Carbon dioxide flue gas emission monitoring and calibrating method and related device

Abstract

The invention discloses a carbon dioxide flue gas emission monitoring and calibrating method and a related device. The method comprises the steps that a plurality of actual emission source simulation scenes are divided based on actual emission characteristics of a target industry factory, and carbon dioxide gas generation parameters, smoke particulate matter aerosol generation parameters and environmental parameters of different emission source simulation scenes are different; controlling the carbon dioxide flue gas emission monitoring standard measurement device according to different actual emission source simulation scenes to provide corresponding test parameters; and controlling the test sequence of the plurality of actual emission source simulation scenes in combination with the actual emission rule of the target industry factory so as to verify the carbon dioxide emission amount measuring instrument. The method can solve the problem that the detection technology needs to be continuously optimized and the data accuracy needs to be improved when the industries face stricter emission control requirements along with the tightening of carbon emission requirements.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of carbon measurement, and more specifically, the present invention relates to a carbon dioxide flue gas emission monitoring and calibration method and related devices. Background Art

[0002] As we actively pursue green, low-carbon development paths, the carbon trading market is gaining increasing attention as a key emission control tool. Accurate, objective, real-time, and credible carbon emissions data is essential for the efficient operation of the carbon trading market. It also underpins international mutual verification, corporate low-carbon production management, and the achievement of the "carbon peak and carbon neutrality" goals.

[0003] Carbon dioxide emissions monitoring is crucial in high-energy-consuming, high-emission industries such as thermal power, building materials, and steel. As carbon emission requirements tighten, these industries face stricter emission control requirements, requiring continuous optimization of detection technology and improved data accuracy. Summary of the Invention

[0004] The Summary of the Invention introduces a series of simplified concepts that will be further described in the Detailed Description of the Invention. The Summary of the Invention is not intended to limit the key features and essential features of the claimed technical solution, nor is it intended to determine the scope of protection of the claimed technical solution.

[0005] In order to solve the problem that these industries face stricter emission control requirements as carbon emission requirements tighten, and need to continuously optimize detection technology and improve data accuracy, in a first aspect, the present invention proposes a carbon dioxide flue gas emission monitoring calibration method for a carbon dioxide flue gas emission monitoring standard measurement device, the carbon dioxide flue gas emission monitoring standard measurement device is used to calibrate a carbon dioxide concentration measuring instrument, the carbon dioxide flue gas emission monitoring standard measurement device is constructed in a straight wind tunnel manner, specifically for generating carbon dioxide gas and smoke particulate aerosols, the carbon dioxide flue gas emission monitoring standard measurement device also includes a value traceability module and the measurement position has a transparent test window, the method comprising:

[0006] Based on the actual emission characteristics of factories in the target industry, multiple actual emission source simulation scenarios are divided. Different emission source simulation scenarios have different carbon dioxide gas generation parameters, smoke particulate aerosol generation parameters, and environmental parameters;

[0007] Controlling the carbon dioxide flue gas emission monitoring standard measuring device according to different actual emission source simulation scenarios to provide corresponding test parameters;

[0008] Combined with the actual emission patterns of factories in the target industry, the test sequence of multiple actual emission source simulation scenarios is controlled to calibrate the carbon dioxide emission measuring instruments.

[0009] Optionally, also include:

[0010] Evaluating the test window contamination risk levels of the plurality of actual emission source simulation scenarios according to the test parameters of the different emission source simulation scenarios, so as to divide the plurality of actual emission source simulation scenarios into test window contamination scenarios and test window cleaning scenarios based on the test window contamination risk levels;

[0011] When the previous actual emission source simulation scenario is a test window pollution scenario, the carbon dioxide flue gas emission monitoring standard measurement device is controlled to provide corresponding test parameters to provide a test window cleaning scenario, and then switch to the next actual emission source simulation scenario in the test sequence after a predetermined period of time.

[0012] Optionally, when the previous actual emission source simulation scenario is a test window pollution scenario, controlling the carbon dioxide flue gas emission monitoring standard measurement device to provide corresponding test parameters to provide a test window cleaning scenario, and switching to the next actual emission source simulation scenario in the test sequence after a predetermined time, includes:

[0013] When the previous actual emission source simulation scenario is a charged mine dust emission scenario, the carbon dioxide flue gas emission monitoring standard measurement device is controlled to provide corresponding test parameters to provide a desulfurization-related emission scenario, and then switch to the next actual emission source simulation scenario in the test sequence after a predetermined period of time.

[0014] Optionally, also include:

[0015] Evaluating the test window pollution risk levels of the plurality of actual emission source simulation scenarios according to the test parameters of the different emission source simulation scenarios, so as to divide the plurality of actual emission source simulation scenarios into test window pollution scenarios and prevention scenarios associated with the scenarios based on the test window pollution risk levels;

[0016] Before providing the test window pollution scenario according to the test sequence, the carbon dioxide flue gas emission monitoring standard measurement device is controlled to provide corresponding test parameters to provide the prevention scenario, and then switched to the test window pollution scenario after a predetermined period of time.

[0017] Optionally, before providing the test window pollution scenario according to the test sequence, controlling the carbon dioxide flue gas emission monitoring standard measurement device to provide corresponding test parameters to provide the prevention scenario, and switching to the test window pollution scenario after a predetermined time, includes:

[0018] Before providing the charged mine dust emission scenario according to the test sequence, the carbon dioxide flue gas emission monitoring standard measurement device is controlled to provide corresponding test parameters to provide a desulfurization-related emission scenario, and then switched to the charged mine dust emission scenario after a predetermined period of time.

[0019] Optionally, also include:

[0020] Periodically acquiring high-precision image data of the same transparent window segment of the transparent test window;

[0021] Analyze the high-precision image data obtained twice, use the frame difference method to compare the differences between the two image data, and identify the coexisting pollution points in the two cycles;

[0022] The contour of the polluted area is extracted by combining threshold segmentation with morphological operations;

[0023] Calculate the geometric characteristics of the contaminated area and, based on the location of the contaminated area, calculate the laser path that may be affected by the laser value traceability module;

[0024] In the case that an affected laser path currently exists, the calibration analysis of the instrument to be calibrated by the quantity traceability module is suspended, and the quantity traceability module includes the LDV and TDLAS gas analyzers.

[0025] Optionally, also include

[0026] Determine a new measurement angle to ensure the laser avoids contaminated areas;

[0027] The incident angle of the measurement traceability module is offset to avoid contamination points.

[0028] In a second aspect, the present invention further provides a standard measurement device for monitoring carbon dioxide flue gas emissions, which is used to calibrate carbon dioxide emission measuring instruments. The standard measurement device for monitoring carbon dioxide flue gas emissions is constructed in a straight wind tunnel manner and is used to generate carbon dioxide gas and smoke particle aerosols. The standard measurement device for monitoring carbon dioxide flue gas emissions also includes a value traceability module and a transparent test window at the measurement position. The standard measurement device for monitoring carbon dioxide flue gas emissions includes:

[0029] The division unit is used to divide multiple actual emission source simulation scenarios based on the actual emission characteristics of factories in the target industry. Different emission source simulation scenarios have different carbon dioxide gas generation parameters, smoke particulate aerosol generation parameters, and environmental parameters;

[0030] A control unit, configured to control the carbon dioxide flue gas emission monitoring standard measuring device to provide corresponding test parameters according to different actual emission source simulation scenarios;

[0031] The test unit is used to control the test sequence of multiple actual emission source simulation scenarios based on the actual emission patterns of target industry factories to calibrate carbon dioxide emission measuring instruments.

[0032] In a third aspect, an electronic device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor is configured to implement the steps of the carbon dioxide flue gas emission monitoring calibration method as described in any one of the first aspects above when executing the computer program stored in the memory.

[0033] In a fourth aspect, the present invention further proposes a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the carbon dioxide flue gas emission monitoring and calibration method according to any one of the above items in the first aspect is implemented.

[0034] In summary, the carbon dioxide flue gas emission monitoring and calibration method proposed in this application is to divide multiple actual emission source simulation scenarios based on the actual emission characteristics of the target industry factory. The carbon dioxide gas generation parameters, smoke particle aerosol generation parameters and environmental parameters of different emission source simulation scenarios are different; according to different actual emission source simulation scenarios, the carbon dioxide flue gas emission monitoring standard measurement device is controlled to provide corresponding test parameters; combined with the actual emission patterns of the target industry factory, the test sequence of multiple actual emission source simulation scenarios is controlled to calibrate the carbon dioxide emission measuring instrument. By simulating the emission characteristics of different factories and controlling parameters such as carbon dioxide concentration, particulate matter concentration, flow rate, temperature and humidity according to actual working conditions, the measurement accuracy and stability of the carbon dioxide concentration measuring instrument can be more comprehensively evaluated and calibrated. In this way, the reliability of the measuring instrument in a variety of industrial emission environments can be ensured, thereby solving the deficiency of traditional calibration methods being limited to a single working condition. By constructing multiple actual emission source simulation scenarios, dynamically controlling the parameters of the standard measurement device and adjusting the test sequence according to the factory emission patterns, the adaptability and calibration accuracy of the carbon dioxide measuring instrument are comprehensively improved. Compared with traditional calibration methods in a single environment, this method can more realistically reflect industrial emission conditions, enabling measuring instruments to maintain high precision and high stability in various complex environments, providing a reliable standard measurement system for environmental monitoring, industrial emission control and laboratory testing.

[0035] The carbon dioxide flue gas emission monitoring calibration method of the present invention, and other advantages, objectives and features of the present invention will be reflected in part through the following description, and in part will be understood by those skilled in the art through research and practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present description. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0037] Figure 1 A flow chart of a carbon dioxide flue gas emission monitoring and calibration method provided in an embodiment of the present application;

[0038] Figure 2 A schematic structural diagram of a carbon dioxide flue gas emission monitoring and calibration device provided in an embodiment of the present application;

[0039] Figure 3 A schematic diagram of the structure of an electronic device for monitoring carbon dioxide flue gas emissions provided in an embodiment of the present application. DETAILED DESCRIPTION

[0040] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of this application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or that are inherent to these processes, methods, products or devices. The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the embodiments described are only part of the embodiments of the present application, not all of the embodiments.

[0041] In order to solve the problem that these industries are facing stricter emission control requirements as carbon emission requirements are tightened, they need to continuously optimize detection technology and improve data accuracy. Figure 1 , which is a flow chart of a carbon dioxide flue gas emission monitoring calibration method provided in an embodiment of the present application, and is used for a standard measuring device for monitoring carbon dioxide flue gas emissions. The standard measuring device for monitoring carbon dioxide flue gas emissions is used to calibrate a carbon dioxide concentration measuring instrument. The standard measuring device for monitoring carbon dioxide flue gas emissions is constructed in a straight wind tunnel manner, and is specifically used to generate carbon dioxide gas and smoke particle aerosols. The standard measuring device for monitoring carbon dioxide flue gas emissions also includes a measurement traceability module and a transparent test window at the measurement position. The specific method may include: steps S110 to S130.

[0042] S110, based on the actual emission characteristics of factories in the target industry, multiple actual emission source simulation scenarios are divided. The carbon dioxide gas generation parameters, smoke particulate aerosol generation parameters and environmental parameters of different emission source simulation scenarios are different.

[0043] S120 , controlling the carbon dioxide flue gas emission monitoring standard measuring device according to different actual emission source simulation scenarios to provide corresponding test parameters.

[0044] S130 , controlling the test sequence of multiple actual emission source simulation scenarios based on actual emission patterns of factories in the target industry, so as to calibrate the carbon dioxide emission measurement instrument.

[0045] For example, a flow velocity / concentration standard measurement device can be established to simulate the multiphase flow field of stationary greenhouse gas emissions, based on the ultra-low emission characteristics of industries such as thermal power, building materials, and steel. Fly ash or dispersed polyalphaolefin (PAO) is used as the ultrafine particulate matter. The air generator generation rate and CO2 gas flow rate are quantitatively controlled. A Venturi device is used to continuously and stably generate PAO or fly ash aerosols. The airflow pressure or flow rate is adjusted to control the aerosol generation concentration and range. To ensure flow field stability, the device is constructed according to relevant standards for straight wind tunnels, with fiber optic mounting holes and transparent test windows reserved at the measurement locations to accommodate the installation requirements of measuring instruments using different principles. For traceability, an L-shaped Pitot tube, temperature and humidity sensors, and a CO2 gas analyzer are used as the primary standard devices to achieve real-time measurement of flow field velocity and CO2 concentration. The device can also be compared with laser Doppler velocimeters, TDLAS gas analyzers, and other instruments. To improve measurement stability, an integrated PID control system has been developed to monitor flow velocity and dust concentration in real time, adjust process instruments such as centrifugal fans, compressors, and flow controllers, and achieve automated control of the device. The development of this device provides a new calibration scheme for carbon dioxide emission monitoring instruments for stationary emission sources, changing the existing situation of separate traceability of flow rate and carbon dioxide concentration, and providing a solution for verifying and evaluating the overall measurement performance and value traceability of instruments.

[0046] It is understandable that in order to accurately simulate the characteristics of emission sources in different industrial sectors, it is necessary to divide multiple actual emission source simulation scenarios according to the specific emission conditions of the target industry factories, so that the working conditions of the standard measurement device can cover different types of carbon dioxide emission sources. For example, in a thermal power plant, the carbon dioxide concentration emitted by coal-fired boilers is generally 10%-14%, accompanied by 10-50mg / m 3The CO2 concentration in the sintering exhaust of the steel industry is generally 8%–12%, and the particulate matter is mainly metal oxides (Fe2O3), with a concentration of up to 20–50 mg / m3. 3 , with temperatures typically between 80–160°C and moderate humidity. In contrast, the CO2 concentration in coke oven flue gas from a coking plant is typically between 5% and 10%, accompanied by a certain amount of tar particles and with higher humidity (above 40%). This classification ensures that standard measurement devices can provide accurate simulated emission conditions in different industrial scenarios, thereby verifying the adaptability and measurement stability of measurement instruments under various real-world operating conditions.

[0047] For example, after the simulation scenario is established, it is necessary to further determine the generation mode of carbon dioxide gas and smoke particles to ensure that their parameters such as concentration, particle size, and flow rate are consistent with the actual working conditions. The generation of carbon dioxide gas uses a high-purity CO2 gas source and is precisely controlled using a mass flow controller (MFC) so that the CO2 concentration can be adjusted under different working conditions. For example, when simulating a coal-fired power plant, the CO2 concentration is set at 10–14%, while in the cement kiln simulation scenario it is set to 14–18%. The generation of smoke particles usually uses a Venturi injection device or a pneumatic conveying system to ensure the suspension stability of the particles in the air flow, and the particle concentration is controlled by adjusting the gas supply pressure and the dust supply amount. For example, when simulating the tail gas of steel sintering, high-temperature Fe2O3 particles can be used and their concentration can be set to 20–50 mg / m 3 To further match industrial working conditions, the system also needs to be equipped with temperature and humidity adjustment modules. For example, when simulating the flue gas of a thermal power plant after wet desulfurization, the humidity needs to be increased to above 40% and the temperature set to 60-80°C to verify the stability of the instrument in high humidity and low temperature environments.

[0048] For example, after determining the emission parameters under different industrial scenarios, it is necessary to dynamically adjust the relevant parameters through the control system of the carbon dioxide flue gas emission monitoring standard measurement device to provide an accurate test environment. The standard measurement device adopts a straight wind tunnel structure to ensure that the gas and particulate matter flow evenly in the pipeline and reduce the impact of turbulence on the measurement. During the experiment, the system first adjusts the CO2 concentration according to the set emission source simulation scenario, and uses a high-precision MFC to control the CO2 mass flow rate, such as setting 12% CO2 when simulating a thermal power plant and 16% under cement kiln conditions. Subsequently, the particulate matter generation system is started, and the aerosol concentration is controlled by adjusting the injection pressure and particle supply rate. For example, when simulating a coking plant, the tar particle concentration is set to 10-40mg / m3 . After ensuring the accuracy of the gas composition, the system needs to adjust the wind speed and flow state to match the exhaust characteristics of different emission sources. For example, in high-temperature industrial emissions (such as steel sintering tail gas), the air flow velocity may be high, so the wind tunnel needs to adjust the wind speed to 8-10m / s, while in low-speed emission sources (such as cement kiln tail gas), it needs to be reduced to 3-5m / s. The wind speed is measured using an L-shaped pitot tube and a laser Doppler velocimeter (LDV) for monitoring, and the wind speed is adjusted by PID control of the fan. In addition, in order to meet the measurement requirements of different working conditions, the device is also equipped with a temperature and humidity adjustment system. For example, when simulating the flue gas after wet desulfurization, the humidity is increased to more than 50% by a humidifier to observe the drift of the measuring instrument in a high humidity environment.

[0049] Understandably, since industrial emissions are not constant but rather vary dynamically across different stages of the production process, the calibration process should prioritize the testing sequence of different scenarios based on actual emission patterns to more closely resemble actual operating conditions. For example, in a thermal power plant test flow, the initial combustion emissions phase (high-temperature fly ash, high CO2 concentration) should be simulated first, followed by the post-desulfurization emissions phase (high-humidity, low-temperature CO2), and finally the post-dust removal purification emissions phase (low particulate matter concentration CO2). In a cement plant test flow, kiln head emissions (high-temperature, high CO2) should be simulated first, followed by the particulate matter purification phase, and finally the low-temperature, low-dust emissions phase. This multi-stage testing approach ensures that the instrument calibration process more closely matches actual emission conditions, ensuring stable operation of the measuring instrument throughout the entire emission cycle. Furthermore, during the test, the measurement results of the reference device (TDLAS) should be continuously compared with the instrument under calibration to analyze the measurement data errors under different scenarios. For example, in a wet flue gas desulfurization environment, if the CO2 reading of the measuring instrument is low, it may be due to absorption error caused by water vapor interference; while in a high-dust environment, if the measured value is high, it may be due to error caused by particle scattering. Through multi-scenario dynamic testing, we can systematically analyze the source of instrument error and optimize its measurement accuracy.

[0050] In summary, the carbon dioxide flue gas emission monitoring and calibration method provided in the embodiment of the present application is divided into multiple actual emission source simulation scenarios based on the actual emission characteristics of the target industry factory. The carbon dioxide gas generation parameters, smoke particulate aerosol generation parameters and environmental parameters of different emission source simulation scenarios are different; according to different actual emission source simulation scenarios, the carbon dioxide flue gas emission monitoring standard measurement device is controlled to provide corresponding test parameters; the test sequence of multiple actual emission source simulation scenarios is controlled in combination with the actual emission laws of the target industry factory to calibrate the carbon dioxide emission measuring instrument. By simulating the emission characteristics of different factories and controlling parameters such as carbon dioxide concentration, particulate matter concentration, flow rate, temperature and humidity according to actual working conditions, the measurement accuracy and stability of the carbon dioxide concentration measuring instrument can be more comprehensively evaluated and calibrated. In this way, the reliability of the measuring instrument in a variety of industrial emission environments can be ensured, thereby solving the deficiency of the traditional calibration method being limited to a single working condition.

[0051] According to some embodiments, further comprising:

[0052] Evaluating the test window contamination risk levels of the plurality of actual emission source simulation scenarios according to the test parameters of the different emission source simulation scenarios, so as to divide the plurality of actual emission source simulation scenarios into test window contamination scenarios and test window cleaning scenarios based on the test window contamination risk levels;

[0053] When the previous actual emission source simulation scenario is a test window pollution scenario, the carbon dioxide flue gas emission monitoring standard measurement device is controlled to provide corresponding test parameters to provide a test window cleaning scenario, and then switch to the next actual emission source simulation scenario in the test sequence after a predetermined period of time.

[0054] It is understandable that currently, the devices used to calibrate measuring equipment mainly calibrate measuring equipment by simulating specific airflows and particle distributions, but actual emission sources usually have more complex and dynamically changing characteristics. For example, the gases and particulate matter in actual emission sources may have instantaneous fluctuations, non-uniform distribution, and different temperature and humidity changes, while the device can only create a relatively stable simulation environment. Based on this, the above method simulates real emission scenarios and, based on the actual emission patterns of the factory, alternately combines these simulation scenarios in a certain order (for example, sorted as scenario a-scenario b-scenario c-scenario d...) to simulate the actual emission patterns of the factory. On this basis, it can be understood that some of the emission scenarios may easily lead to the pollution of the transparent window segment due to the differences in the composition, concentration, flow rate and even humidity of the emissions. These scenarios can be defined as test window pollution scenarios (for example, analysis shows that in the process of simulating scene a, due to the low humidity and low flow rate of scene a and the presence of metal components in the emissions, it is easy to adhere to the test window based on electrostatic effects, so this scene a can be defined as a pollution scene). Correspondingly, due to the differences in emission parameters in some emission scenarios, the window will be cleaned during the simulated emission, so these scenarios can be defined as test window cleaning scenarios (for example, scene d is defined as a cleaning scene). Then, in the simulated factory emissions When switching between different simulated emission scenarios based on a regular emission pattern, further consideration should be given to maintaining window cleanliness. If a particular scenario is considered to be a test window contamination scenario during the original scenario sorting process, the clean scenario can be placed after it in the sorting to ensure window cleanliness (for example, the original sorting is scenario a-scenario b-scenario c-scenario d...). Based on the above principle, this can be changed to (scenario a-scenario d-scenario b-scenario c-scenario d...). It should be emphasized that the so-called clean scenario does not refer to an ideal airflow environment that naturally has a cleansing effect. Instead, it is based on the specific pollution mechanism of the previous pollution scenario, achieving the purpose of localized mitigation or interference suppression of transparent test window contamination through the relative hedging effect of physical parameters. For example, scenario a (low flow rate, low humidity, high electrostatic mineral dust) will cause electrostatically adsorbed particles to accumulate on the test window; scenario d (high humidity, particle deagglomeration, localized microturbulence) can precisely desorb previously attached particles or re-introduce them into the airflow. However, scenario d has no such cleaning effect on scenario b (oil film contamination caused by high-viscosity aerosol). Therefore, scenario d is not a universal cleansing scenario, but a cleansing scenario relative to scenario a. This breaks through the limitations of traditional single steady-state test environments. Relative cleanliness scenarios are not obvious because they lack universal cleanability. They require identification of contamination mechanisms and reverse parameter analysis. Leveraging intelligent scenario sequence optimization strategies, this approach avoids window contamination while reducing downtime. This eliminates the need for additional cleaning systems, and allows for a natural release of test window contamination through scenario rearrangement, resulting in simplified engineering practices and self-maintaining features.It supports the long-term continuous calibration process of the instrument, significantly reduces the frequency of manual cleaning and maintenance, and improves the system efficiency and operational stability. The present invention makes full use of the influence of various parameters in the simulation scene (such as flow rate, humidity, particle charge, particle size distribution, etc.) on the pollution evolution of the transparent test window, and dynamically mines out "relatively clean scenes" with pollution cleaning potential by comparing the physical hedging effect between the pollution scene and other scenes. This type of cleaning scene does not naturally have cleaning capabilities, but shows a neutralization or slow-release effect on the pollution path in the face of a specific pollution mechanism. It is a cleaning relationship discovery method based on parameter logic drive, which is significantly different from traditional physical cleaning systems or absolute purge fields in technology. The introduction of cleaning scenes is not externally imposed, but the rational use of certain stage scenes that already exist in the factory emission cycle (such as desulfurization stage, wet dust removal stage, etc.), combined with its parameter characteristics (such as high humidity, high flow rate, anti-agglomeration effect) to intervene in the pollution trend of the previous scene. This way of going with the flow not only saves system resources, but also avoids the introduction of additional interference signals. It is an embedded optimization strategy. By adjusting the test sequence, the specific pollution scene and the corresponding relatively clean scene combination are embedded in the overall test cycle, so that the dynamic authenticity of the simulated emission law can be maintained, and the accumulation of pollution in the test window is effectively controlled. This sequential optimization strategy not only improves the reliability of the calibration environment, but also avoids human intervention and reliance on additional cleaning modules to the greatest extent, and has significant advantages in engineering implementation simplicity and test continuity assurance. Under complex emission conditions, the pollution-to-clean linkage sequence constructed through scene parameter logic enables the measuring instrument to not only undergo performance verification in a representative pollution environment, but also maintains transparency to key paths (such as laser channels) during a continuous working cycle, thereby improving the calibration accuracy of the entire system under actual working conditions and the credibility of the evaluation results. Compared with traditional directly attached cleaning mechanisms (such as window air scrapers and automatic cleaning links), the present invention does not introduce a physical cleaning device, but actively discovers the next scene with a cleaning effect through in-depth analysis of the parameter coupling relationship between scenes, and integrates it into the emission law simulation sequence, reflecting a highly innovative and professional logical chain.

[0055] For example, based on the actual emission behavior of the target industry (e.g., boiler section, desulfurization section, dust removal section, etc. in the thermal power industry), multiple emission source simulation scenarios (such as a, b, c, d, etc.) are designed. Each scenario defines a specific parameter combination, including airflow velocity, particulate matter concentration, particle size distribution, humidity, temperature, and CO2 concentration. The corresponding physical environment is achieved through controllable gas and particulate matter generation units. By modeling and analyzing the historical emission data of factories in the target industry, the typical emission sequence and switching rules in their process cycles are determined. For example, a common sequence may be: scenario a (electrostatic mineral dust) → scenario b (low-humidity condensation) → scenario c (high-flow flue gas) → scenario d (wet desulfurization), forming a periodic or non-periodic combination rule. In each scenario, the risk mechanism of window contamination is judged based on measured or simulated data, such as whether: particle residence time is too long (low speed); charged particle adsorption; condensed wet dust film adhesion; high temperature causes particle thermal melting adsorption. This type of scenario is defined as a window contamination scenario. For each pollution scenario, we analyze its pollution source mechanism and physical characteristics, and search for other defined scenarios to see if there are scenarios that can produce antagonistic effects on its pollution form, such as desorption / purging / anti-agglomeration, based on parameters such as airflow, particle kinetic energy, and humidity. This scenario is used as its relative cleanliness scenario (e.g., d relative to a). If the original plan is a→b→c→d, then if a is identified as a pollution scenario and d has a relative cleanliness effect on it, d is inserted to form: a→d→b→c→d. However, if b is also a pollution scenario and d has no cleansing effect on b, we need to further search for another cleanliness scenario e that only has an effect on b, forming: a→d→b→e→c→d, thus establishing a combination strategy for dynamic alternation from pollution to cleanliness...

[0056] In some examples, when the previous actual emission source simulation scenario is a test window pollution scenario, controlling the carbon dioxide flue gas emission monitoring standard measurement device to provide corresponding test parameters to provide a test window cleaning scenario, and switching to the next actual emission source simulation scenario in the test sequence after a predetermined time, includes:

[0057] When the previous actual emission source simulation scenario is a charged mine dust emission scenario, the carbon dioxide flue gas emission monitoring standard measurement device is controlled to provide corresponding test parameters to provide a desulfurization-related emission scenario, and then switch to the next actual emission source simulation scenario in the test sequence after a predetermined period of time.

[0058] It is understandable that, based on the aforementioned calibration method based on multiple emission source simulation scenarios, the contamination problem of the test window can be further considered, and a dynamic switching mechanism between contaminated scenarios and clean scenarios can be introduced to improve the stability and measurement accuracy of the calibration process. After a long period of operation, the test window of the traditional standard measurement device for monitoring carbon dioxide flue gas emissions is easily contaminated by particulate matter deposition, electrostatic adsorption, tar or water vapor condensation, etc., resulting in increased measurement errors. This method divides the simulation scenarios of different emission sources into test window contamination scenarios and test window clean scenarios by establishing a pollution risk level assessment mechanism, and uses an automatic cleaning scenario to self-clean the test window when the test window is severely contaminated, so as to restore the optical transmittance of the measurement environment and improve the stability of long-term measurements.

[0059] For example, in industrial production processes, emission characteristics vary significantly across different industries. Therefore, multiple emission source simulation scenarios must be divided based on the operating conditions of the target industry to ensure that the standard measurement device can calibrate the carbon dioxide concentration measurement instrument under various possible environmental conditions. For example, in the thermal power generation industry, the flue gas emitted by boiler combustion typically contains 10%–14% carbon dioxide and 10–50 mg / m 3 The temperature of fly ash particles is generally 80–120°C with low humidity. In cement plant clinker calcination, CO2 concentration is usually high, reaching 14%–18%. The dust emitted is mainly alkaline calcium oxide particles, with a temperature range of 100–180°C and low humidity. In the exhaust gas of steel sintering machines, CO2 concentration is 8%–12%, and the particulate matter emitted is mainly metal oxides (Fe2O3), with a concentration of 20–50 mg / m 3 , temperatures of 80–160°C, and moderate humidity. Furthermore, in coke oven flue gas emissions from coking plants, CO2 concentrations are typically between 5% and 10%, accompanied by tar particles and high humidity (above 40%). These scenarios encompass typical industrial emission characteristics, providing a more realistic calibration environment for the measurement device. To ensure that the test device parameters match different industrial scenarios, the corresponding CO2 gas generation method and soot particle aerosol generation method must be determined for each simulation scenario. The CO2 gas source is high-purity CO2 and precisely regulated by a mass flow controller (MFC) to ensure that the CO2 concentration in different scenarios matches actual operating conditions. For example, when simulating a coal-fired power plant, the CO2 concentration is set at 12%, while in the cement plant simulation scenario, it is set at 16%. The soot particles are generated using a Venturi ejector or pneumatic conveying system to ensure uniform particle distribution in the wind tunnel. The particle concentration is precisely controlled by adjusting the injection pressure and particle supply rate. For example, in the steel sintering exhaust gas scenario, the Fe2O3 particle concentration is set at 20–50 mg / m 3In addition, the temperature and humidity control system is used to match the environmental conditions of different emission scenarios. For example, when simulating flue gas after wet desulfurization, the humidity is increased to above 50% to test the response performance of the measuring instrument in a high humidity environment.

[0060] For example, after determining the parameters of each emission source simulation scenario, it is necessary to make real-time adjustments through the automated control system of the standard measuring device to ensure the accuracy of the test parameters. The device adopts a straight wind tunnel structure, which can provide a stable airflow environment to ensure the comparison accuracy of the measuring instrument. First, the system controls the CO2 mass flow rate according to the set working conditions. For example, in the coal-fired power plant simulation scenario, the CO2 concentration is set to 12%, and in the cement kiln simulation scenario, it is set to 16%. Subsequently, the particulate matter generation system is activated to control the aerosol concentration by adjusting the injection pressure and the particulate matter supply. For example, in the coking plant simulation scenario, the tar particle concentration is set to 10–40 mg / m 3 The wind tunnel system adjusts the flow rate based on the characteristics of the simulation scenario. For example, for high-temperature emissions (such as flaring exhaust), the wind speed is set at 8–10 m / s, while for low-speed emission sources (such as cement kiln exhaust), it is set at 3–5 m / s. Furthermore, the flow rate is monitored using an L-shaped pitot tube and a laser Doppler velocimeter (LDV), and the PID control system adjusts the wind speed in real time to match the actual operating conditions.

[0061] For example, since industrial emissions change with different stages of the production process, the test sequence needs to be adjusted according to the actual emission rules. For example, in the test process of a thermal power plant, the combustion emission stage (high temperature fly ash) is simulated first, then the emission stage after desulfurization (high humidity and low temperature CO2) is switched, and finally the purification emission stage after dust removal (low particle concentration CO2) is tested. In a cement plant, it is necessary to simulate the kiln head emission (high temperature and high CO2) first, then enter the particulate matter purification stage, and finally enter the low temperature and low dust emission stage. By dynamically adjusting the test sequence, the measuring instrument can maintain high precision throughout the emission cycle.

[0062] For example, during multiple emission scene switching processes, since the emission characteristics of certain scenes (such as charged mine dust, high-humidity tar particles, etc.) may cause pollution to the test window, this method further introduces a test window pollution risk assessment mechanism to automatically adjust the test process to reduce pollution accumulation. First, based on the test data of different emission sources, the pollution risk level of the test window is calculated, for example: charged mine dust (high risk), high-temperature dust (medium risk), wet flue gas (low risk), clean air (no pollution). After detecting that the previous scene is a high-pollution emission source (such as charged mine dust), the system will automatically switch to the test window cleaning scene (such as wet flue gas after wet desulfurization) for a short test to use moisture to flush particulate matter and reduce pollution accumulation. The system can set a cleaning time window (such as 10 minutes), during which a high-humidity and low-particle flow field is maintained in the wind tunnel to gradually remove pollutants, and then switch to the next test scene. This method can significantly improve the long-term working stability of the measuring instrument and reduce the need for manual cleaning and maintenance;

[0063] For example, when the previous actual emission source simulation scene is identified as a charged mine dust emission scene, based on the fact that the flue gas particles simulated in this scene have parameter characteristics such as fine particle size, high charge state, low flow rate and low humidity, electrostatic adsorption and accumulation of particles are prone to occur in the transparent test window area, thereby causing a decrease in transmittance and affecting the laser measurement path. Therefore, it is judged as a test window pollution scene.

[0064] In response to this pollution risk, after this scenario, by controlling the wind speed, humidity adjustment module and aerosol generator of the carbon dioxide flue gas emission monitoring standard measurement device, a desulfurization-related emission scenario with relatively high humidity, medium particle concentration and turbulence-enhanced airflow characteristics is loaded. The high humidity conditions and disturbed airflow structure of this scenario in actual emissions are utilized to achieve a purging, dilution or anti-adhesion removal effect on the residual pollution in the previous scenario, thereby achieving a relative cleaning effect on the transparent test window.

[0065] After maintaining the desulfurization-related emission scenario for a set duration (e.g., 30 to 180 seconds), the system automatically switches to the next actual emission source simulation scenario in the test sequence, balancing the restoration of the plant's actual emission cycle with the slow release of accumulated window contamination. This sequential optimization strategy, by fully analyzing the parameter competition mechanisms between different simulation scenarios, dynamically maintains the measurement stability of the traceability channel without introducing additional cleaning hardware.

[0066] In some examples, this also includes:

[0067] Evaluating the test window pollution risk levels of the plurality of actual emission source simulation scenarios according to the test parameters of the different emission source simulation scenarios, so as to divide the plurality of actual emission source simulation scenarios into test window pollution scenarios and prevention scenarios associated with the scenarios based on the test window pollution risk levels;

[0068] Before providing the test window pollution scenario according to the test sequence, the carbon dioxide flue gas emission monitoring standard measurement device is controlled to provide corresponding test parameters to provide the prevention scenario, and then switched to the test window pollution scenario after a predetermined period of time.

[0069] In some examples, before providing the test window pollution scenario according to the test sequence, controlling the carbon dioxide flue gas emission monitoring standard measurement device to provide corresponding test parameters to provide the prevention scenario, and switching to the test window pollution scenario after a predetermined period of time, includes:

[0070] Before providing the charged mine dust emission scenario according to the test sequence, the carbon dioxide flue gas emission monitoring standard measurement device is controlled to provide corresponding test parameters to provide a desulfurization-related emission scenario, and then switched to the charged mine dust emission scenario after a predetermined period of time.

[0071] It is understandable that, in response to the calibration requirements of the standard measuring device for monitoring carbon dioxide flue gas emissions in different industrial emission scenarios, an optimized calibration method is proposed that comprehensively considers the diversity of emission conditions, test window pollution management, and pollution prevention. This method constructs multiple real emission source simulation scenarios and dynamically adjusts key parameters such as carbon dioxide concentration, smoke particle concentration, temperature and humidity, and flow rate according to the characteristics of each condition, so that the measuring device can accurately simulate different industrial emission conditions and conduct a comprehensive calibration of the carbon dioxide measuring instrument. In addition, this method further introduces a test window pollution risk assessment mechanism, divides different emission scenarios into high-pollution scenarios and associated pollution prevention scenarios, and provides a prevention stage before the pollution scenario, so that the test window is pretreated before entering the high-pollution environment to reduce pollution accumulation and improve the stability of long-term measurements. This method mainly includes the following core steps: (1) Divide multiple actual emission source simulation scenarios based on industry emission characteristics to ensure that the working conditions of the test device cover different industrial environments; (2) Dynamically control the measurement device based on the parameters of different emission scenarios to accurately provide the carbon dioxide gas and aerosol characteristics required for each scenario; (3) Optimize the test sequence according to the factory emission characteristics, and reasonably arrange the switching sequence between pollution scenarios and low-pollution or clean scenarios; (4) Provide a prevention scenario before the pollution scenario, use appropriate airflow or environmental conditions to reduce the risk of test window contamination, and improve long-term measurement stability.

[0072] For example, during a multi-scenario test, certain emission scenarios (such as charged mine dust, high-temperature dust, and high-humidity tar particles) may cause pollution to the test window. Therefore, before entering these high-pollution scenarios, the system will prioritize switching to the associated prevention scenarios and pre-treat the test window using appropriate airflow or environmental conditions. For example, before entering a charged mine dust scenario (such as steel sintering tail gas), first switch to a desulfurization-related emission scenario (such as flue gas after wet desulfurization) to form a wet film on the surface of the test window to reduce the probability of adsorption of charged particles. Similarly, before entering the coking plant tar flue gas scenario, you can first simulate a low-dust and high-humidity environment to reduce the possibility of oil film contamination. The system will set a prevention time window (such as 10 minutes), maintain specific environmental conditions during this period, and then switch to a high-pollution scenario to ensure that the measuring instrument always maintains the best working condition throughout the test process.

[0073] For example, when it is identified that the actual emission source simulation scenario to be provided according to the test sequence is a charged mine dust emission scenario, since this type of scenario simulates the release behavior of highly charged, high-concentration mineral dust in a low-humidity, low-flow rate environment, particulate matter is easily electrostatically adsorbed in the transparent area of ​​the test window, thereby forming a deposition layer, causing a decrease in transmittance and interfering with the laser measurement path, and therefore it is determined to be a high-risk test window contamination scenario. To reduce this type of pollution risk, before entering the charged mine dust scenario, the carbon dioxide flue gas emission monitoring standard measurement device is controlled to load a preventive scenario with opposite parameter trends. This preventive scenario can be selected as a desulfurization-related emission scenario, which has the characteristics of high humidity, moderate flow rate and low particle charge state. Pollution suppression can be achieved in the following ways: using high-humidity gas to form a water film or wet layer on the test window surface to reduce the subsequent adsorption tendency of electrostatic particles; using medium-flow rate perturbations to remove residual particles on the window surface; and adjusting the distribution and dispersion of fine particles in the flue gas to change the subsequent particle deposition behavior. After the desulfurization-related prevention scenario is maintained for a set period of time (for example, 30 seconds to 150 seconds) to ensure that a certain anti-pollution aerodynamic boundary condition is formed at the test window, it is automatically switched to the charged mine dust emission scenario, and simulation and verification are continued in the test sequence. Through this "pre-pollution prevention" strategy, early intervention and control of pollution accumulation in the test window are achieved without changing the overall test process and simulation sequence. Compared with the post-pollution cleaning method, this method is more proactive and controllable, avoiding calibration errors or interruptions in window maintenance due to pollution accumulation, thereby improving the measurement stability and traceability of the carbon dioxide solubility measuring instrument during long-term continuous calibration.

[0074] In some examples, this also includes:

[0075] Periodically acquiring high-precision image data of the same transparent window segment of the transparent test window;

[0076] Analyze the high-precision image data obtained twice, use the frame difference method to compare the differences between the two image data, and identify the coexisting pollution points in the two cycles;

[0077] The contour of the polluted area is extracted by combining threshold segmentation with morphological operations;

[0078] Calculate the geometric characteristics of the contaminated area and, based on the location of the contaminated area, calculate the laser path that may be affected by the laser value traceability module;

[0079] In the case that an affected laser path currently exists, the calibration analysis of the instrument to be calibrated by the quantity traceability module is suspended, and the quantity traceability module includes the LDV and TDLAS gas analyzers.

[0080] Exemplarily, on the basis of the standard measuring device for monitoring carbon dioxide flue gas emissions, a transparent test window contamination monitoring and laser traceability path adjustment mechanism are further integrated to improve the long-term measurement stability of the measurement traceability module (including LDV and TDLAS gas analyzers). During the calibration of the standard measuring device, due to factors such as smoke particulate aerosols, humidity changes, and temperature gradients, the test window may gradually become contaminated, affecting the accuracy of the laser measurement. This method uses periodic high-precision image acquisition and computer vision algorithms to analyze the contaminated area, identify the contamination points on the test window, and calculate the laser path that may be affected based on the location of the contaminated area. When contamination may interfere with the measurement accuracy of LDV or TDLAS, the system will suspend the calibration analysis of the instrument to be calibrated by the measurement traceability module to prevent contamination from causing errors in the measurement results. The core steps of this method include: (1) periodically acquiring high-precision image data of a transparent test window to monitor pollution accumulation; (2) using the frame difference method to compare the two image data before and after, identifying the coexisting pollution points in the dual period, and eliminating short-term smoke interference; (3) using threshold segmentation combined with morphological processing to extract the pollution area and accurately outline the pollution contour; (4) calculating the geometric characteristics of the pollution area and its impact on the laser path to determine whether it interferes with the measurement of LDV or TDLAS; (5) when the laser path is affected, suspending the measurement analysis of the value traceability module to avoid erroneous measurement data affecting the instrument calibration results.

[0081] For example, in order to monitor the contamination of the test window, the system is equipped with a high-precision industrial camera or a macro camera, and a fixed time interval (such as every 10 minutes) is set to image the same transparent window segment of the transparent test window. The camera's installation position must ensure that its viewing angle is consistent with the laser path of the LDV and TDLAS, so that the acquired image data can be directly used for pollution identification. To ensure image clarity, the system uses an autofocus mechanism combined with uniform LED backlighting to improve the contrast of pollutants. After image acquisition is completed, it is stored in the data processing module and a timestamp is added for subsequent time series analysis.

[0082] For example, after acquiring two consecutive high-precision image data, the system uses the frame difference method to compare the images and calculate the pixel difference between the two image data to filter out the interference of short-lived floating particles. Specifically, the frame difference method compares the two images pixel by pixel and calculates the difference image:

[0083] D(x,y)=|I t (x,y)-I t-1 (x,y)|

[0084] Among them, I t (x,y) and I t-1 (x, y) represents the pixel values ​​of the current and previous image cycles, respectively, and D(x, y) represents the pixel difference between the two images. If the difference in a certain area remains large for a long time, it is considered to be a static pollution area rather than a short-term aerosol interference. The system then calculates the coexisting pollution points in the two cycles—that is, the fixed pollution areas that are present in both images. This eliminates pollutants that were briefly attached but then carried away by the airflow, improving detection reliability.

[0085] For example, in order to further identify the polluted area, the system uses an adaptive threshold segmentation algorithm to extract the polluted area from the background. Specifically, grayscale processing is first performed, and then the image binarization algorithm is used to dynamically calculate the optimal segmentation threshold:

[0086]

[0087] in, represents the inter-class variance between foreground and background, The goal is to find a threshold T that maximizes the difference between the foreground and background, thereby accurately segmenting the contaminated area. After completing threshold segmentation, the system applies morphological operations (dilation, erosion, and contour extraction) to smooth the edges of the contaminated area, remove noise interference, and generate accurate contamination contour information. Finally, a binary mask of the contaminated area is output for further analysis of its impact on the laser path.

[0088] For example, after the contaminated area is extracted, the system calculates the geometric features of the contaminated area, including: area, which is used to determine the degree of contamination; shape, which is used to analyze the type of contamination, such as particle attachment or oil film coverage; center coordinates, which are used to calculate the location of the contamination point; and contour bounding box, which is used to determine the scope of contamination. Subsequently, the system matches the location information of the contaminated area with the laser measurement path of LDV and TDLAS. The laser path can be represented as one or more straight lines. If the bounding box of the contaminated area intersects with the straight line, it means that the contaminant may affect the laser transmittance and thus affect the measurement accuracy. For example, in LDV speed measurement, if the contaminated area is located at the penetration point of the laser beam, it may cause signal attenuation or scattering anomalies; in TDLAS gas analysis, if the contamination covers the laser path, it may cause an increase in measurement error. Therefore, the system needs to take further measures to ensure measurement accuracy.

[0089] For example, when the contaminated area affects the laser path of LDV or TDLAS, the system automatically suspends the calibration analysis of the instrument to be calibrated by the measurement traceability module, and activates the alarm mechanism to notify the operator to clean or adjust the measurement path. While pausing the measurement, if the measuring device supports laser angle adjustment, the laser path is adjusted to avoid the contaminated area. Trigger the airflow cleaning system: If the pollution is particulate matter deposition, the high-pressure airflow purge system can be started to clean the test window. Enter the test window cleaning scene: If the pollution is serious, you can first switch to a high-humidity and low-dust emission environment (such as wet desulfurization flue gas), use moisture to clean the pollutants, and then resume measurement.

[0090] In some examples, this also includes

[0091] Determine a new measurement angle to ensure the laser avoids contaminated areas;

[0092] The incident angle of the measurement traceability module is offset to avoid contamination points.

[0093] It is understood that when contamination is detected that may affect the laser transmission path of LDV or TDLAS, the system calculates a new measurement angle to make the laser avoid the contaminated area. The current location information of the contaminated area is used to calculate the minimum rotation angle θ to make the laser path deviate from the contaminated area:

[0094] Among them, Δy and Δx are the vertical and horizontal offsets between the contaminated area and the original laser path, respectively. Adjust the incident angle of the LDV or TDLAS laser, and use a high-precision electric rotation platform or micromirror adjustment mechanism to control the laser path so that it bypasses the contaminated area while maintaining measurement accuracy. After calculating the new measurement angle, the system uses a laser adjustment mechanism driven by a stepper motor or servo motor to slightly offset the laser incident angle of the LDV or TDLAS (usually within 3°) to ensure that its transmission path avoids the contamination point. The offset measurement angle is monitored in real time by the system, and combined with an optical feedback mechanism to ensure that the measurement accuracy is not affected by adjusting the angle. In addition, if the contamination is serious, the system can trigger the airflow cleaning system to purge the test window to restore the optimal measurement state.

[0095] See also Figure 2 An embodiment of a standard measuring device for monitoring carbon dioxide flue gas emissions in the embodiments of the present application is used to calibrate a carbon dioxide emission measuring instrument. The standard measuring device for monitoring carbon dioxide flue gas emissions is constructed in a straight wind tunnel manner and is used to generate aerosols of carbon dioxide gas and smoke particles. The standard measuring device for monitoring carbon dioxide flue gas emissions also includes a value traceability module and a transparent test window at the measurement position. The device may include:

[0096] A division unit 21 is used to divide a plurality of actual emission source simulation scenarios based on the actual emission characteristics of the target industry factory, wherein the carbon dioxide gas generation parameters, smoke particulate matter aerosol generation parameters and environmental parameters of different emission source simulation scenarios are different;

[0097] A control unit 22 is used to control the carbon dioxide flue gas emission monitoring standard measurement device to provide corresponding test parameters according to different actual emission source simulation scenarios;

[0098] The testing unit 23 is used to control the test sequence of multiple actual emission source simulation scenarios in combination with the actual emission patterns of factories in the target industry, so as to calibrate the carbon dioxide emission measuring instrument.

[0099] In summary, the carbon dioxide flue gas emission monitoring and calibration device provided in the embodiment of the present application is divided into multiple actual emission source simulation scenarios based on the actual emission characteristics of the target industry factory. The carbon dioxide gas generation parameters, smoke particle aerosol generation parameters and environmental parameters of different emission source simulation scenarios are different; according to different actual emission source simulation scenarios, the carbon dioxide flue gas emission monitoring standard measurement device is controlled to provide corresponding test parameters; the test sequence of multiple actual emission source simulation scenarios is controlled in combination with the actual emission law of the target industry factory to calibrate the carbon dioxide emission measuring instrument. By simulating the emission characteristics of different factories and controlling parameters such as carbon dioxide concentration, particulate matter concentration, flow rate, temperature and humidity according to actual working conditions, the measurement accuracy and stability of the carbon dioxide concentration measuring instrument can be more comprehensively evaluated and calibrated. In this way, the reliability of the measuring instrument in a variety of industrial emission environments can be ensured, thereby solving the deficiency of the traditional calibration method being limited to a single working condition. By constructing multiple actual emission source simulation scenarios, dynamically controlling the parameters of the standard measurement device and adjusting the test sequence according to the factory emission law, the adaptability and calibration accuracy of the carbon dioxide measuring instrument are comprehensively improved. Compared with traditional calibration methods in a single environment, this method can more realistically reflect industrial emission conditions, enabling measuring instruments to maintain high precision and high stability in various complex environments, providing a reliable standard measurement system for environmental monitoring, industrial emission control and laboratory testing.

[0100] like Figure 3 As shown, an embodiment of the present application further provides an electronic device 300, including a memory 310, a processor 320, and a computer program 311 stored in the memory 320 and executable on the processor. When the processor 320 executes the computer program 311, the steps of any of the above-mentioned methods for carbon dioxide flue gas emission monitoring and calibration are implemented:

[0101] Based on the actual emission characteristics of factories in the target industry, multiple actual emission source simulation scenarios are divided. Different emission source simulation scenarios have different carbon dioxide gas generation parameters, smoke particulate aerosol generation parameters, and environmental parameters;

[0102] Controlling the carbon dioxide flue gas emission monitoring standard measuring device according to different actual emission source simulation scenarios to provide corresponding test parameters;

[0103] Combined with the actual emission patterns of factories in the target industry, the test sequence of multiple actual emission source simulation scenarios is controlled to calibrate the carbon dioxide emission measuring instruments.

[0104] Since the electronic device introduced in this embodiment is the equipment used to implement a carbon dioxide flue gas emission monitoring and calibration device in the embodiment of this application, based on the method introduced in the embodiment of this application, technical personnel in this field can understand the specific implementation of the electronic device of this embodiment and its various variations. Therefore, how the electronic device implements the method in the embodiment of this application will not be introduced in detail here. As long as the equipment used by technical personnel in this field to implement the method in the embodiment of this application falls within the scope of protection of this application.

[0105] In the specific implementation process, the computer program 311 can be implemented when executed by the processor Figure 1 Any implementation manner in the corresponding embodiment:

[0106] Based on the actual emission characteristics of factories in the target industry, multiple actual emission source simulation scenarios are divided. Different emission source simulation scenarios have different carbon dioxide gas generation parameters, smoke particulate aerosol generation parameters, and environmental parameters;

[0107] Controlling the carbon dioxide flue gas emission monitoring standard measuring device according to different actual emission source simulation scenarios to provide corresponding test parameters;

[0108] Combined with the actual emission patterns of factories in the target industry, the test sequence of multiple actual emission source simulation scenarios is controlled to calibrate the carbon dioxide emission measuring instruments.

[0109] It should be noted that, in the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0110] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0111] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0112] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0113] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0114] The present application also provides a computer program product, which includes computer software instructions. When the computer software instructions are executed on a processing device, the processing device is caused to execute the following Figure 1 The process of carbon dioxide flue gas emission monitoring and calibration in the corresponding embodiment.

[0115] A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium can be any available medium that a computer can store or a data storage device such as a server or data center that includes one or more available media integrated. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state drive (SSD)).

[0116] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0117] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0118] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0119] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0120] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0121] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A carbon dioxide flue gas emission monitoring and calibration method, characterized in that: A standard measuring device for monitoring carbon dioxide flue gas emissions is used to calibrate a carbon dioxide emission measuring instrument. The standard measuring device for monitoring carbon dioxide flue gas emissions is constructed in a straight wind tunnel manner and is used to generate carbon dioxide gas and smoke particle aerosols. The standard measuring device for monitoring carbon dioxide flue gas emissions also includes a value traceability module and a transparent test window at the measurement position. The method includes: Based on the actual emission characteristics of factories in the target industry, multiple actual emission source simulation scenarios are divided. Different emission source simulation scenarios have different carbon dioxide gas generation parameters, smoke particulate aerosol generation parameters, and environmental parameters; Controlling the carbon dioxide flue gas emission monitoring standard measuring device according to different actual emission source simulation scenarios to provide corresponding test parameters; Combined with the actual emission patterns of factories in the target industry, the test sequence of multiple actual emission source simulation scenarios is controlled to calibrate the carbon dioxide emission measuring instruments.

2. The method according to claim 1, wherein Also includes: Evaluating the test window contamination risk levels of the plurality of actual emission source simulation scenarios according to the test parameters of the different emission source simulation scenarios, so as to divide the plurality of actual emission source simulation scenarios into test window contamination scenarios and test window cleaning scenarios based on the test window contamination risk levels; When the previous actual emission source simulation scenario is a test window pollution scenario, the carbon dioxide flue gas emission monitoring standard measurement device is controlled to provide corresponding test parameters to provide a test window cleaning scenario, and then switch to the next actual emission source simulation scenario in the test sequence after a predetermined period of time.

3. The method according to claim 2, wherein When the previous actual emission source simulation scene is a test window pollution scene, controlling the carbon dioxide flue gas emission monitoring standard measurement device to provide corresponding test parameters to provide a test window cleaning scene, and switching to the next actual emission source simulation scene in the test sequence after a predetermined time, includes: When the previous actual emission source simulation scenario is a charged mine dust emission scenario, the carbon dioxide flue gas emission monitoring standard measurement device is controlled to provide corresponding test parameters to provide a desulfurization-related emission scenario, and then switch to the next actual emission source simulation scenario in the test sequence after a predetermined period of time.

4. The method according to claim 1, wherein Also includes: Evaluating the test window pollution risk levels of the plurality of actual emission source simulation scenarios according to the test parameters of the different emission source simulation scenarios, so as to divide the plurality of actual emission source simulation scenarios into test window pollution scenarios and prevention scenarios associated with the scenarios based on the test window pollution risk levels; Before providing the test window pollution scenario according to the test sequence, the carbon dioxide flue gas emission monitoring standard measurement device is controlled to provide corresponding test parameters to provide the prevention scenario, and then switched to the test window pollution scenario after a predetermined period of time.

5. The method according to claim 4, wherein Before providing the test window pollution scenario according to the test sequence, controlling the carbon dioxide flue gas emission monitoring standard measurement device to provide corresponding test parameters to provide the prevention scenario, and switching to the test window pollution scenario after a predetermined time, includes: Before providing the charged mine dust emission scenario according to the test sequence, the carbon dioxide flue gas emission monitoring standard measurement device is controlled to provide corresponding test parameters to provide a desulfurization-related emission scenario, and then switched to the charged mine dust emission scenario after a predetermined period of time.

6. The method according to any one of claims 1 to 5, characterized in that Also includes: Periodically acquiring high-precision image data of the same transparent window segment of the transparent test window; Analyze the high-precision image data obtained twice, use the frame difference method to compare the differences between the two image data, and identify the coexisting pollution points in the two cycles; The contour of the polluted area is extracted by combining threshold segmentation with morphological operations; Calculate the geometric characteristics of the contaminated area and, based on the location of the contaminated area, calculate the laser path that may be affected by the laser value traceability module; In the case that an affected laser path currently exists, the calibration analysis of the instrument to be calibrated by the quantity traceability module is suspended, and the quantity traceability module includes the LDV and TDLAS gas analyzers.

7. The method according to claim 6, wherein Also includes Determine a new measurement angle to ensure the laser avoids contaminated areas; The incident angle of the measurement traceability module is offset to avoid contamination points.

8. A standard measuring device for monitoring carbon dioxide flue gas emissions, characterized in that: Used to calibrate carbon dioxide emission measuring instruments, the carbon dioxide flue gas emission monitoring standard measuring device is built in a straight wind tunnel manner and is used to generate carbon dioxide gas and smoke particle aerosols. The carbon dioxide flue gas emission monitoring standard measuring device also includes a value traceability module and a transparent test window at the measurement position. The carbon dioxide flue gas emission monitoring standard measuring device includes: The division unit is used to divide multiple actual emission source simulation scenarios based on the actual emission characteristics of factories in the target industry. Different emission source simulation scenarios have different carbon dioxide gas generation parameters, smoke particulate aerosol generation parameters, and environmental parameters; A control unit, configured to control the carbon dioxide flue gas emission monitoring standard measuring device to provide corresponding test parameters according to different actual emission source simulation scenarios; The test unit is used to control the test sequence of multiple actual emission source simulation scenarios based on the actual emission patterns of target industry factories to calibrate carbon dioxide emission measuring instruments.

9. An electronic device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor is configured to implement the steps of the carbon dioxide flue gas emission monitoring and calibration method according to any one of claims 1 to 7 when executing the computer program stored in the memory.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the carbon dioxide flue gas emission monitoring and calibration method according to any one of claims 1 to 7 is implemented.

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