Industrial combustion optimization method and apparatus

Abstract

The embodiment of the present specification provides an industrial combustion optimization method, device, computing equipment, computer readable storage medium and computer program product, wherein the industrial combustion optimization method comprises: determining a combustion reference condition of an industrial combustion equipment and equipment air volume information of the industrial combustion equipment in response to a combustion optimization request triggered for the industrial combustion equipment; loading a gas composition analysis model and a gas temperature analysis model associated with the industrial combustion equipment, wherein the gas composition analysis model is constructed based on a relationship between air volume and gas composition, and the gas temperature analysis model is constructed based on a time series prediction algorithm; processing the equipment air volume information through the gas composition analysis model and the gas temperature analysis model to obtain gas composition information and gas temperature information corresponding to the equipment air volume information; and adjusting the air volume of the industrial combustion equipment according to the equipment air volume information in the case that the gas composition information and the gas temperature information meet the combustion reference condition.

Description

Technical Field

[0001] The embodiments in this specification relate to the field of combustion control technology, and in particular to industrial combustion optimization methods and apparatus. Background Technology

[0002] With the development of industrial technology, projects in industries such as cement, solid waste, power generation, and heating all have certain requirements for the completeness of combustion of combustibles. Optimizing the combustion process can reduce energy consumption, save costs, and achieve the goals of energy conservation and carbon reduction. However, as the structure of industrial combustion equipment continues to iterate and the composition of combustibles becomes more diverse, the combustion process has become more complex. Theoretically, it is necessary to use complex mechanisms such as fluid mechanics and chemical kinetics to perform simulation calculations for different equipment in order to optimize the combustion process. Although such combustion optimization schemes can achieve the goal of combustion optimization, they consume a lot of time and costs, and due to the error between simulation calculations and actual conditions, the final optimization effect is difficult to achieve as expected. Therefore, there is an urgent need for an effective solution to address the above problems. Summary of the Invention

[0003] In view of this, embodiments of this specification provide an industrial combustion optimization method. One or more embodiments of this specification also relate to an industrial combustion optimization apparatus, a computing device, a computer-readable storage medium, and a computer program product, to address the technical deficiencies existing in the prior art.

[0004] According to a first aspect of the embodiments of this specification, an industrial combustion optimization method is provided, comprising:

[0005] In response to a combustion optimization request triggered by an industrial combustion device, determine the combustion baseline conditions and equipment airflow information of the industrial combustion device.

[0006] Load the gas composition analysis model and gas temperature analysis model associated with the industrial combustion equipment, wherein the gas composition analysis model is constructed based on the relationship between air volume and gas composition, and the gas temperature analysis model is constructed based on a time series prediction algorithm;

[0007] The gas composition analysis model and the gas temperature analysis model are used to process the air volume information of the equipment to obtain the gas composition information and gas temperature information corresponding to the air volume information of the equipment.

[0008] If the gas composition information and the gas temperature information meet the combustion reference conditions, the air volume of the industrial combustion equipment is adjusted according to the equipment air volume information.

[0009] According to a second aspect of the embodiments of this specification, another industrial combustion optimization method is provided, applied to cloud-side equipment, comprising:

[0010] Receive combustion optimization requests submitted by the end-side devices of industrial combustion equipment, and determine the combustion baseline conditions and equipment airflow information of industrial combustion equipment based on the combustion optimization requests;

[0011] Load the gas composition analysis model and gas temperature analysis model associated with the industrial combustion equipment, wherein the gas composition analysis model is constructed based on the relationship between air volume and gas composition, and the gas temperature analysis model is constructed based on a time series prediction algorithm;

[0012] The gas composition analysis model and the gas temperature analysis model are used to process the air volume information of the equipment to obtain the gas composition information and gas temperature information corresponding to the air volume information of the equipment.

[0013] When the gas composition information and the gas temperature information meet the combustion reference conditions, the equipment airflow information is sent to the end-side device to adjust the airflow of the industrial combustion equipment.

[0014] According to a third aspect of the embodiments of this specification, an industrial combustion optimization device is provided, comprising:

[0015] The determination module is configured to determine the combustion baseline conditions and equipment airflow information of the industrial combustion equipment in response to a combustion optimization request triggered for the industrial combustion equipment.

[0016] The loading module is configured to load the gas composition analysis model and gas temperature analysis model associated with the industrial combustion equipment, wherein the gas composition analysis model is constructed based on the relationship between air volume and gas composition, and the gas temperature analysis model is constructed based on a time-series prediction algorithm.

[0017] The processing module is configured to process the equipment airflow information through the gas composition analysis model and the gas temperature analysis model to obtain the gas composition information and gas temperature information corresponding to the equipment airflow information;

[0018] The adjustment module is configured to adjust the airflow of the industrial combustion equipment according to the equipment airflow information, provided that the gas composition information and the gas temperature information meet the combustion reference conditions.

[0019] According to a fourth aspect of the embodiments of this specification, another industrial combustion optimization device is provided, applied to cloud-side equipment, comprising:

[0020] The request receiving module is configured to receive combustion optimization requests submitted by the end-side devices of the industrial combustion equipment, and determine the combustion baseline conditions and equipment airflow information of the industrial combustion equipment based on the combustion optimization requests.

[0021] The loading model module is configured to load the gas composition analysis model and gas temperature analysis model associated with the industrial combustion equipment, wherein the gas composition analysis model is constructed based on the relationship between air volume and gas composition, and the gas temperature analysis model is constructed based on a time-series prediction algorithm;

[0022] The information processing module is configured to process the equipment airflow information through the gas composition analysis model and the gas temperature analysis model to obtain the gas composition information and gas temperature information corresponding to the equipment airflow information;

[0023] The information transmission module is configured to send the equipment airflow information to the end-side device when the gas composition information and the gas temperature information meet the combustion reference conditions, so as to adjust the airflow of the industrial combustion equipment.

[0024] According to a fifth aspect of the embodiments of this specification, a computing device is provided, comprising:

[0025] Memory and processor;

[0026] The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions, which, when executed by the processor, implement the steps of the above-described industrial combustion optimization method.

[0027] According to a sixth aspect of the embodiments of this specification, a computer-readable storage medium is provided that stores computer-executable instructions that, when executed by a processor, implement the steps of the above-described industrial combustion optimization method.

[0028] According to a seventh aspect of the embodiments of this specification, a computer program product is provided, including a computer program or instructions that, when executed by a processor, implement the steps of the above-described industrial combustion optimization method.

[0029] The industrial combustion optimization method provided in this embodiment aims to improve combustion optimization efficiency, reduce carbon emissions, and achieve energy conservation. Upon triggering a combustion optimization request for industrial combustion equipment, it determines the corresponding combustion baseline conditions and equipment airflow information in response to the request. Subsequently, to improve the combustion optimization efficiency of the industrial combustion equipment, a gas composition analysis model based on the relationship between airflow and gas composition, and a gas temperature analysis model based on a time-series prediction algorithm, can be loaded. Then, the gas composition and temperature analysis models can be used to perform gas composition and temperature analysis on the equipment airflow information, thereby obtaining the gas composition and temperature information corresponding to the combustion gas of the industrial combustion equipment under the current equipment airflow information. This gas composition and temperature information reflects the combustion effect of the industrial combustion equipment under the current equipment airflow information. Therefore, by combining gas composition and temperature information, it can be determined whether the current combustion effect meets the combustion baseline conditions. If not, it indicates that the current equipment airflow information cannot enable the industrial combustion equipment to achieve a higher combustion rate or lower energy consumption. Therefore, new equipment airflow information can be selected for further testing until the conditions are met. Then, the airflow of the industrial combustion equipment can be adjusted according to the equipment airflow information that meets the conditions to improve the complete combustion of the combustibles and reduce the heat carried away by the equipment exhaust gas. This will enable the industrial combustion equipment to have better combustion performance under the current combustion conditions, thereby saving energy and reducing carbon emissions. Attached Figure Description

[0030] Figure 1 This is a schematic diagram of an industrial combustion optimization method provided in one embodiment of this specification;

[0031] Figure 2 This is a flowchart illustrating an industrial combustion optimization method provided in one embodiment of this specification;

[0032] Figure 3 This is a process flow diagram of an industrial combustion optimization method provided in one embodiment of this specification;

[0033] Figure 4 This is a flowchart of another industrial combustion optimization method provided in one embodiment of this specification;

[0034] Figure 5 This is a schematic diagram of the structure of an industrial combustion optimization device provided in one embodiment of this specification;

[0035] Figure 6 This is a schematic diagram of another industrial combustion optimization device provided in one embodiment of this specification;

[0036] Figure 7This is a structural block diagram of a computing device provided in one embodiment of this specification. Detailed Implementation

[0037] Many specific details are set forth in the following description to provide a full understanding of this specification. However, this specification can be implemented in many other ways than those described herein, and those skilled in the art can make similar extensions without departing from the spirit of this specification. Therefore, this specification is not limited to the specific implementations disclosed below.

[0038] The terminology used in one or more embodiments of this specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the one or more embodiments of this specification. The singular forms “a,” “described,” and “the” as used in one or more embodiments of this specification and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in one or more embodiments of this specification refers to and includes any or all possible combinations of one or more associated listed items.

[0039] It should be understood that although the terms first, second, etc., may be used to describe various information in one or more embodiments of this specification, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, first may also be referred to as second without departing from the scope of one or more embodiments of this specification, and similarly, second may also be referred to as first. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to a determination."

[0040] Furthermore, it should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in one or more embodiments of this specification are all information and data authorized by the user or fully authorized by all parties. Moreover, the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0041] First, the terms and concepts used in one or more embodiments of this specification will be explained.

[0042] Model Predictive Control (MPC) is an advanced process control method that employs a model-based closed-loop optimization control strategy. It achieves system control through key steps such as predictive modeling, rolling optimization, and feedback correction. The main idea is to obtain the current control action at each sampling instant by solving a finite-time open-loop optimal control problem. This optimal control problem is typically solved by minimizing a performance index function, which contains a weighted sum of the system state and control inputs.

[0043] The Transformer is a model designed for sequence-to-sequence (end-to-end) tasks, primarily consisting of two parts: an encoder and a decoder. Both parts contain multiple identical layers, each with two sub-layers: the first sub-layer uses a multi-head self-attention mechanism, and the second sub-layer is a position-based feedforward neural network. Each sub-layer employs residual connections.

[0044] This specification provides an industrial combustion optimization method, and also relates to an industrial combustion optimization device, a computing device, a computer-readable storage medium, and a computer program product, which are described in detail in the following embodiments.

[0045] See Figure 1The schematic diagram illustrates the industrial combustion optimization method provided in this embodiment. To improve combustion optimization efficiency, reduce carbon emissions, and achieve energy conservation, the method determines the corresponding combustion baseline conditions and airflow information of the industrial combustion equipment in response to a combustion optimization request triggered by the equipment. Subsequently, to improve the combustion optimization efficiency, a gas composition analysis model based on the relationship between airflow and gas composition, and a gas temperature analysis model based on a time-series prediction algorithm, can be loaded. The gas composition and temperature analysis models can then be used to perform gas composition and temperature analysis on the equipment airflow information, thereby obtaining the gas composition and temperature information corresponding to the combustion gas of the industrial combustion equipment under the current airflow information. This gas composition and temperature information reflects the combustion effect of the industrial combustion equipment under the current airflow information. Therefore, by combining gas composition and temperature information, it can be determined whether the current combustion effect meets the combustion baseline conditions. If not, it indicates that the current equipment airflow information cannot enable the industrial combustion equipment to achieve a higher combustion rate or lower energy consumption. Therefore, new equipment airflow information can be selected for further testing until the conditions are met. Then, the airflow of the industrial combustion equipment can be adjusted according to the equipment airflow information that meets the conditions to improve the complete combustion of the combustibles and reduce the heat carried away by the equipment exhaust gas. This will enable the industrial combustion equipment to have better combustion performance under the current combustion conditions, thereby saving energy and reducing carbon emissions.

[0046] See Figure 2 , Figure 2 A flowchart of an industrial combustion optimization method according to an embodiment of this specification is shown, which specifically includes the following steps.

[0047] Step S202: In response to a combustion optimization request triggered for the industrial combustion equipment, determine the combustion baseline conditions and equipment airflow information of the industrial combustion equipment.

[0048] The industrial combustion optimization method provided in this embodiment can be applied to any scenario with combustion optimization needs, such as power generation, solid waste, cement, and chemical industries. These scenarios require the combustion of combustibles such as coal, garbage, and straw to generate electricity, produce steam, or provide heat for chemical reactions. However, industrial combustion equipment generates carbon emissions. To reduce carbon emissions and save energy, combustion can be optimized by combining combustion mechanisms and machine learning methods. By exploring the relationship between airflow and gas temperature, as well as airflow and gas composition, the airflow can be adjusted to change the completeness of combustion of the combustibles, thereby achieving carbon reduction and energy conservation. This embodiment uses a boiler in a heating scenario as an example to illustrate the industrial combustion optimization method. The same or corresponding descriptions in other scenarios can be found in this embodiment, and will not be elaborated upon further here.

[0049] Specifically, industrial combustion equipment refers to equipment that burns materials in different industrial combustion scenarios; for example, boilers that burn coal and straw in power generation and heating scenarios; incinerators that burn coal and garbage in solid waste scenarios; and furnaces that burn coal in chemical scenarios. Correspondingly, a combustion optimization request specifically refers to an optimization request triggered by industrial combustion equipment. This request is used to optimize the combustion of industrial combustion equipment. The purpose of optimization is to adjust the exhaust gas flow rate of the industrial combustion equipment, so that the exhaust gas can carry away less heat, thereby ensuring that the heat generated by combustion can be fully utilized to reduce energy consumption. The combustion optimization request can be triggered in various ways: it can be triggered at a set time, such as once every 5 minutes; it can be triggered when the material to be burned changes, such as when the material to be burned changes from coal to straw; or it can be triggered manually. In practical applications, it can be set according to actual needs, and this embodiment does not impose any limitations. Correspondingly, combustion baseline conditions specifically refer to the conditions that need to be met when optimizing the combustion of industrial combustion equipment. Since the purpose of combustion optimization is to reduce the amount of heat carried away by exhaust gases, combustion baseline conditions can be used as an indicator to measure the heat in the exhaust gases. If the heat in the exhaust gases meets the combustion baseline conditions by changing the airflow of the industrial combustion equipment, it means that the current combustion conditions can promote higher combustion efficiency and lower energy consumption. Correspondingly, equipment airflow information specifically refers to the initial airflow information set for the industrial combustion equipment during the current combustion optimization phase. By predicting the equipment airflow information, the amount of heat in the exhaust gases under that airflow information can be understood. By continuously adjusting the equipment airflow information to reduce the heat in the exhaust gases and reach the combustion baseline conditions, the adjusted equipment airflow information can be used as the airflow that the industrial combustion equipment needs to control.

[0050] Therefore, to improve combustion optimization, reduce carbon emissions, and achieve energy conservation, upon triggering a combustion optimization request for industrial combustion equipment, the corresponding combustion baseline conditions and equipment airflow information for the industrial combustion equipment can be determined in response to the request. Subsequently, to improve the combustion optimization efficiency of the industrial combustion equipment, a gas composition analysis model based on the relationship between airflow and gas composition, and a gas temperature analysis model based on a time-series prediction algorithm, can be loaded. Then, the gas composition and temperature analysis models can be used to process the equipment airflow information, thereby obtaining the gas composition and temperature information corresponding to the combustion gas of the industrial combustion equipment under the current equipment airflow information. This gas composition and temperature information reflects the combustion effect of the industrial combustion equipment under the current equipment airflow information. Therefore, by combining gas composition and temperature information, it can be determined whether the current combustion effect meets the combustion baseline conditions. If not, it indicates that the current equipment airflow information cannot enable the industrial combustion equipment to achieve a higher combustion rate or lower energy consumption. Therefore, new equipment airflow information can be selected for further testing until the conditions are met. Then, the airflow of the industrial combustion equipment can be adjusted according to the equipment airflow information that meets the conditions to improve the complete combustion of the combustibles and reduce the heat carried away by the equipment exhaust gas. This will enable the industrial combustion equipment to have better combustion performance under the current combustion conditions, thereby saving energy and reducing carbon emissions.

[0051] Furthermore, when determining the combustion baseline conditions and equipment airflow information, in order to ensure that the industrial combustion equipment achieves better combustion results and saves more energy consumption, a combustion optimization request can be triggered when changes in the combustible material are detected, and then an appropriate airflow can be selected for the current combustion optimization process. In this embodiment, the specific implementation method is as follows:

[0052] When a change in the combustor of an industrial combustion device is detected, a combustion optimization request is constructed for the industrial combustion device; in response to the combustion optimization request, an energy consumption optimization target corresponding to the industrial combustion device is determined, wherein the energy consumption optimization target is determined based on the target gas combustion heat and gas hot air heat; the energy consumption optimization target is used as the combustion baseline condition, and test air volume information is created for the industrial combustion device according to the combustion optimization request, which is used as the device air volume information.

[0053] Specifically, a change in the combustible material refers to a change in the object being burned by the industrial combustion equipment to another object, or a change in the quantity / volume of the combustible material. Correspondingly, the energy consumption optimization target refers to an index based on the target gas combustion heat and the gas hot air heat composition. A smaller index indicates more complete combustion, less heat carried away by the exhaust gas, and lower energy consumption. Therefore, the energy consumption optimization index is a suitable heat value selected under the current conditions, such as the minimum heat value. This value is calculated by summing the target gas combustion heat and the gas hot air heat. Correspondingly, the airflow information to be tested refers to the airflow information used for heat calculation under the current conditions. When the energy consumption optimization target is met, i.e., the total heat reaches the minimum heat, it can be used to adjust the airflow of the industrial combustion equipment.

[0054] Therefore, when a change in the combustible material of an industrial combustion device is detected, it indicates that the original airflow of the device may not be suitable for the changed material, potentially leading to more heat being carried away by the exhaust gas. To reduce energy consumption and save costs, the combustion process can be optimized after the change. First, a combustion optimization request can be created for the industrial combustion device. Then, in response to the request, an energy consumption optimization target can be determined, based on the minimum sum of the target gas combustion heat and the gas hot air heat. This target serves as the combustion baseline condition. Simultaneously, test airflow information is created for the device based on the optimization request, serving as its airflow information. This airflow information is then continuously adjusted using the combustion baseline condition as a constraint to obtain the appropriate airflow for the current state, thereby achieving energy savings.

[0055] For example, in a solid waste combustion scenario, if the waste fed into the incinerator is a difficult-to-burn fuel, the same airflow will lead to an increase in CO content, resulting in more heat being carried away in the exhaust gas and causing energy waste. To save energy consumption, a combustion optimization request can be established for the waste incinerator. Based on the combustion optimization request, the optimization objective of the waste incinerator can be determined as: minimizing the heat carried away by the exhaust gas. That is, minimizing the total heat of CO combustion and the heat of hot air in the exhaust gas. Factors affecting the total heat include not only the CO content in the exhaust gas but also the exhaust gas temperature. Both the CO content and the exhaust gas temperature are affected by the airflow of the waste incinerator. Therefore, by adjusting the inlet and outlet airflow of the waste incinerator, the CO content and exhaust gas temperature can be changed, thereby minimizing the total heat. To save energy, reduce computational costs, and shorten time, a test airflow information F can be created for the waste incinerator. This test airflow information can then be adjusted until the target airflow information is obtained, minimizing the total heat. This allows for the adjustment of the inlet and outlet airflow of the waste incinerator, thereby reducing energy consumption.

[0056] In summary, by combining the target gas combustion heat and the gas hot air heat to determine the combustion baseline conditions, and using these as constraints for testing equipment airflow information, we can ensure that the testing of airflow information for different equipment can be completed quickly and accurately at the computational level, thereby reducing time costs and rapidly optimizing the combustion of industrial combustion equipment.

[0057] Step S204: Load the gas composition analysis model and gas temperature analysis model associated with the industrial combustion equipment, wherein the gas composition analysis model is constructed based on the relationship between air volume and gas composition, and the gas temperature analysis model is constructed based on a time-series prediction algorithm.

[0058] Specifically, after determining the combustion baseline conditions and airflow information for the industrial combustion equipment, the airflow information can be tested under the constraints of the combustion baseline conditions to determine if it is suitable for the current combustion stage of the industrial combustion equipment. Before testing, to reduce time costs and improve efficiency, and to quickly adjust the airflow of the industrial combustion equipment while avoiding energy waste, the associated gas composition analysis model and gas temperature analysis model can be loaded. This allows the gas composition analysis model, based on the relationship between airflow and gas composition, to detect whether the airflow information meets the combustion baseline conditions from an influencing perspective, and the gas temperature analysis model, based on a time-series prediction algorithm, to detect whether the airflow information meets the combustion baseline conditions from an algorithmic perspective. Based on the test results, more suitable airflow information can be selected to adjust the airflow of the industrial combustion equipment.

[0059] Specifically, the gas composition analysis model refers to a model built based on the relationship between airflow and gas composition in industrial combustion equipment. In other words, the composition of the gas produced after combustion in industrial combustion equipment is related to the airflow. By exploring the relationship between airflow and gas composition, a gas composition analysis model is constructed. This allows the model to determine the gas composition corresponding to the airflow information when testing equipment airflow information, based on the relationships recorded in the model, for subsequent thermal analysis. Correspondingly, the gas temperature analysis model refers to a model built based on time-series prediction algorithms, such as the Transformer architecture, or it can be implemented using regression algorithms such as XGBoot and linear regression. By inputting airflow information into the model, it can predict the gas temperature under the given airflow information, for subsequent thermal analysis.

[0060] It should be noted that different industrial combustion equipment will correspond to different gas temperature analysis models and gas composition analysis models, thereby ensuring that the processing results correspond to the industrial combustion equipment and ensuring the accuracy of the equipment's air volume information detection.

[0061] Furthermore, in order to construct a gas composition analysis model for industrial combustion equipment and thus improve the accuracy of gas composition analysis, it can be constructed by combining changes in air volume and gas content. In this embodiment, the specific implementation is as follows:

[0062] A gas analyzer is used to determine the content of a first gas and a second gas in the combustion exhaust gas of the industrial combustion equipment, and a gas content relationship is established between the first gas content and the second gas content. When the content of the first gas in the combustion exhaust gas changes, the content of the second gas after the change is determined based on the changed first gas content and the gas content relationship, as well as the first air volume information before the change and the second air volume information after the change. Based on the first air volume information, the second air volume information, the first gas content and the second gas content before the change, and the first gas content and the second gas content after the change, a gas composition analysis model is constructed.

[0063] Specifically, a gas analyzer is a device used to detect the composition and concentration of gases. Its working principle involves measuring the interaction between the gas and a sensor to infer the type and concentration of the gas. Correspondingly, combustion exhaust gas refers to the exhaust gas produced by industrial combustion equipment after burning fuel. The first gas content specifically refers to the carbon monoxide (CO) content in the combustion exhaust gas, and the second gas content specifically refers to the oxygen (O2) content. The gas content relationship specifically refers to the relationship between the first and second gas contents in the combustion exhaust gas. Because the first and second gases have a chemical reaction relationship, this relationship allows us to determine the unknown second gas content or first gas content when the first or second gas content is known. Similarly, the first airflow information specifically refers to the airflow information before the change in the first gas content in the exhaust gas, and the second airflow information specifically refers to the airflow information after the change in the first gas content in the exhaust gas. By exploring the relationships between the first gas content, second gas content, and airflow information before and after the change, a gas composition analysis model can be constructed.

[0064] Based on this, in constructing a gas composition analysis model, to uncover the relationship between airflow and gas composition, and thus to deduce gas composition during airflow information analysis and subsequently perform heat analysis, a gas analyzer can be used to first determine the content of a first gas and a second gas in the combustion exhaust gas of industrial combustion equipment. Based on these contents, a gas content relationship between the first and second gas contents can be established. Then, when the first gas content in the combustion exhaust gas changes, this gas content relationship and the changed first gas content can be used to determine the changed second gas content. To further uncover the relationship between airflow and content, the first airflow information before the change and the second airflow information after the change can be determined. Finally, based on the first airflow information, the second airflow information, the first and second gas contents before and after the change, a gas composition analysis model can be constructed. This model can be used to analyze the gas composition during the equipment airflow information analysis phase, thereby completing heat detection.

[0065] In practice, the CO and O2 contents in the combustion exhaust gas of the industrial combustion equipment can be determined first by using historical data collected by a gas evaluator under normal operating conditions. Then, a relationship model F(x) between CO and O2 can be established based on their contents in the exhaust gas. Next, the CO content (CO_0) of the industrial combustion equipment during production can be obtained using the gas evaluator. According to the relationship model F(x), the O2 content under the current condition can be calculated as O2_0 = F(CO_0). Assuming a 1 ppm change in CO, the changed CO content (CO_d) = CO_0 + 1 / 1000000. Through the relationship model, the O2 content (O2_d) after the CO content change can be obtained as F(CO_d).

[0066] Furthermore, obtain the air volume air_0 before the CO change and the air volume air_d after the change; at this time, assume that the change of O2 comes entirely from the change of air volume and the chemical reaction between CO2 and CO, and then the relationship between them can be obtained as: changed air volume * changed O2 content + changed air volume * changed CO content / 2 + changed air volume * changed CO2 content = changed air volume * changed O2 content + changed air volume * changed CO content / 2 + changed air volume * changed CO2 content + (changed air volume - changed air volume) * 0.21, and the corresponding formula (1) is: air_d * O2_d + air_d * CO_d / 2 + air_d * CO2_d = air_0 * O2_0 + air_0 * CO_0 / 2 + air_0 * CO2_0 + (air_d - air_0) * 0.21.

[0067] Furthermore, assuming that the burnout rate of C has not changed, we can obtain the following relationship: changed air volume * changed CO content + changed air volume * changed CO2 content = original air volume * original CO content + original air volume * original CO2 content; the corresponding formula (2) is: air_d * CO_d + air_d * CO2_d = air_0 * CO_0 + air_0 * CO2_0. By subtracting formula (1) from formula (2), we can obtain the following relationship: air_d * O2_d - air_d * CO_d / 2 = air_0 * O2_0 - air_0 * CO_0 / 2 + (air_d - air_0) * 0.21. Therefore, after the CO content changes, the air volume air_d = air_0 * (O2_0 - 0.21 - CO_0 / 2) / (O2_d - 0.21 - CO_d / 2).

[0068] Based on this, the relationship between increasing CO by 1 ppm and the change in airflow is delta = air_d - air_0; the relationship between increasing CO by 1 ppm and the change in total CO is delta_CO = air_d * CO_d - air_0 * CO_0; and the relationship between changing a unit airflow and the change in CO is delta_co / delta. Furthermore, a gas composition analysis model can be constructed based on the airflow, oxygen, and carbon monoxide content before and after the change. In the application stage, this model can be directly used to determine the gas composition under any airflow setting for subsequent heat analysis, thereby achieving the goal of combustion optimization for industrial combustion equipment.

[0069] In summary, by combining the air volume information before and after the change, as well as the contents of the first and second gases, the relationship between air volume and gas composition changes is fully explored. This leads to the construction of a gas composition analysis model for industrial combustion equipment. Once any air volume information to be tested is determined, the exhaust gas composition can be determined using this model. This allows for the theoretical detection of air volume information, thereby improving the combustion optimization efficiency of industrial combustion equipment.

[0070] Furthermore, in order to train a machine learning model that accurately predicts gas temperature, training can be performed using sample pairs contained in the sample set. In this embodiment, the specific implementation is as follows:

[0071] Target sample pairs are selected from the sample set corresponding to the industrial combustion equipment, wherein the target sample pair consists of sample air volume information and sample gas temperature information; the sample air volume information is input into the initial gas temperature analysis model for processing to obtain the predicted gas temperature information corresponding to the sample air volume information; a loss value is calculated based on the sample gas temperature information and the predicted gas temperature information, and the parameters of the initial gas temperature analysis model are adjusted based on the loss value until the gas temperature analysis model that meets the training stopping condition is obtained.

[0072] Specifically, the sample set refers to a combination of sample pairs constructed from real data collected from industrial combustion equipment. Each sample pair consists of sample airflow information and sample gas temperature information, both of which are data collected under real-world conditions from industrial combustion equipment. This ensures that the trained model matches the industrial combustion equipment and exhibits stronger robustness. Correspondingly, the predicted gas temperature information refers to the temperature information predicted after inputting the sample airflow information into the model. And correspondingly, the training stopping condition refers to the conditions under which training the gas temperature analysis model is stopped, including but not limited to loss value comparison conditions, iteration count conditions, or validation set conditions.

[0073] Based on this, when training a usable gas temperature analysis model, target sample pairs can be selected from the sample set corresponding to industrial combustion equipment. These target sample pairs consist of sample airflow information and sample gas temperature information. Therefore, the sample airflow information can be input into the initial gas temperature analysis model for processing. Based on the processing results, the predicted gas temperature information corresponding to the sample airflow information can be obtained. Subsequently, the loss value can be calculated based on the sample gas temperature information and the predicted gas temperature information. Then, the parameters of the initial gas temperature analysis model can be tuned based on the loss value. The predictive ability of the tuned model can be checked to see if it meets the training stopping condition. If it does not meet the condition, new samples can be selected from the sample set for training until a gas temperature analysis model that meets the training stopping condition is obtained and deployed.

[0074] In practice, the sample set used to train the model can be constructed by collecting data from sensors such as an air volume meter. In the model training stage, in order to improve the prediction accuracy of the model and achieve the expected purpose, combustion-related variables, such as combustion air temperature and fuel quantity, can be set as covariates of the algorithm to model the dynamic relationship between air volume and exhaust gas temperature, thereby obtaining a gas temperature analysis model that can input air volume information and output temperature information.

[0075] In summary, by training the model using a sample set built from real samples, the trained model can be made more robust, thus ensuring the accuracy and precision of testing equipment airflow information.

[0076] Step S206: Process the equipment airflow information using the gas composition analysis model and the gas temperature analysis model to obtain the gas composition information and gas temperature information corresponding to the equipment airflow information.

[0077] Specifically, after loading the gas temperature analysis model and gas composition analysis model used to analyze the equipment's airflow information, the airflow information can be further processed using these two types of analysis models. This allows for the determination of the gas composition and temperature information of the exhaust gas generated after adjusting the airflow according to the theoretical conditions of the industrial combustion equipment. Subsequently, by comparing the gas composition and temperature information with the combustion baseline conditions, it can be determined whether the airflow information can minimize heat waste in the industrial combustion equipment. This completes the combustion optimization operation of the industrial combustion equipment.

[0078] Specifically, the gas composition information refers to the gas composition information of the exhaust gas produced by the industrial combustion equipment after fuel combustion, obtained by processing the equipment's airflow information using a gas composition analysis model, within a defined computational dimension. This gas composition information includes the content of each gas in the exhaust gas. Correspondingly, the gas temperature information refers to the temperature information of the exhaust gas produced by the industrial combustion equipment after fuel combustion, obtained by predicting the equipment's airflow information using a gas temperature analysis model.

[0079] Furthermore, when processing equipment airflow information using gas composition analysis models and gas temperature analysis models, the actual process involves analyzing temperature and composition based on changes in airflow. In this embodiment, the specific implementation is as follows:

[0080] The airflow change relationship recorded in the gas composition analysis model is determined. Based on the equipment airflow information and the airflow change relationship, the gas composition information corresponding to the equipment airflow information is calculated, wherein the airflow change relationship records the relationship between airflow and gas composition. The equipment airflow information is input into the gas temperature analysis model. The equipment airflow information is encoded by the encoder in the gas temperature analysis model, and the encoding result is decoded by the decoder in the gas temperature analysis model to obtain the gas temperature information corresponding to the equipment airflow information.

[0081] Specifically, the airflow variation relationship refers to the relationship obtained after analyzing the airflow and gas composition of industrial combustion equipment. This relationship allows for the calculation of gas composition information given a fixed airflow. Correspondingly, the gas temperature analysis model refers to a model composed of an encoder and decoder architecture.

[0082] Based on this, when performing gas temperature and composition analysis based on equipment airflow information, the relationship between airflow changes and gas composition recorded in the gas composition analysis model can be determined first. At this point, the gas composition information corresponding to the equipment airflow information can be calculated based on the equipment airflow information and the relationship between airflow changes. Simultaneously, the equipment airflow information can be input into the gas temperature analysis model. The encoder in the gas temperature analysis model encodes the equipment airflow information to obtain an encoded vector. Then, the decoder in the gas temperature analysis model decodes the encoded vector, and the gas temperature information corresponding to the equipment airflow information can be obtained based on the decoding result.

[0083] Continuing the previous example, given the determined test airflow F for the waste incinerator and the optimization objective of minimizing the total heat generated by CO combustion and the heat generated by hot air in the exhaust gas, a gas temperature analysis model and a gas composition analysis model can be determined to calculate the total heat generated by the test airflow F while saving time and cost. Inputting the test airflow information into the gas temperature analysis model for prediction processing yields the exhaust gas temperature A under the test airflow F. Processing the test airflow information F through the gas composition analysis model yields the CO content H in the exhaust gas under the test airflow information F. Subsequently, the exhaust gas temperature A and CO content H can be combined to detect the test airflow information F, thereby optimizing the combustion of the waste incinerator.

[0084] In summary, by combining two types of models to detect the airflow information of the equipment, it is possible to ensure that testing after different airflow settings is completed before airflow adjustment, thereby saving more costs.

[0085] Step S208: If the gas composition information and the gas temperature information meet the combustion reference conditions, adjust the air volume of the industrial combustion equipment according to the equipment air volume information.

[0086] Specifically, after obtaining the gas temperature and composition information corresponding to the equipment airflow information, the following steps can be taken: Based on the gas temperature and composition information, it can be calculated whether the combustion effect of the industrial combustion equipment meets the combustion baseline conditions under the current equipment airflow information. If not, the equipment airflow information needs adjustment, and new equipment airflow information can be selected for the above processing operation. If it meets the requirements, the equipment airflow information allows the industrial combustion equipment to achieve a better combustion effect under the current state, and therefore the airflow of the industrial combustion equipment can be adjusted according to the equipment airflow information. In practical applications, the airflow adjustment of the industrial combustion equipment can be accomplished through the airflow control unit of the industrial combustion equipment. That is, the airflow control unit is adjusted according to the set airflow and exhaust airflow, so that the industrial combustion equipment can reduce the heat carried away by the exhaust gas under the current combustion state, thereby reducing energy efficiency and avoiding resource waste.

[0087] Furthermore, if the gas composition and temperature information do not meet the combustion baseline conditions, it indicates that the equipment airflow information cannot reduce heat waste in the industrial combustion equipment. Therefore, new equipment airflow information can be selected for testing. In this embodiment, the specific implementation method is as follows:

[0088] If the gas composition information and the gas temperature information do not meet the combustion benchmark conditions, variable air volume information is constructed based on the equipment air volume information; the variable air volume information is used as the equipment air volume information, and the steps of loading the gas composition analysis model and gas temperature analysis model associated with the industrial combustion equipment are executed; until the target air volume information corresponding to the target gas composition information and target gas temperature information that meet the combustion benchmark conditions is determined, the air volume of the industrial combustion equipment is adjusted according to the target air volume information.

[0089] Specifically, variable airflow information refers to airflow information obtained after adjusting the equipment airflow information. Based on this, if the gas composition and temperature information do not meet the combustion baseline conditions, it indicates that the current equipment airflow information cannot reduce energy consumption of the industrial combustion equipment or achieve the expected combustion effect. Therefore, variable airflow information can be constructed based on the equipment airflow information. This variable airflow information can then be used as the equipment airflow information, and step S204 is executed. Through continuous iterative calculations, until the target gas composition and temperature information that meet the combustion baseline conditions are determined, it indicates that the target airflow information can have a better combustion effect. Therefore, the airflow of the industrial combustion equipment can be adjusted according to the target airflow information.

[0090] In practical applications, when selecting airflow information for industrial combustion equipment under current conditions, a rolling optimization operation within the MPC algorithm can be used to select the airflow information in order to ensure that the exhaust gas from the industrial combustion equipment carries away less heat. By using the combustion baseline conditions as the CV (Control Variables) of MPC and the equipment airflow information as the MV (Manipulated Variables) of MPC, and substituting the gas temperature and gas composition predicted by the gas temperature analysis model and the gas composition analysis model into MPC, dynamic optimization can be achieved. Based on changes in combustion conditions, the exhaust gas airflow of the industrial combustion equipment is continuously updated to a more suitable level to achieve combustion optimization.

[0091] In summary, by iteratively updating the airflow information to suit industrial combustion equipment, we can ensure that the industrial combustion equipment can achieve more complete combustion at each stage of combustion, thereby reducing energy consumption.

[0092] Furthermore, when detecting whether the airflow information of the detection device meets the combustion baseline conditions based on gas composition and temperature information, this is actually achieved by calculating the total heat. In this embodiment, the specific implementation is as follows:

[0093] The gas combustion heat corresponding to the equipment airflow information is calculated based on the gas composition information, and the hot air heat corresponding to the equipment airflow information is calculated based on the gas temperature information; the heat consumption corresponding to the equipment airflow information is determined based on the gas combustion heat and the hot air heat, and the heat consumption is detected according to the combustion reference conditions; if the heat consumption is detected to meet the combustion reference conditions, the step of adjusting the airflow of the industrial combustion equipment according to the equipment airflow information is executed.

[0094] Specifically, the heat of gas combustion refers to the heat of carbon monoxide combustion in the exhaust gas calculated based on gas composition information. Correspondingly, the heat of hot air refers to the heat carried in the exhaust gas calculated based on other temperature information. Consequently, the heat consumed is the sum of the heat from gas combustion and the heat of hot air.

[0095] Based on this, in order to reduce energy consumption, the combustion baseline condition can be set to minimize the total heat in the exhaust gas. Therefore, the heat of gas combustion corresponding to the equipment airflow information can be calculated based on the gas composition information, and the heat of hot air corresponding to the equipment airflow information can be calculated based on the gas temperature information. Then, the heat of gas combustion and the heat of hot air are summed to obtain the heat consumption corresponding to the equipment airflow information. The heat consumption is then detected according to the combustion baseline condition. If the detected heat consumption meets the combustion baseline condition, the step of adjusting the airflow of the industrial combustion equipment according to the equipment airflow information can be executed.

[0096] In practical applications, calculating the heat of combustion of gas by combining gas composition information actually involves calculating the heat of combustion of CO in the exhaust gas of industrial combustion equipment. Similarly, calculating the heat of hot air by combining gas temperature information involves calculating the heat of hot air from the exhaust gas in industrial combustion equipment. Specifically, the heat of combustion of CO in the exhaust gas = exhaust gas volume * exhaust gas CO content * heat of combustion per unit of CO; the heat of hot air in the exhaust gas = exhaust gas volume * exhaust gas temperature * exhaust gas specific heat capacity * exhaust gas density. In practical applications, the heat of combustion per unit of CO, the specific heat capacity of the exhaust gas, and the exhaust gas density can be collected and calculated using appropriate equipment.

[0097] Following the previous example, after processing the air volume information F under test using the gas composition analysis model and the gas temperature analysis model, we obtain the exhaust gas temperature of the waste incinerator as A and the CO content in the exhaust gas as H under the conditions of the air volume information F. At this point, we can combine the air volume information F, the CO content in the exhaust gas as H, and the heat of combustion per unit of CO to calculate the heat of combustion of CO in the exhaust gas produced after fuel combustion in the waste incinerator under the conditions of the air volume F as R1. Simultaneously, combining the air volume information F, the exhaust gas temperature A, the specific heat capacity of the exhaust gas, and the exhaust gas temperature, we can calculate the heat of hot air in the exhaust gas produced after fuel combustion in the waste incinerator under the conditions of the air volume F as R2. Therefore, the total heat consumption is R = R1 + R2. After testing, it is determined that the total heat consumption R does not meet the optimization condition (minimizing the total heat of combustion of CO in the exhaust gas and the heat of hot air in the exhaust gas). Therefore, we can choose a new air volume information F to continue the above calculations. Finally, it was determined that under the condition of air volume Fm, the total heat consumption met the optimization conditions. Therefore, the inlet and outlet air volumes of the waste incinerator can be adjusted according to the air volume Fm.

[0098] In summary, by calculating heat to detect the airflow information of the equipment, it can be ensured that the airflow information of each piece of equipment can be calculated theoretically, thereby detecting whether it is suitable for industrial combustion equipment and achieving the goal of combustion optimization.

[0099] Furthermore, to save more energy, detection can be performed at set time intervals, and the airflow control unit can be adjusted after the detection is completed. In this embodiment, the specific implementation method is as follows:

[0100] The combustion optimization request corresponding to the industrial combustion equipment is triggered at a preset time interval, and the steps of determining combustion baseline conditions and equipment airflow information in response to the combustion optimization request triggered for the industrial combustion equipment are executed; wherein, the step of adjusting the airflow of the industrial combustion equipment according to the equipment airflow information includes: generating an airflow adjustment command based on the equipment airflow information, and adjusting the airflow control unit of the industrial combustion equipment based on the airflow adjustment command, for adjusting the airflow of the industrial combustion equipment.

[0101] Specifically, the time interval refers to the combustion optimization interval set for industrial combustion equipment, such as 10 minutes, 30 minutes, etc.; correspondingly, the air volume adjustment command refers to the command submitted to the air volume control unit to control the inlet and outlet air volume of the air volume control unit to achieve the purpose of combustion optimization.

[0102] Therefore, in order to save more energy, a combustion optimization request corresponding to the industrial combustion equipment can be triggered at preset time intervals, followed by the execution of steps S202 to S208. Furthermore, when adjusting the airflow, an airflow adjustment command can be generated based on the equipment's airflow information to adjust the airflow control unit of the industrial combustion equipment, thereby adjusting the airflow of the industrial combustion equipment to achieve combustion optimization.

[0103] The industrial combustion optimization method provided in this embodiment aims to improve combustion optimization efficiency, reduce carbon emissions, and achieve energy conservation. Upon triggering a combustion optimization request for industrial combustion equipment, it determines the corresponding combustion baseline conditions and equipment airflow information in response to the request. Subsequently, to improve the combustion optimization efficiency of the industrial combustion equipment, a gas composition analysis model based on the relationship between airflow and gas composition, and a gas temperature analysis model based on a time-series prediction algorithm, can be loaded. Then, the gas composition and temperature analysis models can be used to perform gas composition and temperature analysis on the equipment airflow information, thereby obtaining the gas composition and temperature information corresponding to the combustion gas of the industrial combustion equipment under the current equipment airflow information. This gas composition and temperature information reflects the combustion effect of the industrial combustion equipment under the current equipment airflow information. Therefore, by combining gas composition and temperature information, it can be determined whether the current combustion effect meets the combustion baseline conditions. If not, it indicates that the current equipment airflow information cannot enable the industrial combustion equipment to achieve a higher combustion rate or lower energy consumption. Therefore, new equipment airflow information can be selected for further testing until the conditions are met. Then, the airflow of the industrial combustion equipment can be adjusted according to the equipment airflow information that meets the conditions to improve the complete combustion of the combustibles and reduce the heat carried away by the equipment exhaust gas. This will enable the industrial combustion equipment to have better combustion performance under the current combustion conditions, thereby saving energy and reducing carbon emissions.

[0104] The following is in conjunction with the appendix Figure 3 Taking the application of the industrial combustion optimization method provided in this specification in a power generation scenario as an example, the industrial combustion optimization method will be further explained. Among other things, Figure 3 This specification illustrates a process flow diagram of an industrial combustion optimization method according to an embodiment, which specifically includes the following steps.

[0105] Step S302: If a change in the combustible material of the industrial combustion equipment is detected, a combustion optimization request is generated for the industrial combustion equipment.

[0106] Step S304: In response to the combustion optimization request, determine the energy consumption optimization target corresponding to the industrial combustion equipment, wherein the energy consumption optimization target is determined based on the heat of gas combustion and the heat of hot air.

[0107] Step S306: Use the energy consumption optimization target as the combustion baseline condition, and create test air volume information for the industrial combustion equipment according to the combustion optimization request, as the equipment air volume information.

[0108] In power generation scenarios, to save energy consumption, a combustion optimization request can be established for pulverized coal boilers. Based on this request, the optimization objective for the pulverized coal boiler is determined to be: minimizing the heat carried away by the exhaust gas. Specifically, this means minimizing the total heat generated by CO combustion and the heat generated by hot air in the exhaust gas. Subsequently, a test airflow information F can be created for the pulverized coal boiler, and adjustments can be made to this airflow information until the target airflow information is obtained, minimizing the total heat. This allows for the adjustment of the inlet and outlet airflow of the pulverized coal boiler, thereby reducing energy consumption.

[0109] Step S308: Load the gas composition analysis model and gas temperature analysis model associated with the industrial combustion equipment. The gas composition analysis model is constructed based on the relationship between air volume and gas composition, and the gas temperature analysis model is constructed based on a time-series prediction algorithm.

[0110] Step S310: Process the equipment airflow information using a gas composition analysis model to obtain the gas composition information corresponding to the equipment airflow information.

[0111] Step S312: Input the equipment airflow information into the gas temperature analysis model for prediction to obtain the gas temperature information corresponding to the equipment airflow information.

[0112] Specifically, the gas temperature analysis model and gas composition analysis model corresponding to the pulverized coal boiler can be determined. By inputting the air volume information to be tested into the gas temperature analysis model for prediction processing, the exhaust gas temperature of the pulverized coal boiler under the condition of the air volume information F can be obtained as A. After processing the air volume information F under the test using the gas composition analysis model, the CO content in the exhaust gas of the pulverized coal boiler under the condition of the air volume information F can be obtained as H.

[0113] Step S314: Calculate the gas combustion heat corresponding to the equipment air volume information based on the gas composition information, and calculate the hot air heat corresponding to the equipment air volume information based on the gas temperature information.

[0114] Step S316: Determine the heat consumption corresponding to the equipment air volume information based on the heat of gas combustion and the heat of hot air.

[0115] Step S318: Check whether the consumed heat meets the combustion reference conditions. If not, proceed to step S320; if yes, proceed to step S322.

[0116] Step S320: Construct variable air volume information based on equipment air volume information, use variable air volume information as equipment air volume information, and execute step S308.

[0117] Step S322: Adjust the air volume of the industrial combustion equipment according to the equipment air volume information.

[0118] Specifically, by combining the test airflow information F, the CO content in the exhaust gas H, and the unit CO combustion heat, the CO combustion heat in the exhaust gas produced by the pulverized coal boiler after fuel combustion under the test airflow F can be calculated as R1. Simultaneously, by combining the test airflow information F, the exhaust gas temperature A, the exhaust gas specific heat capacity, and the exhaust gas temperature, the hot air heat in the exhaust gas produced by the pulverized coal boiler after fuel combustion under the test airflow F can be calculated as R2. Thus, the total heat consumption is obtained as R = R1 + R2. After testing, it was determined that the total heat consumption R does not meet the optimization condition (minimizing the sum of the CO combustion heat and the hot air heat in the exhaust gas). Therefore, a new test airflow information F can be selected to continue the above calculations. Finally, it was determined that under the airflow condition Fm, the total heat consumption meets the optimization condition. Therefore, the inlet and outlet airflow of the pulverized coal boiler can be adjusted according to the airflow Fm.

[0119] In summary, to improve combustion optimization, reduce carbon emissions, and achieve energy conservation, upon triggering a combustion optimization request for industrial combustion equipment, the corresponding combustion baseline conditions and airflow information for the industrial combustion equipment can be determined in response to the request. Subsequently, to improve the combustion optimization efficiency of the industrial combustion equipment, a gas composition analysis model based on the relationship between airflow and gas composition, and a gas temperature analysis model based on a time-series prediction algorithm, can be loaded. Then, the gas composition and temperature analysis models can be used to process the airflow information, thereby obtaining the gas composition and temperature information of the combustion gas in the industrial combustion equipment under the current airflow information. This gas composition and temperature information reflects the combustion effect of the industrial combustion equipment under the current airflow information. Therefore, by combining gas composition and temperature information, it can be determined whether the current combustion effect meets the combustion baseline conditions. If not, it indicates that the current equipment airflow information cannot enable the industrial combustion equipment to achieve a higher combustion rate or lower energy consumption. Therefore, new equipment airflow information can be selected for further testing until the conditions are met. Then, the airflow of the industrial combustion equipment can be adjusted according to the equipment airflow information that meets the conditions to improve the complete combustion of the combustibles and reduce the heat carried away by the equipment exhaust gas. This will enable the industrial combustion equipment to have better combustion performance under the current combustion conditions, thereby saving energy and reducing carbon emissions.

[0120] Corresponding to the above method embodiments, this specification also provides another embodiment for industrial combustion optimization. Figure 4 A flowchart illustrating another industrial combustion optimization method provided in one embodiment of this specification is shown. Figure 4 As shown, this method is applied to cloud-side devices, including:

[0121] Step S402: Receive a combustion optimization request submitted by the end-side device of the industrial combustion equipment, and determine the combustion baseline conditions and equipment airflow information of the industrial combustion equipment based on the combustion optimization request;

[0122] Step S404: Load the gas composition analysis model and gas temperature analysis model associated with the industrial combustion equipment, wherein the gas composition analysis model is constructed based on the relationship between air volume and gas composition, and the gas temperature analysis model is constructed based on a time-series prediction algorithm;

[0123] Step S406: Process the equipment airflow information using the gas composition analysis model and the gas temperature analysis model to obtain the gas composition information and gas temperature information corresponding to the equipment airflow information;

[0124] Step S408: If the gas composition information and the gas temperature information meet the combustion reference conditions, the equipment airflow information is sent to the end-side device to adjust the airflow of the industrial combustion equipment.

[0125] In this embodiment, the cloud-side device specifically refers to the device corresponding to the service platform that provides industrial combustion optimization services. This platform provides industrial combustion optimization services to different end-side devices. After an end-side device submits a combustion optimization request for its corresponding industrial combustion equipment, it can respond to the request by executing the industrial combustion optimization method, thereby obtaining the optimal equipment airflow information corresponding to the industrial combustion equipment in the current state. After sending it to the end-side device, the end-side device can adjust the airflow of the industrial combustion equipment, thereby improving combustion efficiency and reducing energy consumption.

[0126] It should be noted that the implementation of the other industrial combustion optimization method provided in this embodiment can refer to the same or corresponding descriptions in the above embodiments, and will not be elaborated further in this embodiment.

[0127] Corresponding to the above method embodiments, this specification also provides embodiments of industrial combustion optimization devices. Figure 5 A schematic diagram of an industrial combustion optimization device according to one embodiment of this specification is shown. Figure 5 As shown, the device includes:

[0128] The determination module 502 is configured to determine the combustion baseline conditions of the industrial combustion equipment and the equipment airflow information of the industrial combustion equipment in response to a combustion optimization request triggered for the industrial combustion equipment;

[0129] The loading module 504 is configured to load the gas composition analysis model and the gas temperature analysis model associated with the industrial combustion equipment, wherein the gas composition analysis model is constructed based on the relationship between air volume and gas composition, and the gas temperature analysis model is constructed based on a time-series prediction algorithm.

[0130] The processing module 506 is configured to process the equipment airflow information through the gas composition analysis model and the gas temperature analysis model to obtain the gas composition information and gas temperature information corresponding to the equipment airflow information.

[0131] The adjustment module 508 is configured to adjust the air volume of the industrial combustion equipment according to the equipment air volume information when the gas composition information and the gas temperature information meet the combustion reference conditions.

[0132] In an optional embodiment, the determining module 502 is further configured to:

[0133] When a change in the combustor of an industrial combustion device is detected, a combustion optimization request is constructed for the industrial combustion device; in response to the combustion optimization request, an energy consumption optimization target corresponding to the industrial combustion device is determined, wherein the energy consumption optimization target is determined based on the target gas combustion heat and gas hot air heat; the energy consumption optimization target is used as the combustion baseline condition, and test air volume information is created for the industrial combustion device according to the combustion optimization request, which is used as the device air volume information.

[0134] In an optional embodiment, the processing module 506 is further configured to:

[0135] The airflow change relationship recorded in the gas composition analysis model is determined. Based on the equipment airflow information and the airflow change relationship, the gas composition information corresponding to the equipment airflow information is calculated, wherein the airflow change relationship records the relationship between airflow and gas composition. The equipment airflow information is input into the gas temperature analysis model. The equipment airflow information is encoded by the encoder in the gas temperature analysis model, and the encoding result is decoded by the decoder in the gas temperature analysis model to obtain the gas temperature information corresponding to the equipment airflow information.

[0136] In an optional embodiment, the adjustment module 508 is further configured to:

[0137] The gas combustion heat corresponding to the equipment airflow information is calculated based on the gas composition information, and the hot air heat corresponding to the equipment airflow information is calculated based on the gas temperature information; the heat consumption corresponding to the equipment airflow information is determined based on the gas combustion heat and the hot air heat, and the heat consumption is detected according to the combustion reference conditions; if the heat consumption is detected to meet the combustion reference conditions, the step of adjusting the airflow of the industrial combustion equipment according to the equipment airflow information is executed.

[0138] In an optional embodiment, the apparatus further includes:

[0139] The iterative module is configured to, when the gas composition information and the gas temperature information do not meet the combustion benchmark conditions, construct variable air volume information based on the equipment air volume information; use the variable air volume information as the equipment air volume information, and execute the steps of loading the gas composition analysis model and gas temperature analysis model associated with the industrial combustion equipment; until a target air volume information corresponding to the target gas composition information and target gas temperature information that meet the combustion benchmark conditions is determined, adjust the air volume of the industrial combustion equipment according to the target air volume information.

[0140] In an optional embodiment, the apparatus further includes:

[0141] The first model construction module is configured to use a gas analyzer to determine the content of a first gas and a second gas in the combustion exhaust gas of the industrial combustion equipment, and to establish a gas content relationship between the first gas content and the second gas content; when the first gas content in the combustion exhaust gas changes, to determine the changed second gas content based on the changed first gas content and the gas content relationship, and to determine the first air volume information before the change and the changed second air volume information; and to construct the gas composition analysis model based on the first air volume information, the second air volume information, the first gas content and the second gas content before the change, and the changed first gas content and the second gas content.

[0142] In an optional embodiment, the apparatus further includes:

[0143] The second model construction module is configured to select target sample pairs from the sample set corresponding to the industrial combustion equipment, wherein the target sample pair consists of sample air volume information and sample gas temperature information; input the sample air volume information into the initial gas temperature analysis model for processing to obtain the predicted gas temperature information corresponding to the sample air volume information; calculate the loss value based on the sample gas temperature information and the predicted gas temperature information, and adjust the parameters of the initial gas temperature analysis model based on the loss value until the gas temperature analysis model that meets the training stopping condition is obtained.

[0144] In an optional embodiment, the apparatus further includes:

[0145] The triggering module is configured to trigger a combustion optimization request corresponding to the industrial combustion equipment at a preset time interval, and to perform the steps of determining combustion baseline conditions and equipment airflow information in response to the combustion optimization request triggered for the industrial combustion equipment.

[0146] The adjustment module 508 is further configured to generate an airflow adjustment command based on the equipment airflow information, and adjust the airflow control unit of the industrial combustion equipment based on the airflow adjustment command, so as to adjust the airflow of the industrial combustion equipment.

[0147] The industrial combustion optimization device provided in this embodiment, in order to improve combustion optimization effect, reduce carbon emissions, and achieve energy saving, can determine the corresponding combustion baseline conditions and equipment airflow information of the industrial combustion equipment in response to the combustion optimization request triggered. Subsequently, to improve the combustion optimization efficiency of the industrial combustion equipment, a gas composition analysis model based on the relationship between airflow and gas composition, and a gas temperature analysis model based on a time-series prediction algorithm can be loaded. Then, the gas composition analysis model and the gas temperature analysis model can be used to perform gas composition analysis and gas temperature analysis on the equipment airflow information, thereby obtaining the gas composition information and gas temperature information corresponding to the combustion gas of the industrial combustion equipment under the current equipment airflow information. The gas composition information and gas temperature information can represent the combustion effect of the industrial combustion equipment under the current equipment airflow information. Therefore, by combining gas composition and temperature information, it can be determined whether the current combustion effect meets the combustion baseline conditions. If not, it indicates that the current equipment airflow information cannot enable the industrial combustion equipment to achieve a higher combustion rate or lower energy consumption. Therefore, new equipment airflow information can be selected for further testing until the conditions are met. Then, the airflow of the industrial combustion equipment can be adjusted according to the equipment airflow information that meets the conditions to improve the complete combustion of the combustibles and reduce the heat carried away by the equipment exhaust gas. This will enable the industrial combustion equipment to have better combustion performance under the current combustion conditions, thereby saving energy and reducing carbon emissions.

[0148] The above is a schematic scheme of an industrial combustion optimization device according to this embodiment. It should be noted that the technical solution of this industrial combustion optimization device and the technical solution of the above-described industrial combustion optimization method belong to the same concept. For details not described in detail in the technical solution of the industrial combustion optimization device, please refer to the description of the technical solution of the above-described industrial combustion optimization method.

[0149] Corresponding to the above method embodiments, this specification also provides another embodiment of an industrial combustion optimization device. Figure 6 A schematic diagram of another industrial combustion optimization device provided in one embodiment of this specification is shown. Figure 6 As shown, this device is applied to cloud-side equipment and includes:

[0150] The request receiving module 602 is configured to receive a combustion optimization request submitted by the end-side device of the industrial combustion equipment, and determine the combustion reference conditions and equipment air volume information of the industrial combustion equipment based on the combustion optimization request.

[0151] The loading model module 604 is configured to load the gas composition analysis model and the gas temperature analysis model associated with the industrial combustion equipment, wherein the gas composition analysis model is constructed based on the relationship between air volume and gas composition, and the gas temperature analysis model is constructed based on a time series prediction algorithm;

[0152] The information processing module 606 is configured to process the equipment airflow information through the gas composition analysis model and the gas temperature analysis model to obtain the gas composition information and gas temperature information corresponding to the equipment airflow information;

[0153] The information transmission module 608 is configured to send the equipment airflow information to the end-side device when the gas composition information and the gas temperature information meet the combustion reference conditions, so as to adjust the airflow of the industrial combustion equipment.

[0154] The above is an illustrative scheme of another industrial combustion optimization device according to this embodiment. It should be noted that the technical solution of this industrial combustion optimization device and the technical solution of the above-described industrial combustion optimization method belong to the same concept. For details not described in detail in the technical solution of the industrial combustion optimization device, please refer to the description of the technical solution of the above-described industrial combustion optimization method.

[0155] Figure 7 A structural block diagram of a computing device 700 according to one embodiment of this specification is shown. The components of the computing device 700 include, but are not limited to, a memory 710 and a processor 720. The processor 720 is connected to the memory 710 via a bus 730, and a database 750 is used to store data.

[0156] The computing device 700 also includes an access device 740, which enables the computing device 700 to communicate via one or more networks 760. Examples of these networks include Public Switched Telephone Network (PSTN), Local Area Network (LAN), Wide Area Network (WAN), Personal Area Network (PAN), or combinations of communication networks such as the Internet. The access device 740 may include one or more of any type of wired or wireless network interface (e.g., a network interface controller (NIC)), such as an IEEE 802.11 Wireless Local Area Network (WLAN) wireless interface, a Wi-MAX (Worldwide Interoperability for Microwave Access) interface, an Ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a Bluetooth interface, or a Near Field Communication (NFC) interface.

[0157] In one embodiment of this specification, the above-described components of the computing device 700 and Figure 7 Other components, not shown, can also be connected to each other, for example, via a bus. It should be understood that... Figure 7 The block diagram of the computing device shown is for illustrative purposes only and is not intended to limit the scope of this specification. Those skilled in the art can add or replace other components as needed.

[0158] The computing device 700 can be any type of stationary or mobile computing device, including mobile computers or mobile computing devices (e.g., tablet computers, personal digital assistants, laptop computers, notebook computers, netbooks, etc.), mobile phones (e.g., smartphones), wearable computing devices (e.g., smartwatches, smart glasses, etc.) or other types of mobile devices, or stationary computing devices such as desktop computers or personal computers (PCs). The computing device 700 can also be a mobile or stationary server.

[0159] The processor 720 is used to execute the following computer-executable instructions, which, when executed by the processor, implement the steps of the above-described industrial combustion optimization method.

[0160] The above is a schematic representation of a computing device according to this embodiment. It should be noted that the technical solution of this computing device and the technical solution of the aforementioned industrial combustion optimization method belong to the same concept. Details not described in detail in the technical solution of the computing device can be found in the description of the technical solution of the aforementioned industrial combustion optimization method.

[0161] An embodiment of this specification also provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the above-described industrial combustion optimization method.

[0162] The above is an illustrative embodiment of a computer-readable storage medium. It should be noted that the technical solution of this storage medium belongs to the same concept as the technical solution of the aforementioned industrial combustion optimization method. Details not described in detail in the technical solution of the storage medium can be found in the description of the technical solution of the aforementioned industrial combustion optimization method.

[0163] An embodiment of this specification also provides a computer program, wherein when the computer program is executed in a computer, it causes the computer to perform the steps of the above-described industrial combustion optimization method.

[0164] The above is an illustrative example of a computer program according to this embodiment. It should be noted that the technical solution of this computer program and the technical solution of the aforementioned industrial combustion optimization method belong to the same concept. Details not described in detail in the computer program's technical solution can be found in the description of the technical solution of the aforementioned industrial combustion optimization method.

[0165] An embodiment of this specification also provides a computer program product, including a computer program or instructions that, when executed by a processor, implement the steps of the above-described industrial combustion optimization method.

[0166] The above is an illustrative scheme of a computer program product according to this embodiment. It should be noted that the technical solution of this computer program product and the technical solution of the above-described industrial combustion optimization method belong to the same concept. For details not described in detail in the technical solution of the computer program product, please refer to the description of the technical solution of the above-described industrial combustion optimization method.

[0167] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0168] The computer instructions include computer program code, which may be in the form of source code, object code, executable file, or certain intermediate forms. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium may be appropriately added or removed according to the requirements of patent practice. For example, in some regions, according to patent practice, computer-readable media may not include electrical carrier signals and telecommunication signals.

[0169] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the embodiments in this specification are not limited to the described order of actions, because according to the embodiments in this specification, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in this specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the embodiments in this specification.

[0170] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0171] The preferred embodiments disclosed above are merely illustrative of this specification. The optional embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the embodiments described herein. These embodiments are selected and specifically described in this specification to better explain the principles and practical applications of the embodiments, thereby enabling those skilled in the art to better understand and utilize this specification. This specification is limited only by the claims and their full scope and equivalents.

Claims

1. An industrial combustion optimization method, comprising: In response to a combustion optimization request triggered by an industrial combustion device, the combustion baseline conditions and the device airflow information of the industrial combustion device are determined, wherein the combustion baseline conditions are indicators that measure the heat in the exhaust gas. Load the gas composition analysis model and gas temperature analysis model associated with the industrial combustion equipment, wherein the gas composition analysis model is constructed based on the relationship between air volume and gas composition, the gas temperature analysis model is constructed based on a time-series prediction algorithm, and the gas temperature analysis model is constructed based on the relationship between air volume and exhaust gas temperature, and the gas composition includes carbon monoxide content and / or oxygen content; The gas composition analysis model and the gas temperature analysis model are used to process the air volume information of the equipment to obtain the gas composition information and exhaust gas temperature information corresponding to the air volume information of the equipment. Based on the gas combustion heat corresponding to the gas composition information and the hot air heat corresponding to the exhaust gas temperature information, the heat consumption corresponding to the equipment air volume information is determined. When the heat consumption meets the combustion reference conditions, the air volume of the industrial combustion equipment is adjusted according to the equipment air volume information.

2. The method according to claim 1, wherein determining the combustion baseline conditions of the industrial combustion equipment and the equipment airflow information of the industrial combustion equipment in response to a combustion optimization request triggered for the industrial combustion equipment includes: If a change in the combustible material of an industrial combustion device is detected, a combustion optimization request is generated for the industrial combustion device. In response to the combustion optimization request, an energy consumption optimization target corresponding to the industrial combustion equipment is determined, wherein the energy consumption optimization target is determined based on the target gas combustion heat and gas hot air heat. The energy consumption optimization target is used as the combustion baseline condition, and the air volume information to be tested is created for the industrial combustion equipment according to the combustion optimization request, which is used as the equipment air volume information.

3. The method according to claim 1, wherein processing the equipment airflow information using the gas composition analysis model and the gas temperature analysis model to obtain the gas composition information and exhaust gas temperature information corresponding to the equipment airflow information includes: The airflow change relationship recorded in the gas composition analysis model is determined, and the gas composition information corresponding to the equipment airflow information is calculated based on the equipment airflow information and the airflow change relationship, wherein the airflow change relationship records the relationship between airflow and gas composition; The airflow information of the equipment is input into the gas temperature analysis model. The airflow information of the equipment is encoded by the encoder in the gas temperature analysis model, and the encoding result is decoded by the decoder in the gas temperature analysis model to obtain the exhaust gas temperature information corresponding to the airflow information of the equipment.

4. The method according to claim 1, wherein determining the heat consumption corresponding to the equipment airflow information based on the gas combustion heat corresponding to the gas composition information and the hot air heat corresponding to the exhaust gas temperature information, and adjusting the airflow of the industrial combustion equipment according to the equipment airflow information when the heat consumption meets the combustion reference conditions, comprises: The gas combustion heat corresponding to the equipment air volume information is calculated based on the gas composition information, and the hot air heat corresponding to the equipment air volume information is calculated based on the exhaust gas temperature information. The heat consumption corresponding to the air volume information of the equipment is determined based on the heat of gas combustion and the heat of hot air, and the heat consumption is detected according to the combustion reference conditions; If the heat consumption is detected to meet the combustion reference conditions, the step of adjusting the air volume of the industrial combustion equipment according to the equipment air volume information is performed.

5. The method according to claim 1, after the step of processing the equipment airflow information through the gas composition analysis model and the gas temperature analysis model to obtain the gas composition information and exhaust gas temperature information corresponding to the equipment airflow information is performed, it further includes: If the heat consumption does not meet the combustion reference conditions, variable air volume information is constructed based on the equipment air volume information; The variable air volume information is used as the equipment air volume information, and the steps of loading the gas composition analysis model and gas temperature analysis model associated with the industrial combustion equipment are executed. Once the target gas composition information and target exhaust gas temperature information that meet the combustion reference conditions are determined, the air volume of the industrial combustion equipment is adjusted according to the target air volume information.

6. The method according to any one of claims 1-5, wherein before the step of loading the gas composition analysis model and gas temperature analysis model associated with the industrial combustion equipment is performed, it further comprises: The content of a first gas and a second gas in the combustion exhaust gas of the industrial combustion equipment is determined using a gas analyzer, and the gas content relationship between the first gas content and the second gas content is established. When the content of the first gas in the combustion exhaust gas changes, the content of the second gas after the change is determined based on the content of the first gas after the change and the relationship between the gas contents, and the information of the first air volume before the change and the information of the second air volume after the change are determined. Based on the first air volume information, the second air volume information, the first gas content and the second gas content before the change, and the first gas content and the second gas content after the change, the gas composition analysis model is constructed.

7. The method according to any one of claims 1-5, wherein before the step of loading the gas composition analysis model and gas temperature analysis model associated with the industrial combustion equipment is performed, it further comprises: Select a target sample pair from the sample set corresponding to the industrial combustion equipment, wherein the target sample pair consists of sample air volume information and sample gas temperature information; The sample air volume information is input into the initial gas temperature analysis model for processing to obtain the predicted gas temperature information corresponding to the sample air volume information. The loss value is calculated based on the sample gas temperature information and the predicted gas temperature information, and the parameters of the initial gas temperature analysis model are adjusted based on the loss value until the gas temperature analysis model that meets the training stopping condition is obtained.

8. The method according to any one of claims 1-5, wherein before the step of determining the combustion baseline conditions of the industrial combustion equipment and the equipment airflow information of the industrial combustion equipment in response to a combustion optimization request triggered for the industrial combustion equipment is executed, it further comprises: The combustion optimization request corresponding to the industrial combustion equipment is triggered at a preset time interval, and the steps of determining the combustion reference conditions and equipment air volume information of the industrial combustion equipment in response to the combustion optimization request triggered for the industrial combustion equipment are executed. The step of adjusting the airflow of the industrial combustion equipment according to the equipment airflow information includes: An airflow adjustment command is generated based on the airflow information of the equipment, and the airflow control unit of the industrial combustion equipment is adjusted based on the airflow adjustment command to adjust the airflow of the industrial combustion equipment.

9. An industrial combustion optimization method, applied to cloud-side equipment, comprising: The system receives combustion optimization requests submitted by end-side devices of industrial combustion equipment, and determines the combustion baseline conditions and equipment airflow information of industrial combustion equipment based on the combustion optimization requests. The combustion baseline conditions are indicators that measure the heat in the exhaust gas. Load the gas composition analysis model and gas temperature analysis model associated with the industrial combustion equipment, wherein the gas composition analysis model is constructed based on the relationship between air volume and gas composition, the gas temperature analysis model is constructed based on a time-series prediction algorithm, and the gas temperature analysis model is constructed based on the relationship between air volume and exhaust gas temperature, and the gas composition includes carbon monoxide content and / or oxygen content; The gas composition analysis model and the gas temperature analysis model are used to process the air volume information of the equipment to obtain the gas composition information and exhaust gas temperature information corresponding to the air volume information of the equipment. Based on the gas combustion heat corresponding to the gas composition information and the hot air heat corresponding to the exhaust gas temperature information, the heat consumption corresponding to the equipment air volume information is determined. When the heat consumption meets the combustion reference conditions, the equipment air volume information is sent to the end-side device for adjusting the air volume of the industrial combustion equipment.

10. An industrial combustion optimization device, comprising: The determination module is configured to determine the combustion baseline conditions and equipment airflow information of the industrial combustion equipment in response to a combustion optimization request triggered for the industrial combustion equipment, wherein the combustion baseline conditions are indicators that measure the heat in the exhaust gas. The loading module is configured to load the gas composition analysis model and gas temperature analysis model associated with the industrial combustion equipment, wherein the gas composition analysis model is constructed based on the relationship between air volume and gas composition, the gas temperature analysis model is constructed based on a time-series prediction algorithm, and the gas temperature analysis model is constructed based on the relationship between air volume and exhaust gas temperature, and the gas composition includes carbon monoxide content and / or oxygen content; The processing module is configured to process the equipment airflow information through the gas composition analysis model and the gas temperature analysis model to obtain the gas composition information and exhaust gas temperature information corresponding to the equipment airflow information; The adjustment module is configured to determine the heat consumption corresponding to the equipment airflow information based on the gas combustion heat corresponding to the gas composition information and the hot air heat corresponding to the exhaust gas temperature information, and adjust the airflow of the industrial combustion equipment according to the equipment airflow information when the heat consumption meets the combustion reference conditions.

11. An industrial combustion optimization device, applied to cloud-side equipment, comprising: The request receiving module is configured to receive combustion optimization requests submitted by the end-side devices of the industrial combustion equipment, and determine the combustion baseline conditions and equipment air volume information of the industrial combustion equipment based on the combustion optimization requests, wherein the combustion baseline conditions are indicators that measure the heat in the exhaust gas. The loading model module is configured to load the gas composition analysis model and gas temperature analysis model associated with the industrial combustion equipment, wherein the gas composition analysis model is constructed based on the relationship between air volume and gas composition, the gas temperature analysis model is constructed based on a time-series prediction algorithm, and the gas temperature analysis model is constructed based on the relationship between air volume and exhaust gas temperature, and the gas composition includes carbon monoxide content and / or oxygen content; The information processing module is configured to process the equipment airflow information through the gas composition analysis model and the gas temperature analysis model to obtain the gas composition information and exhaust gas temperature information corresponding to the equipment airflow information; The information sending module is configured to determine the heat consumption corresponding to the equipment airflow information based on the gas combustion heat corresponding to the gas composition information and the hot air heat corresponding to the exhaust gas temperature information, and to send the equipment airflow information to the end-side device when the heat consumption meets the combustion reference conditions, so as to adjust the airflow of the industrial combustion equipment.

12. A computing device, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions, which, when executed by the processor, implement the steps of the method according to any one of claims 1 to 9.

13. A computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the method according to any one of claims 1 to 9.

14. A computer program product comprising a computer program or instructions which, when executed by a processor, implement the steps of the method according to any one of claims 1 to 9.

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