel temperature and increasing the carrier gas flow rate; S5: Output the detection result of the current sample based on the corrected chromatographic response signal, and use it as the final detection output of the current sample.

[0019] This invention provides a gas chromatography-based waste gas detection method. By recording and comparing the difference between the current chromatographic response signal and the reference signal in real time during each detection process, and calculating the matching degree index, this method can effectively identify and compensate for the "concentration jump" and "residual tailing" phenomena caused by nonlinear adsorption and desorption in the chromatographic system. By using reverse intervention operations (such as increasing the channel temperature and increasing the carrier gas flow rate) to fit and correct the signal, the method can eliminate the influence of historical residues, avoid misleading detection results, and significantly improve the accuracy and reliability of detection. This method effectively solves the problems of false alarms, missed alarms, and erroneous control decisions caused by the chromatographic memory effect in the prior art, ensuring accurate monitoring of pollutant concentrations and more reasonable control decisions. In one embodiment, in step S1, S1: standard gas samples of each target pollutant are injected into the gas chromatograph, and the chromatographic response signals of the target pollutants at different concentrations are recorded as reference chromatographic response signals; Specifically, during the self-calibration phase after detection is initiated, standard gas samples are automatically injected sequentially into the chromatograph, containing multiple pre-defined target pollutant samples. Each pollutant is arranged in a concentration gradient sequence from low to high concentration points. For example, for formaldehyde, multiple points such as 0.1 ppm, 0.5 ppm, 1 ppm, and 5 ppm can be set. Each point is injected independently under stable flow rate and constant temperature control conditions, and the complete chromatographic response process is collected to ensure a clean baseline and response curve are obtained without being affected by the residue of the previous round. To ensure the ability to recognize chromatographic memory effects under complex detection environments, different background gases are also used. The above process is repeated under different conditions, such as dry nitrogen, 50% humidity air, or the addition of small amounts of other common interfering substances (such as low concentrations of benzene, acetic acid, etc.) to form the background environment. A feature model is generated completely under each background. Finally, these models generated under different backgrounds are unified and constructed into a combined condition mapping matrix, i.e., a behavior feature matrix table. This enables the system to automatically match the closest reference trajectory based on the current response characteristics even when facing mixed gases, high humidity environments, or multi-component interference in actual detection. This achieves generalized adaptation of the memory response across different scenarios, thereby significantly improving the modeling depth and application robustness of the nonlinear adsorption tailing problem.

[0020] In one embodiment, in step S2, after each round of exhaust gas sample injection, the chromatograph begins recording the complete chromatographic response signal. At this time, the captured response signal is transmitted to the data processing module via a high-precision sensor and stored and monitored in real time as a time series. This signal contains all information about the exhaust gas sample after separation by the chromatographic column, including peak formation, the decay process after peak arrival, and other possible background noise. Subsequently, the signal processing module performs noise reduction processing on the received chromatographic signal. During this process, a filtering algorithm removes high-frequency noise and background interference, ensuring that the extracted signal only reflects the true response of the target pollutant. For example, for changes in the concentration of volatile organic compounds (VOCs) in the exhaust gas, errors caused by equipment noise or environmental factors (such as electromagnetic interference) are eliminated to ensure data accuracy.

[0021] In one embodiment, S3: The step of calculating the matching index reflecting the degree of matching risk based on the reference chromatographic response signal and the current chromatographic response signal is as follows: The dynamic trajectory deformation matching index and the signal complexity matching index are calculated based on the comparison results. The dynamic trajectory deformation matching index and the signal complexity matching index are added together to obtain the residual risk index. The residual risk index is used as an indicator to reflect the degree of matching of residual risk. It should be noted that all data involved in the calculation of the dynamic trajectory deformation matching index is obtained through real-time acquisition and processing of the chromatographic response signal of the exhaust gas sample. First, the time-amplitude sequence of the chromatographic response signal is obtained by detecting the real-time recorded chromatographic data; the signal amplitude changes over time, with time on the x-axis and signal amplitude on the y-axis. Recording and analysis of the chromatographic response signal begins after each sample injection, ensuring the accuracy and completeness of the acquired signal data. This data is continuously updated and stored, especially throughout the entire process from peak to signal decay to baseline. For the calculation of the local slope, the rate of change between adjacent time points is first calculated using the time difference and amplitude difference to obtain the local slope at each time point, which helps describe the local trend of signal change. Second, during the signal descent phase, a quadratic polynomial fitting method is used to generate a theoretical fitting curve by fitting the descent portion of the signal. The deviation from the actual signal is then used to calculate the nonlinear factor at each time point, reflecting the nonlinear behavior that occurs during signal change. The Jacobian transform is a measure of the rate of change of a signal in time and amplitude space by analyzing its local variations. It reflects the degree of local deformation at a specific point in time and is an important tool for measuring signal deformation. In this context, the Jacobian transform helps identify dynamic deformation in the signal, especially during the decay phase, by quantitatively describing the rate and pattern of signal change. Through these calculations, a measure of signal deformation can be obtained, and the deformation value of the current sample can be compared with benchmark data to derive a dynamic trajectory deformation matching index. The advantage of this calculation method is that it can more accurately capture minute changes in the signal, especially in details such as decay and tailing, thereby improving the ability to identify memory effects and avoiding simple comparisons based solely on peak values ​​or standard patterns.

[0022] It's important to note that the Dynamic Trajectory Deformation Matching Index (VTDI) is a quantitative indicator used to measure the similarity between the chromatographic response signal of a current exhaust gas sample and benchmark data, particularly the degree of signal morphology matching. It comprehensively evaluates the characteristics of signal deformation, nonlinear changes, and local change rates during the descent phase by performing multi-dimensional analysis of the dynamic changes in the chromatographic response signal (including local slope, nonlinearity factor, and Jacobian transform measure), ultimately deriving a numerical value that reflects whether the current sample's response signal exhibits historical residual effects or chromatographic memory effects. A higher VTDI value indicates a greater similarity in morphology between the current sample's response signal and the benchmark signal, suggesting stronger nonlinear deformation or a greater degree of morphological change, indicating a stronger influence from residual pollutants. For example, when an exhaust gas sample contains a high concentration of pollutants (such as benzene), due to the adsorption characteristics of the chromatographic column, the pollutant signal will exhibit a tailing effect after the peak, and this tailing effect becomes more pronounced with increasing concentration. At this point, the deformation of the current sample's response signal closely matches the trajectory of the reference signal, resulting in a high dynamic trajectory deformation matching index. This indicates that residual pollutants in the sample have a significant and persistent impact on the signal. Conversely, if the dynamic trajectory deformation matching index is close to 0, it indicates a large morphological difference between the current signal and the reference signal, with a small residual effect, suggesting no significant memory effect or that the pollutants have been completely removed. In summary, the magnitude of the dynamic trajectory deformation matching index directly reflects the degree of influence of potential residual pollutants in the exhaust gas sample on the chromatographic signal. A larger index indicates a stronger residual effect, requiring further processing of these effects.

[0023] It should be noted that the data involved in the calculation of the signal complexity matching index all come from the raw response signals collected during the actual exhaust gas sample detection process by chromatographic detection. This signal is continuously recorded at high frequency by the detector of the chromatograph (such as a flame ionization detector or a thermal conductivity detector) to record the response intensity of the sample components after separation in the chromatographic column, forming time series data containing the response value and corresponding timestamp of each sampling moment. During the detection process, the location of the target peak is automatically identified, and the complete descent phase from the peak to the signal decay regression baseline is extracted as the analysis segment. The time sequence and response value of all sampling points in this segment constitute the basic signal data used for complexity analysis. It should be noted that the signal complexity matching index is an indicator used to measure the similarity between the structure of the current exhaust gas sample's chromatographic response signal during the descent phase and the structure of the historical standard signal response. By quantitatively analyzing the complexity of the signal during its change, it specifically measures whether the signal change exhibits a complex pattern similar to historical residual signals. The signal complexity matching index ranges from 0 to 1. A value closer to 1 indicates a more similar complexity structure to the historical standard signal, and a stronger influence of residual pollutants on the current response. Conversely, a value closer to 0 indicates a significant difference between the current signal's complexity structure and the historical signal's change pattern, suggesting a smaller or non-existent residual effect. The reason why a larger signal complexity matching index indicates a stronger residual effect is that chromatographic signal residues typically manifest as tailing, slow decay, and non-linear changes during the signal descent phase. These characteristics usually appear in historical signals and repeatedly influence the new round of response through adsorption-desorption dynamics. For example, if a pollutant's signal initially produced a strong tailing effect at high concentrations, and this signal exhibits a similar pattern of change (such as a slow decline and a similar tailing shape) in subsequent tests of low-concentration samples, it can be inferred that the signal at this point is partly due to historical residual pollutants that have not been removed. Therefore, a high value of the signal complexity matching index indicates that the current sample signal is still significantly influenced by historical signals, with a strong residual effect, while a low value indicates that the current signal was generated by a fresh sample, with a weaker residual effect.

[0024] In one embodiment, the residual risk index is compared with a preset residual risk index threshold. If the residual risk index of the current sample is greater than or equal to the preset threshold, the system determines that a memory residual effect exists and enters a reverse intervention mode. In reverse intervention mode, firstly, the system automatically increases the temperature of the chromatographic channel to a preset temperature rise value, which is usually set above the normal operating temperature. The purpose is to promote the desorption of pollutants by heating, thereby reducing residual pollutants in the chromatographic column. For example, the set temperature rise value may be 20°C above the normal operating temperature to ensure effective elimination of the memory effect caused by nonlinear adsorption. Next, the system increases the carrier gas flow rate, typically by 1.2 to 2 times the set value, adjusted according to the characteristics of different target pollutants and the required response time. The increased flow rate helps accelerate pollutant desorption and speed up signal recovery, preventing signal delays or incomplete pollutant removal due to insufficient gas flow. After performing the heating and carrier gas flow rate increase operations described above, the system performs fitting correction on the tail of the chromatographic response signal. This is mainly done by fitting the tailed portion of the signal using a nonlinear regression model (such as an exponential decay model or a polynomial fitting model) to eliminate the tailing phenomenon caused by the memory effect. For example, if there is nonlinear decay in the tailed portion, the system will correct this part by fitting the curve to ensure that the signal decay is restored to a level close to the actual concentration, thereby obtaining a more accurate detection result. Finally, the corrected chromatographic response signal will be used as the final detection output for the current sample. This correction process ensures that when facing nonlinear adsorption / desorption problems, the system can effectively eliminate misleading data through dynamic adjustment and signal fitting, providing more accurate and reliable exhaust gas monitoring results.

[0025] In one embodiment, S5: Output the detection result of the current sample based on the corrected chromatographic response signal, and use it as the final detection output of the current sample.

[0026] It should be noted that the chromatographic response signal is corrected in the reverse intervention mode. Through the previous reverse intervention and signal fitting correction steps, the tailing and nonlinear attenuation caused by historical residual pollutants have been eliminated, and the corrected signal is closer to the concentration characteristics of the actual sample. At this time, the corrected chromatographic response signal is transmitted to the data processing module for final result output. For example, if the response signal of the target pollutant (such as aldehydes or phenols) originally recorded by the system has obvious residual tailing or concentration jumps, after reverse intervention and fitting correction, the system can provide a smooth signal that truly reflects the current pollutant concentration. The system ensures that the output signal reflects a pollutant concentration closer to the actual concentration through regression model and attenuation curve fitting, avoiding misleading detection results caused by chromatographic memory effect. Finally, the corrected signal is used as the final detection output of the current exhaust gas sample, which means that the detection result of the sample will no longer be affected by residual pollutants and can be accurately used for subsequent decision-making or further analysis. The core of this step is to ensure the accuracy and reliability of the detection results through precise signal correction, avoiding false alarms or missed alarms.

[0027] Based on the same inventive concept, this invention also provides a gas chromatography-based waste gas detection device, comprising: Reference module: Injects standard gas samples of each target pollutant into the gas chromatograph and records the chromatographic response signals of the target pollutants at different concentrations as reference chromatographic response signals; Current module: After each round of exhaust gas sample is injected into the gas chromatograph, the chromatographic response signal is recorded as the current chromatographic response signal; Calculation module: Calculates a matching index reflecting the degree of relevance to residual risk based on the reference chromatographic response signal and the current chromatographic response signal; Intervention module: If the matching degree index is higher than the preset threshold, a reverse intervention operation is performed to fit and correct the chromatographic response signal; the reverse intervention operation includes increasing the channel temperature and increasing the carrier gas flow rate; Detection module: Outputs the detection result of the current sample based on the corrected chromatographic response signal, and serves as the final detection output for the current sample.

[0028] This invention provides a gas chromatography-based waste gas detection device. By recording and comparing the difference between the current chromatographic response signal and the reference signal in real time during each detection process, and calculating the matching degree index, this method can effectively identify and compensate for the "concentration jump" and "residual tailing" phenomena caused by nonlinear adsorption and desorption in the chromatographic system. Through reverse intervention operations (such as increasing the channel temperature and carrier gas flow rate) to fit and correct the signal, the method can eliminate the influence of historical residues, avoid misleading detection results, and significantly improve the accuracy and reliability of detection. This method effectively solves the problems of false alarms, missed alarms, and erroneous control decisions caused by chromatographic memory effects in existing technologies, ensuring accurate monitoring of pollutant concentrations and more reasonable control decisions. The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention should still fall within the scope of the claims of the present invention.

Claims

1. A method for detecting waste gas based on gas chromatography, characterized in that, Includes the following steps: Inject standard gas samples of each target pollutant and record the chromatographic response signals of the target pollutants at different concentrations as reference chromatographic response signals. After each round of exhaust gas sample is injected into the gas chromatograph, the chromatographic response signal is recorded as the current chromatographic response signal; A matching index reflecting residual risk is calculated based on the baseline chromatographic response signal and the current chromatographic response signal; If the matching degree index is higher than the preset threshold, a reverse intervention operation is performed to fit and correct the chromatographic response signal; the reverse intervention operation includes increasing the channel temperature and increasing the carrier gas flow rate; The detection result of the current sample is output based on the corrected chromatographic response signal, and is used as the final detection output of the current sample.

2. The waste gas detection method based on gas chromatography according to claim 1, characterized in that, The steps for calculating the matching index reflecting residual risk based on the reference chromatographic response signal and the current chromatographic response signal are as follows: The dynamic trajectory deformation matching index and signal complexity matching index are calculated based on the reference chromatographic response signal and the current chromatographic response signal. The residual risk index is obtained by adding the dynamic trajectory deformation matching index and the signal complexity matching index, and is used as an indicator to reflect the degree of matching of residual risk.

3. The waste gas detection method based on gas chromatography according to claim 2, characterized in that, The calculation steps for the dynamic trajectory deformation matching index are as follows: After each round of exhaust gas sample is injected into the gas chromatograph, the time-amplitude sequence of the current chromatographic response signal is recorded; The signal after the autonomous peak in the current chromatographic response signal is taken as the falling phase signal; for the time-amplitude sequence corresponding to the falling phase signal, the amplitude difference and time difference between each time point and its previous time point are calculated, and the amplitude difference is divided by the time difference to obtain the local slope of each time point; The quadratic polynomial fitting method is used to fit the signal during the descent phase to obtain the fitting curve. For each time point, the deviation between the fitted curve and the actual signal at each time point is used to obtain the nonlinear factor of the signal at the corresponding time point. The Jacobian transform is used to calculate the derivative of the amplitude and time change of the signal during the descent phase at each time point, so as to obtain the Jacobian transform value at each time point. The local slope, nonlinear factor and Jacobian transform metric at each time point are added together to obtain the deformation metric at the corresponding time point. The deformation metrics at all time points in the descent phase signal are added together to obtain the deformation value of the current sample, which is recorded as the first deformation value. The deformation value of the reference chromatographic response signal is calculated as the second deformation value. The first deformation value is divided by the second deformation value to obtain the dynamic trajectory deformation matching index.

4. The waste gas detection method based on gas chromatography according to claim 2, characterized in that, The steps for calculating the signal complexity matching index are as follows: The signal following the autonomous peak in the current chromatographic response signal is taken as the descending phase signal. For the time-amplitude sequence corresponding to the falling phase signal, the signal values ​​of the continuous sampling points in the falling phase are symbolized. For the signal values ​​of two adjacent sampling points, if the value of the later sampling point is greater than the value of the earlier sampling point, it is marked as rising; if the two values ​​are equal, it is marked as stationary; if the later point is less than the earlier point, it is marked as falling. This generates a set of change direction sequences containing only the three types of symbols: rising, falling, and stationary. Multiple continuous sliding subsequences are constructed in the sequence of changing directions with a fixed length as the unit, forming multiple local change mode units of the same length; The number of different change pattern units was counted, and the frequency of occurrence of each type of pattern unit in the whole sequence was calculated. Multiply the frequency of occurrence of each pattern by its own logarithm and then sum them to obtain the distribution uncertainty value of each change pattern; use the negative value of the distribution uncertainty value as the uncertainty value; The uncertainty value is used as the numerator, the logarithm of the number of local change patterns that actually appear in the current sample is used as the denominator, and the result of the division is used as the complexity concentration value. The complexity concentration value of the current sample is compared with the complexity concentration value of the corresponding target pollutant recorded in the baseline behavior database. The absolute value of the difference between the two is calculated, and the difference is subtracted from the result. The resulting value is the signal complexity matching index.

5. The waste gas detection method based on gas chromatography according to claim 1, characterized in that, If the matching degree index is higher than the preset threshold, the steps for performing reverse intervention to fit and correct the chromatographic response signal are as follows: The residual risk index is compared with the preset residual risk index threshold. If the residual risk index is not less than the preset residual risk index threshold, the reverse intervention mode is entered. In reverse intervention mode, the temperature of the chromatographic channel is automatically increased to the preset temperature rise value; And increase the carrier gas velocity, with the increase ranging from 1.2 to 2 times the set value; After the reverse intervention operation is completed, the chromatographic response signal is fitted and corrected.

6. A waste gas detection device based on gas chromatography, characterized in that, The device includes: Reference module: Inject standard gas samples of each target pollutant and record the chromatographic response signals of the target pollutants at different concentrations as reference chromatographic response signals; Current module: After each round of exhaust gas sample is injected into the gas chromatograph, the chromatographic response signal is recorded as the current chromatographic response signal; Calculation module: Calculates a matching index reflecting the degree of relevance to residual risk based on the reference chromatographic response signal and the current chromatographic response signal; Intervention module: If the matching degree index is higher than the preset threshold, a reverse intervention operation is performed to fit and correct the chromatographic response signal; the reverse intervention operation includes increasing the channel temperature and increasing the carrier gas flow rate; Detection module: Outputs the detection result of the current sample based on the corrected chromatographic response signal, and serves as the final detection output for the current sample.

7. The waste gas detection device based on gas chromatography according to claim 6, characterized in that, The computing module includes: Residual Risk Module: Based on the reference chromatographic response signal and the current chromatographic response signal, the dynamic trajectory deformation matching index and the signal complexity matching index are calculated. The dynamic trajectory deformation matching index and the signal complexity matching index are added together to obtain the residual risk index, which is used as an indicator to reflect the degree of matching of residual risk.

8. The waste gas detection device based on gas chromatography according to claim 7, characterized in that, The residual risk module includes: Acquisition module: After each round of exhaust gas sample is injected into the gas chromatograph, the time-amplitude sequence of the current chromatographic response signal is recorded; Local slope module: The signal after the autonomous peak in the current chromatographic response signal is taken as the falling phase signal; for the time-amplitude sequence corresponding to the falling phase signal, the amplitude difference and time difference between each time point and its previous time point are calculated, and the amplitude difference is divided by the time difference to obtain the local slope of each time point; Nonlinear module: A quadratic polynomial fitting method is used to fit the signal during the descent phase to obtain a fitting curve. For each time point, the deviation between the fitted curve and the actual signal at each time point is used to obtain the nonlinear factor of the signal at the corresponding time point. Transformation module: Uses Jacobian transform to calculate the derivative of the amplitude and time change of the signal during the descent phase at each time point, and obtains the Jacobian transform quantity at each time point; First Deformation Value Module: The local slope, nonlinear factor and Jacobian transform metric at each time point are added together to obtain the deformation metric at the corresponding time point. The deformation metrics at all time points in the falling phase signal are added together to obtain the deformation value of the current sample, which is recorded as the first deformation value. Dynamic trajectory deformation matching module: Calculates the deformation value of the reference chromatographic response signal as the second deformation value, and divides the first deformation value by the second deformation value to obtain the dynamic trajectory deformation matching index.

9. The waste gas detection device based on gas chromatography according to claim 7, characterized in that, The residual risk module also includes: Falling phase signal module: The signal after the autonomous peak in the current chromatographic response signal is used as the falling phase signal; Change direction module: For the time-amplitude sequence corresponding to the falling phase signal, the signal values ​​of the continuous sampling points in the falling phase are symbolized. For the signal values ​​of two adjacent sampling points, if the value of the later sampling point is greater than the value of the earlier sampling point, it is marked as rising; if the two values ​​are equal, it is marked as stationary; if the later point is less than the earlier point, it is marked as falling. This generates a set of change direction sequences containing only the three types of symbols: rising, falling, and stationary. Frequency module: Construct multiple continuous sliding subsequences in the sequence of changes in direction with a fixed length, forming multiple local change pattern units of the same length; count the number of all different change pattern units, and calculate the frequency of each type of pattern unit in the whole sequence; Uncertainty Value Module: Multiply the frequency of occurrence of each type of pattern by its own logarithm and then sum them to obtain the distribution uncertainty value of each change pattern; use the negative value of the distribution uncertainty value as the uncertainty value; Complexity Concentration Value Module: The uncertainty value is used as the numerator, the logarithm of the number of local change patterns that actually appear in the current sample is used as the denominator, and the result of the division is used as the complexity concentration value. Signal Complexity Matching Index Module: Compares the complexity concentration value of the current sample with the complexity concentration value recorded in the baseline behavior database for the corresponding target pollutant, calculates the absolute value of the difference between the two, and subtracts the absolute value of the difference from the value of 1. The resulting value is the signal complexity matching index.

10. A waste gas detection device based on gas chromatography according to claim 6, characterized in that, The intervention module includes: Comparison module: Compares the residual risk index with the preset residual risk index threshold. If the residual risk index is not less than the preset residual risk index threshold, it enters the reverse intervention mode. Intervention Operation Module: In reverse intervention mode, it automatically raises the temperature of the chromatographic channel to the preset temperature rise value; and increases the carrier gas flow rate, with the increase range being 1.2 to 2 times the set value; Correction module: After the reverse intervention operation is completed, the chromatographic response signal is fitted and corrected.

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