Low-concentration gas combustion control method and device, electronic equipment and storage medium

Abstract

The invention discloses a low-concentration gas combustion control method and device, electronic equipment and a storage medium, and the control method comprises the steps: collecting first data of a low-concentration gas combustion process, constructing a matrix, and carrying out matrix operation according to a preset program to obtain first target data, mapping each entity parameter of the equipment module and each index data information contained in the first target data to an information space so as to construct a digital twin model, and collecting second data in the low-concentration gas combustion process under the condition that the first target data meets a preset threshold value, and analyzing the second data based on the digital twin model to obtain simulation data information. According to the method, the digital twinborn body model is established by collecting data from the generator set equipment module, the digital twinborn body model can analyze the collected real-time data and simulate the combustion process with high fidelity, and different working conditions and combustion conditions are simulated in a virtual environment so as to predict performance and safety.

Description

Technical Field

[0001] The present application relates to the technical field of gas combustion, and in particular to a low-concentration gas combustion control method, device, electronic equipment and storage medium. Background Art

[0002] As one of the mainstream power generation methods, gas power generation has extremely outstanding power generation advantages. It can not only reduce the occurrence of coal mine gas accidents, but also significantly improve the production conditions of coal mines, and can increase the supply of clean energy from a certain perspective, thereby playing a role in protecting the environment. Gas generators are generally suitable for high-concentration gas. Once the gas concentration cannot maintain a certain concentration, the efficiency and safety of power generation will be seriously reduced. With the development of technology, current gas generators have been able to directly utilize low-concentration gas at 3%-9%, thereby improving the utilization rate of gas and reducing the waste and pollution of low-concentration gas; however, there are still certain risks in the direct combustion process of low-concentration gas. In order to improve the safety of low-concentration gas power generation, it is necessary to monitor the operation process of low-concentration gas direct combustion units in real time.

[0003] In the related technology, the monitoring of gas combustion units adopts a combination of video monitoring system and PLC control system; the video monitoring system mainly performs visual monitoring and cannot provide information related to real-time data such as gas concentration, temperature and pressure, and it is difficult to adjust the combustion parameters in real time to cope with changing conditions; the PLC control system is used for automatic control, lacks complex logic and intelligent response, and is difficult to adapt to the environmental conditions of low-concentration gas. It is impossible to simulate different operating conditions and combustion conditions in a virtual environment to predict performance and safety, and it does not have data analysis and optimization functions, which makes it difficult for low-concentration gas direct combustion units to optimize combustion parameters to improve energy utilization and reduce emissions. Summary of the invention

[0004] The embodiments of the present application provide a low-concentration gas combustion control method, device, electronic device and storage medium, which can use digital twin technology to create a digital model of the actual system, allowing real-time simulation and optimization of the combustion process.

[0005] In the first aspect, an embodiment of the present application provides a low-concentration gas combustion control method, the method comprising: collecting first data of low-concentration gas burning in an equipment module of a generator set, the first data being used to characterize index information such as temperature, pressure, concentration, and liquid level during the combustion of the low-concentration gas; constructing a matrix based on the first data and performing matrix operations according to a preset procedure to clean and standardize the first data to obtain first target data; mapping various physical parameters of the equipment module and various index data information contained in the first target data to an information space to construct a digital twin model, the digital twin model being able to characterize the operating status information of the equipment module; when the first target data meets a preset threshold, collecting second data during the combustion of the low-concentration gas; analyzing the second data based on the digital twin model to obtain simulation data information corresponding to the current combustion process of the equipment module.

[0006] According to the first aspect of the embodiment of the present application, after constructing a matrix based on the first data and performing matrix operations according to a preset procedure to clean and standardize the first data to obtain the first target data, the method also includes: dividing the first target data into multiple data groups containing the same number of elements to obtain input samples, and dividing the input samples into a training set, a validation set and a test set; using the mean square error of the training set as the loss function, using a stochastic gradient descent optimizer to train the initial model to obtain a first sequence model and hyperparameter information corresponding to the first sequence model; verifying the first sequence model based on the validation set, selecting the hyperparameter information to determine the second sequence model; verifying and adjusting the second sequence model based on the test set to determine a time series model, which is used to diagnose real-time data during low-concentration gas combustion to determine whether the low-concentration gas combustion is in normal operating condition.

[0007] According to the first aspect of the embodiment of the present application, the aforementioned initial model is an LSTM model, and the LSTM model includes a forget gate, an input gate, an output gate and a state unit.

[0008] According to the first aspect of the embodiment of the present application, various physical parameters of the equipment module and various indicator data information contained in the first target data are mapped to the information space to construct a digital twin model, including: mapping the physical size of the equipment module to the information space and performing gridding processing to obtain multiple control bodies; based on the conservation of mass, momentum and energy in the gas combustion process, physical modeling and chemical modeling of multiple control bodies are performed according to the indicator information in the first target data to obtain an initial twin model; a proportional integral differential controller is selected, and a first-order lag system is used to model sensors and actuators to describe the dynamic behavior of sensors and actuators, and a target twin model is obtained for control system integration to maintain the stability of the combustion process; the initial twin model and the target twin model are digitally combined to obtain a digital twin model.

[0009] According to the first aspect of an embodiment of the present application, the second data is analyzed based on a digital twin model to obtain simulation data information corresponding to the current combustion process of the equipment module, including: based on the digital twin model, using computational fluid dynamics software to analyze the second data to obtain a continuous conservation equation; adding initial conditions, convection boundary conditions and thermal boundary conditions to the continuous conservation equation, wherein the initial condition is a steady-state solution or an empirical estimate, and the thermal boundary condition is a fixed temperature or heat flow; using a finite volume method to discretize the continuous equation into an algebraic equation, and solving the discretized algebraic equation based on a semi-implicit method of the pressure-coupled equation group to obtain simulation data information.

[0010] According to the first aspect of the embodiment of the present application, after analyzing the second data based on the digital twin model to obtain simulation data information corresponding to the current combustion process of the equipment module, the method also includes: extracting second target data related to various physical parameters such as temperature distribution, pressure distribution, velocity field and gas concentration from the simulation data information; based on the visualization software and the second target data, creating a visual mapping for each physical parameter to obtain first visualization information; creating a three-dimensional temperature field based on the first visualization information, and adding interactive functions such as timeline control, view rotation and view zooming to the three-dimensional temperature field to obtain a visualization module.

[0011] According to the first aspect of the embodiment of the present application, after creating a three-dimensional temperature field based on the first visualization information and adding interactive functions such as timeline control, view rotation and view zooming to the three-dimensional temperature field to obtain a visualization module, the method also includes: collecting low-concentration gas combustion information at different times, and determining the simulated visual information at the corresponding time based on the visualization module; comparing the low-concentration gas combustion information with the simulated visual information to obtain a display deviation; based on the display deviation, adjusting the view parameters in the visualization module, the view parameters including at least one of a color scheme, transparency and graphic layout.

[0012] In the second aspect, an embodiment of the present application provides a low-concentration gas combustion control device, which includes an acquisition module, a cleaning module, a mapping module and an analysis module. The acquisition module is used to collect first data on the combustion of low-concentration gas in the equipment module of the generator set; the cleaning module is used to construct a matrix based on the first data and perform matrix operations according to a preset procedure to clean and standardize the first data to obtain first target data; the mapping module is used to map various entity parameters of the equipment module and various indicator data information contained in the first target data to the information space to construct a digital twin model; the aforementioned acquisition module is also used to collect second data in the low-concentration gas combustion process when the first target data meets a preset threshold; the analysis module is used to analyze the second data based on the digital twin model to obtain simulation data information corresponding to the current combustion process of the equipment module.

[0013] In a third aspect, an embodiment of the present application provides an electronic device, which includes a processor, a memory, and a program stored in the memory and executable on the processor, and when the program is executed by the processor, the low-concentration gas combustion control method in the first aspect is implemented.

[0014] In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored, and when the program or instruction is executed by a processor, the steps of the low-concentration gas combustion control method in the first aspect are implemented.

[0015] The embodiments of the present application provide a low-concentration gas combustion control method, device, electronic device and storage medium. The method establishes a digital twin model and a time series model by collecting data from the equipment module of the generator set; the digital twin model can analyze the collected real-time data and simulate the combustion process with high fidelity, simulate different operating conditions and combustion conditions in a virtual environment to predict performance and safety; the time series model can remotely maintain and diagnose faults of the equipment module based on real-time data, and then improve energy utilization and reduce emissions by optimizing combustion parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The features, advantages and technical effects of exemplary embodiments of the present application will be described below with reference to the accompanying drawings.

[0017] Figure 1 It is a flow chart of a low-concentration gas combustion control method provided in an embodiment of the present application;

[0018] Figure 2 It is a schematic diagram of the process of building a digital twin model provided in an embodiment of the present application;

[0019] Figure 3It is a schematic diagram of the process of building a time series model provided in an embodiment of the present application;

[0020] Figure 4 It is a schematic diagram of the process of establishing a visualization module provided in an embodiment of the present application;

[0021] Figure 5 It is a schematic diagram of the process of data collection and transmission provided in the embodiment of the present application;

[0022] Figure 6 It is a schematic diagram of a process of analyzing the data provided in the embodiment of the present application through a digital twin model and a time series model;

[0023] Figure 7 It is a structural schematic diagram of a low-concentration gas combustion control device provided in an embodiment of the present application;

[0024] Figure 8 It is a structural schematic diagram of another low-concentration gas combustion control device provided in an embodiment of the present application;

[0025] Fig. 9 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0026] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is only to provide a better understanding of the present application by illustrating the examples of the present application.

[0027] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "include..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0028] This application is based on the inventor's discovery and understanding of the following facts and problems:

[0029] With the breakthrough of modern industrial technology, in view of the current situation of low-concentration gas emission, waste and pollution, the relevant technology can use the low-concentration gas safe and stable combustion technology to establish a low-concentration gas safe ignition and stable combustion experimental system. This system can directly burn the low-concentration gas with a concentration of 3%-9% that cannot be directly used by gas generators. This system effectively expands the direct utilization scope of extracted gas, can greatly improve the utilization rate of extracted gas, and provides effective technical support for achieving the goal of "zero emission of extracted gas".

[0030] At present, traditional video surveillance and automatic control systems can provide real-time visual monitoring and highly automated operation for low-concentration gas direct combustion systems. However, the combination of traditional video surveillance systems and PLC control systems is mainly used for visual monitoring and cannot provide information related to real-time data such as gas concentration, temperature and pressure. This makes it difficult to adjust combustion parameters in real time to cope with changing environmental conditions; in addition, PLC control systems are usually used for automatic control, and PLC control systems may lack complex logic and intelligent reactions, making it difficult to adapt to environmental conditions with low concentrations of gas. In summary, current video surveillance and automatic control systems usually do not have simulation and digital twin functions, and cannot simulate different operating conditions and combustion conditions in a virtual environment to predict performance and safety; and lack fault diagnosis, remote maintenance and data analysis optimization functions, making system maintenance and troubleshooting more complicated and time-consuming, and difficult to optimize combustion parameters to improve energy utilization and reduce emissions.

[0031] In order to solve the problems of the prior art, the embodiments of the present application provide a low-concentration gas combustion control method, device, electronic device and storage medium.

[0032] The following first introduces a low-concentration gas combustion control method provided in an embodiment of the present application.

[0033] The present application provides a flow chart of a low-concentration gas combustion control method, as shown in FIG. Figure 1 As shown, the low-concentration gas combustion control method may include the following steps S110-S150.

[0034] S110, collecting first data of combustion of low-concentration gas in the generator set equipment module, the first data being used to characterize index information such as temperature, pressure, concentration and liquid level during a stage of combustion of the low-concentration gas.

[0035] In the embodiments of this application, please refer to Figure 5The equipment modules of the low-concentration gas direct combustion system may include a low-concentration gas safe transportation sub-module, a gas pretreatment sub-module, a combustion sub-module and a waste heat boiler sub-module; the temperature, concentration and other sensor modules in the perception module can collect temperature, pressure, concentration and other data of the equipment module, and each sensor module can transmit the collected first data to the local data storage center and the cloud center through the gateway device.

[0036] S120, constructing a matrix based on the first data and performing matrix operations according to a preset program to clean and standardize the first data to obtain first target data.

[0037] In an embodiment of the present application, when processing the first data, a data matrix can be constructed based on the first data, where each row of the data matrix represents a data sample and each column represents a feature. The first data is then cleaned using matrix operations to remove noise and outliers in the first data and fill in missing values. After obtaining the cleaned data, the data can be standardized.

[0038] S130. Map various entity parameters of the equipment module and various indicator data information contained in the first target data to the information space to construct a digital twin model, which can represent the operating status information of the equipment module.

[0039] In an embodiment of the present application, in order to simulate the operation of the actual equipment module in the information space, it is necessary to map all parameters of the equipment module to the information space to establish a digital twin model. To construct a digital twin model of a low-concentration gas direct safe and stable combustion device, it is necessary to simulate the combustion dynamics, fluid flow, heat transfer and control system in detail, and to perform geometric modeling, physical process modeling, chemical process modeling, control strategy modeling, sensor modeling and actuator modeling on the equipment module, so as to ensure that the established digital twin model can accurately represent the operating status information of the equipment module.

[0040] S140. When the first target data meets a preset threshold, second data is collected during the combustion of low-concentration gas, where the second data is used to characterize index information such as temperature, pressure, concentration, and liquid level during the combustion of low-concentration gas in another stage.

[0041] In the embodiment of the present application, after the digital twin model is established, the data in the equipment module of the low-concentration gas direct combustion system can be analyzed based on the digital twin model to monitor various indicators of the combustion system, thereby judging the safety of the combustion system. Figure 5,After building the digital twin model, the second data can continue to be collected through the perception module, and the second data can be transmitted to the local data storage center and the cloud center through devices such as the industrial communication module and the 5G network transmission module.

[0042] S150. Analyze the second data based on the digital twin model to obtain simulation data information corresponding to the current combustion process of the equipment module.

[0043] In the embodiments of this application, please refer to Figure 6 After the second data is transmitted to the local data center, the second data can be used as online real-time data to determine the operation of the digital twin model, and the second data can be analyzed to simulate the combustion process with high fidelity, thereby obtaining various specific data of the equipment modules in the low-concentration gas direct combustion system.

[0044] The above is a specific implementation method of the low-concentration gas combustion control method provided in the embodiment of the present application. By collecting data from the generator set equipment module, a digital twin model is established. The digital twin model can analyze the collected real-time data and simulate the combustion process with high fidelity, simulating different operating conditions and combustion conditions in a virtual environment to predict performance and safety.

[0045] In some embodiments, the second data is analyzed based on the digital twin model to obtain simulation data information corresponding to the current combustion process of the equipment module, that is, S150 may include the following steps:

[0046] S151. Based on the digital twin model, use computational fluid dynamics software to analyze the second data to obtain a continuous conservation equation.

[0047] In an embodiment of the present application, after obtaining the second data, a chemical reaction model can be constructed based on the Arrhenius formula, and physical process modeling can be performed based on the relevant fluid dynamics, energy conservation, and chemical reaction model in the aforementioned digital twin model to obtain continuous conservation equations.

[0048] S152. Add initial conditions, convection boundary conditions and thermal boundary conditions to the continuous conservation equations, where the initial condition is a steady-state solution or an empirical estimate, and the thermal boundary condition is a fixed temperature or heat flow.

[0049] In the embodiment of the present application, on the one hand, in order to solve the conservation equation, it is necessary to set the boundary conditions of the combustion chamber inlet and outlet, wherein the boundary conditions include flow rate, temperature, pressure and gas concentration. On the other hand, it is also necessary to set the initial flow and temperature conditions for each point in the calculation domain.

[0050] S153. The continuous equation is discretized into an algebraic equation using the finite volume method, and the discretized algebraic equation is solved based on a semi-implicit method of the pressure coupling equation group to obtain simulation data information.

[0051] In the embodiment of the present application, after adding initial conditions and boundary conditions to the conservation equation, the continuous conservation equation can be converted into a discrete equation using a finite volume method or a finite element method, and then a suitable numerical solver is selected to solve the incompressible flow. For example, a semi-implicit method based on a pressure coupled equation group can be used to solve the discretized algebraic equation.

[0052] In some embodiments, building a digital twin model of a low-concentration gas direct safe and stable combustion device requires detailed simulation of combustion dynamics, fluid flow, heat transfer, and control systems, such as Figure 2 As shown, the entity parameters of the equipment module and the indicator data information contained in the first target data are mapped to the information space to construct a digital twin model, that is, S130 may include the following steps:

[0053] S210, mapping the physical size of the equipment module to the information space and performing grid processing to obtain multiple control volumes.

[0054] In the embodiment of the present application, 3D CAD software can be used to draw an accurate three-dimensional model according to the size of the equipment module, and a geometric grid can be constructed based on the three-dimensional model to split the three-dimensional model and obtain multiple control bodies.

[0055] S220. Based on the conservation of mass, momentum and energy in the gas combustion process, physical modeling and chemical modeling are performed on multiple control bodies according to the indicator information in the first target data to obtain an initial twin model.

[0056] In the embodiment of the present application, it can be understood that the simulation of the gas combustion process needs to consider the conservation of mass, momentum and energy in the combustion process. The conservation of mass can be applied to each control body and discretized in matrix form. The Navier-Stokes equations can be applied to each control body to describe the motion equations of the conservation of momentum of the viscous and incompressible fluid of low-concentration gas. Based on this, the initial twin model is constructed.

[0057] S230. Select a proportional-integral-differential controller, use a first-order lag system to model the sensor and actuator to describe the dynamic behavior of the sensor and actuator, and obtain a target twin model for control system integration to maintain the stability of the combustion process.

[0058] In the embodiments of the present application, it can be understood that in order to maintain the stability of the combustion process and ensure efficiency and safety under different operating conditions, control system integration is required. In the process of establishing a digital twin model, control system integration usually involves control strategy modeling, sensor and actuator modeling. Specifically, when performing control strategy modeling, a proportional-integral-differential (PID) controller can be used. In addition, a first-order lag system can also be used to represent the sensor model. Based on this, a target twin model is obtained to maintain the stability of the combustion process.

[0059] S240. Digitally combine the initial twin model and the target twin model to obtain a digital twin model.

[0060] In an embodiment of the present application, by digitally combining the initial twin model and the target twin model, the fluid flow, heat transfer and control system in the low-concentration gas combustion process can be simulated to obtain a digital twin model.

[0061] In some embodiments, the constructed digital twin model can simulate the gas combustion process with high fidelity. On this basis, in order to perform remote maintenance and fault diagnosis on the gas combustion system, it is also necessary to train a time series model to determine whether the low-concentration gas combustion is in normal operation.

[0062] Based on the aforementioned low-concentration gas combustion control method, the present application also provides another implementation of the low-concentration gas combustion control method. The implementation between S120 and S130 further includes:

[0063] S310, dividing the first target data into multiple data groups containing the same number of elements to obtain input samples, and dividing the input samples into a training set, a validation set, and a test set.

[0064] In the embodiment of the present application, it can be understood that in the process of training the model based on the first target data, in order to prevent overfitting in the training, the input samples need to be divided into a training set, a validation set and a test set in proportion.

[0065] S320, taking the mean square error of the training set as the loss function, adopting the stochastic gradient descent optimizer to train the initial model, and obtaining the first sequence model and the hyperparameter information corresponding to the first sequence model.

[0066] In an embodiment of the present application, the training set is used to train the initial model, that is, to determine the learning parameters of the model, such as weights and biases. That is, the first sequence model and its corresponding hyperparameter information can be obtained by performing initial training on the training set.

[0067] S330: Validate the first sequence model based on the validation set, and select hyperparameter information to determine the second sequence model.

[0068] In the embodiment of the present application, it can be understood that the validation set does not participate in the determination of the learning parameters, that is, the validation set does not participate in the gradient descent process. The validation set is used to select hyperparameters based on the first sequence model and the corresponding hyperparameter information to obtain the second sequence model.

[0069] S340. Verify and adjust the second sequence model based on the test set to determine the time series model. The time series model is used to diagnose the real-time data in the low-concentration gas combustion process to determine whether the low-concentration gas combustion is in a normal operating state.

[0070] In the embodiment of the present application, it can be understood that the test set is used only once, and the test set is used to evaluate the second sequence model. The test set itself does not participate in the learning parameter process, nor does it participate in the hyperparameter selection process. After evaluating the second sequence model based on the test set, the second sequence model can be verified and adjusted based on the corresponding evaluation results to obtain the final mature time series model. Based on this, the time series model can be used to diagnose the real-time data in the low-concentration gas combustion process, and then determine whether the low-concentration gas combustion is in a normal operating state.

[0071] In some embodiments, the initial model is an LSTM model, which includes a forget gate, an input gate, an output gate, and a state unit. It is understandable that the LSTM model can alleviate the problems of gradient explosion or vanishing faced by traditional RNN.

[0072] In some embodiments, based on the aforementioned low-concentration gas combustion control method, the present application also provides another implementation of the low-concentration gas combustion control method. After S150, the implementation further includes:

[0073] S410, extracting second target data related to various physical parameters such as temperature distribution, pressure distribution, velocity field and gas concentration from the simulation data information.

[0074] S420: Create a visual mapping for each physical parameter based on the visualization software and the second target data to obtain first visualization information.

[0075] S430: Create a three-dimensional temperature field according to the first visualization information, and add interactive functions such as time axis control, view rotation, and view zooming to the three-dimensional temperature field to obtain a visualization module.

[0076] In the embodiment of the present application, it can be understood that after obtaining the simulation data information corresponding to the current combustion process of the equipment module, in order to intuitively display the low-concentration gas combustion process, information related to various physical parameters such as temperature distribution, pressure distribution, velocity field and gas concentration can be extracted from the simulation data information, and then processed using visualization software, and a three-dimensional temperature field is established to realize data visualization function. Furthermore, by adding interactive functions such as timeline control, view rotation and view zooming to the three-dimensional temperature field, the information in the low-concentration gas combustion process can be better displayed.

[0077] In some embodiments, based on the aforementioned low-concentration gas combustion control method, the present application also provides another implementation method of the low-concentration gas combustion control method, which, after S430, further includes:

[0078] S440, collecting low-concentration gas combustion information at different times, and determining simulated visual information at corresponding times based on a visualization module.

[0079] S450, comparing the low-concentration gas combustion information with the simulated visual information to obtain a display deviation.

[0080] S460. Adjust the view parameters in the visualization module based on the display deviation, where the view parameters include at least one of a color scheme, transparency, and a graphic layout.

[0081] In the embodiment of the present application, it can be understood that after the visualization module is established, the visualization model can also be adjusted based on the actual situation of low-concentration gas combustion, so as to ensure that the visualization model can more accurately reflect the actual low-concentration gas combustion information.

[0082] The present application also provides a low-concentration gas combustion control device 500, such as Figure 7 As shown, the device 500 may include the following modules: a collection module 510 , a cleaning module 520 , a mapping module 530 and an analysis module 540 .

[0083] The acquisition module 510 can be used to collect first data on the combustion of low-concentration gas in the equipment module of the generator set. The first data is used to characterize indicator information such as temperature, pressure, concentration and liquid level during the combustion of the low-concentration gas. The acquisition module 510 can also be used to collect second data during the combustion of the low-concentration gas when the first target data meets a preset threshold.

[0084] The cleaning module 520 can be used to construct a matrix based on the first data and perform matrix operations according to a preset program to clean and standardize the first data to obtain first target data.

[0085] The mapping module 530 can be used to map various entity parameters of the equipment module and various indicator data information contained in the first target data to the information space to construct a digital twin model, which can characterize the operating status information of the equipment module.

[0086] The analysis module 540 can be used to analyze the second data based on the digital twin model to obtain simulation data information corresponding to the current combustion process of the equipment module.

[0087] According to an embodiment of the present application, any multiple modules among the acquisition module 510, the cleaning module 520, the mapping module 530 and the analysis module 540 can be combined into one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module.

[0088] In some embodiments, the mapping module 530 is specifically configured to: map the physical dimensions of the equipment module to the information space and perform gridding processing to obtain multiple control bodies; based on the conservation of mass, momentum, and energy in the gas combustion process, perform physical modeling and chemical modeling on the multiple control bodies according to the indicator information in the first target data to obtain an initial twin model; select a proportional integral differential controller, and use a first-order lag system to model the sensors and actuators to describe the dynamic behavior of the sensors and actuators, and obtain a target twin model for control system integration to maintain the stability of the combustion process; digitally combine the initial twin model and the target twin model to obtain a digital twin model.

[0089] In some embodiments, the analysis module 540 is specifically configured as follows: based on the digital twin model, use computational fluid dynamics software to analyze the second data to obtain continuous conservation equations; add initial conditions, convection boundary conditions and thermal boundary conditions to the continuous conservation equations, wherein the initial condition is a steady-state solution or an empirical estimate, and the thermal boundary condition is a fixed temperature or heat flow; use the finite volume method to discretize the continuous equations into algebraic equations, and solve the discretized algebraic equations based on the semi-implicit method of the pressure-coupled equations to obtain simulation data information.

[0090] In some embodiments, please refer to Figure 8The low-concentration gas combustion control device 500 may further include a determination module 550, which may be specifically configured to: divide the first target data into a plurality of data groups containing the same number of elements to obtain input samples, and divide the input samples into a training set, a validation set, and a test set; use the mean square error of the training set as a loss function, use a stochastic gradient descent optimizer to train the initial model, and obtain a first sequence model and hyperparameter information corresponding to the first sequence model; verify the first sequence model based on the validation set, and select the hyperparameter information to determine the second sequence model;

[0091] The second sequence model is verified and adjusted based on the test set to determine the time series model. The time series model is used to diagnose the real-time data in the low-concentration gas combustion process to determine whether the low-concentration gas combustion is in normal operation.

[0092] In some other optional embodiments, please refer to Figure 8 The low-concentration gas combustion control device 500 may also include a visualization module 560, which may be specifically configured as follows: extracting second target data related to various physical parameters such as temperature distribution, pressure distribution, velocity field, and gas concentration from the simulation data information; creating a visual mapping for various physical parameters based on the visualization software and the second target data to obtain first visualization information; creating a three-dimensional temperature field based on the first visualization information, and adding interactive functions such as timeline control, view rotation, and view zooming to the three-dimensional temperature field to obtain a visualization module.

[0093] In some embodiments, the visualization module 560 can also be specifically configured to: collect low-concentration gas combustion information at different times, and determine the simulated visual information at the corresponding time based on the visualization module; compare the low-concentration gas combustion information with the simulated visual information to obtain display deviation; based on the display deviation, adjust the view parameters in the visualization module, and the view parameters include at least one of the color scheme, transparency and graphic layout.

[0094] Figure 8 Each module in the device shown has the function of implementing each step in the aforementioned low-concentration gas combustion control method and can achieve its corresponding technical effect. For the sake of concise description, it will not be repeated here.

[0095] In some embodiments, the present application provides an electronic device 600, the structure diagram of the electronic device 600 is as follows: Fig. 9 shown.

[0096] The electronic device may include a processor 610 and a memory 620 storing computer program instructions.

[0097] Specifically, the processor 610 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0098] The memory 620 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 620 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. In appropriate cases, the memory 620 may include a removable or non-removable (or fixed) medium. In appropriate cases, the memory 620 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 620 is a non-volatile solid-state memory.

[0099] The memory 620 may include a read-only memory (ROM), a random access memory (RAM), a disk storage medium device, an optical storage medium device, a flash memory device, an electrical, optical or other physical / tangible memory storage device. Therefore, generally, the memory 620 includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) encoded with software including computer executable instructions, and when the software is executed (e.g., by one or more processors), it can perform the operations described in any one of the low-concentration gas combustion control methods in the above-mentioned embodiments.

[0100] The processor 610 implements any one of the low-concentration gas combustion control methods in the above embodiments by reading and executing computer program instructions stored in the memory 620 .

[0101] In one example, the electronic device may further include a communication interface 630 and a bus 640. Fig. 9 As shown, the processor 610, the memory 620, and the communication interface 630 are connected via a bus 640 and communicate with each other.

[0102] The communication interface 630 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0103] Bus 640 includes hardware, software or both, and the parts of online data flow billing equipment are coupled to each other. For example, but not limitation, bus may include accelerated graphics port (AGP) or other graphics bus, enhanced industrial standard architecture (EISA) bus, front-end bus (FSB), hypertransport (HT) interconnection, industrial standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 640 may include one or more buses. Although the present application embodiment describes and shows a specific bus, the application considers any suitable bus or interconnection.

[0104] In addition, in combination with the low-concentration gas combustion control method in the above embodiment, the embodiment of the present application can provide a computer-readable storage medium for implementation. The computer-readable storage medium stores computer program instructions; when the computer program instructions are executed by the processor, any one of the low-concentration gas combustion control methods in the above embodiment is implemented.

[0105] It should be clear that the present application is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present application.

[0106] The functional blocks shown in the above block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0107] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be performed simultaneously.

[0108] Aspects of the present disclosure are described above with reference to the flowchart and / or block diagram of the method, device (system) and computer program product according to the embodiment of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field programmable logic circuit. It can also be understood that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs a specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0109] The above are only specific implementation methods of the present application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the protection scope of the present application is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in this application, and these modifications or replacements should be covered by the protection scope of this application.

Claims

1. A low-concentration gas combustion control method, characterized in that: include: Collecting first data of low-concentration gas burning in a generator set equipment module, wherein the first data is used to characterize index information such as temperature, pressure, concentration, and liquid level during a stage of low-concentration gas combustion; Constructing a matrix based on the first data and performing matrix operations according to a preset program to clean and standardize the first data to obtain first target data; Mapping various entity parameters of the equipment module and various indicator data information contained in the first target data to the information space to construct a digital twin model, wherein the digital twin model can represent the operating status information of the equipment module; When the first target data meets the preset threshold, second data in the combustion process of low-concentration gas is collected, and the second data is used to characterize index information such as temperature, pressure, concentration and liquid level of the low-concentration gas in another stage of combustion; The second data is analyzed based on the digital twin model to obtain simulation data information corresponding to the current combustion process of the equipment module.

2. The low-concentration gas combustion control method according to claim 1, characterized in that: The mapping of various entity parameters of the equipment module and various indicator data information contained in the first target data to the information space to construct a digital twin model includes: Mapping the physical dimensions of the equipment module to the information space and performing gridding processing to obtain a plurality of control volumes; Based on the conservation of mass, momentum and energy in the gas combustion process, physical modeling and chemical modeling are performed on the plurality of control bodies according to the indicator information in the first target data to obtain an initial twin model; A proportional-integral-derivative controller is selected, and a first-order lag system is used to model the sensor and actuator to describe their dynamic behaviors, and a target twin model is obtained for control system integration to maintain the stability of the combustion process. The initial twin model and the target twin model are digitally combined to obtain a digital twin model.

3. The low-concentration gas combustion control method according to claim 1, characterized in that: After constructing a matrix based on the first data and performing matrix operations according to a preset program to clean and standardize the first data to obtain first target data, the method further includes: Dividing the first target data into a plurality of data groups containing the same number of elements to obtain input samples, and dividing the input samples into a training set, a validation set, and a test set; Using the mean square error of the training set as a loss function, and using a stochastic gradient descent optimizer to train the initial model, to obtain a first sequence model and hyperparameter information corresponding to the first sequence model; Verifying the first sequence model based on the verification set, and selecting the hyperparameter information to determine a second sequence model; The second sequence model is verified and adjusted based on the test set to determine a time series model, wherein the time series model is used to diagnose real-time data during the low-concentration gas combustion process to determine whether the low-concentration gas combustion is in a normal operating state.

4. The low-concentration gas combustion control method according to claim 3, characterized in that: The initial model is an LSTM model, which includes a forget gate, an input gate, an output gate and a state unit.

5. The low-concentration gas combustion control method according to claim 1, characterized in that: The analyzing the second data based on the digital twin model to obtain simulation data information corresponding to the current combustion process of the equipment module includes: Based on the digital twin model, using computational fluid dynamics software to analyze the second data to obtain a continuous conservation equation; Adding initial conditions, convection boundary conditions and thermal boundary conditions to the continuous conservation equations, wherein the initial condition is a steady-state solution or an empirical estimate, and the thermal boundary condition is a fixed temperature or heat flow; The continuity equation is discretized into an algebraic equation using a finite volume method, and the discretized algebraic equation is solved based on a semi-implicit method of a pressure-coupled equation group to obtain simulation data information.

6. The low-concentration gas combustion control method according to claim 1, characterized in that: After analyzing the second data based on the digital twin model to obtain simulation data information corresponding to the current combustion process of the equipment module, the method further includes: Extracting second target data related to various physical parameters such as temperature distribution, pressure distribution, velocity field and gas concentration from the simulation data information; Creating a visual mapping for each of the physical parameters based on the visualization software and the second target data to obtain first visualization information; A three-dimensional temperature field is created according to the first visualization information, and interactive functions such as timeline control, view rotation and view zooming are added to the three-dimensional temperature field to obtain a visualization module.

7. The low-concentration gas combustion control method according to claim 6, characterized in that: After creating a three-dimensional temperature field according to the first visualization information and adding interactive functions such as timeline control, view rotation and view zooming to the three-dimensional temperature field to obtain a visualization module, the method further includes: Collecting low-concentration gas combustion information at different times, and determining simulated visual information at corresponding times based on the visualization module; Comparing the low-concentration gas combustion information with the simulated visual information to obtain a display deviation; Based on the display deviation, a view parameter in the visualization module is adjusted, the view parameter comprising at least one of a color scheme, transparency, and a graphic layout.

8. A low-concentration gas combustion control device, characterized in that: include: A collection module, used to collect first data of low-concentration gas burning in the equipment module of the generator set, wherein the first data is used to characterize index information such as temperature, pressure, concentration and liquid level during the combustion of the low-concentration gas; A cleaning module, used for constructing a matrix based on the first data and performing matrix operations according to a preset program to clean and standardize the first data to obtain first target data; A mapping module, used to map various entity parameters of the equipment module and various indicator data information contained in the first target data to an information space to construct a digital twin model, wherein the digital twin model can represent the operating status information of the equipment module; The acquisition module is further used to acquire second data during the low-concentration gas combustion process when the first target data meets a preset threshold; An analysis module is used to analyze the second data based on the digital twin model to obtain simulation data information corresponding to the current combustion process of the equipment module.

9. An electronic device, characterized in that: include: A processor, a memory, and a program stored in the memory and executable on the processor, wherein the program, when executed by the processor, implements the low-concentration gas combustion control method as claimed in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores programs or instructions, and when the programs or instructions are executed by the processor, the low-concentration gas combustion control method according to any one of claims 1 to 7 is implemented.

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