A CO catalytic purification device and method for fire flue gas

Abstract

This invention provides a CO catalytic purification device and method for fire flue gas, relating to the field of flue gas heating and catalytic technology. The device includes: a housing, a combined overcurrent catalytic metal mesh, a flue gas dust collector, a fan, and a reaction temperature control system. The housing has a hollow structure with an air inlet at one end. The combined overcurrent catalytic metal mesh is disposed inside the housing and comprises at least two layers of catalytic metal mesh. The flue gas dust collector is fixedly disposed between the air inlet of the housing and the combined overcurrent catalytic metal mesh. The fan is fixedly disposed between the air inlet of the housing and the flue gas dust collector. The reaction temperature control system is electrically connected to both the combined overcurrent catalytic metal mesh and the fan. This invention significantly increases the contact area between the flue gas and the catalyst by designing a multi-layered structure in the combined overcurrent catalytic metal mesh, with each layer composed of serpentine strip metal mesh connected in series and parallel, thereby improving the catalytic purification efficiency.

Description

Technical Field

[0001] This invention relates to the field of flue gas heating and catalysis technology, and more specifically, to a CO catalytic device and purification method for fire flue gas. Background Technology

[0002] Fire, as a high-risk event, poses a serious threat to public safety, with fire smoke being a significant contributing factor to casualties. Fire smoke contains a large amount of suspended particulate matter and toxic gases, especially carbon monoxide (CO), whose high concentration and rapid formation make it a primary toxic gas. Currently, traditional CO purification technologies mainly include physical adsorption, biological purification, and combustion control. However, these methods face many limitations in practical applications, such as limited adsorption capacity, low treatment efficiency, and complex equipment, making it difficult to meet the needs of rapid response at fire scenes. Furthermore, existing catalytic purification systems often rely on overall heating of the flue gas, resulting in slow initial heating rates and high energy consumption, leading to significant heat waste and significantly increased economic costs. This makes it difficult to quickly heat the flue gas to the specific temperature required for the catalytic reaction during a sudden fire, thus reducing purification effectiveness and efficiency.

[0003] In view of the limitations of the prior art, this application proposes a CO catalytic purification device and method for fire flue gas, which can monitor and adjust the flue gas temperature in real time to adapt to the rapid changes in CO concentration and temperature of flue gas during the fire process. Summary of the Invention

[0004] The purpose of this invention is to provide a CO catalytic purification device and method for fire smoke to improve the aforementioned problems. To achieve the above objective, the technical solution adopted by this invention is as follows:

[0005] In a first aspect, this application provides a CO catalytic purification device for fire flue gas, comprising: a housing, a combined overcurrent catalytic metal mesh, a flue gas dust collector, a fan, and a reaction temperature control system. The housing is a hollow structure, with an air inlet at one end; the combined overcurrent catalytic metal mesh is disposed within the housing, comprising at least two layers of catalytic metal mesh, all arranged in parallel; the flue gas dust collector is fixedly disposed between the air inlet of the housing and the combined overcurrent catalytic metal mesh; the fan is fixedly disposed between the air inlet of the housing and the flue gas dust collector; and the reaction temperature control system is electrically connected to both the combined overcurrent catalytic metal mesh and the fan.

[0006] Furthermore, the housing includes a baffle grille and a metal box. The metal box has a hollow structure and an entrance is provided at one end. The baffle grille cooperates with the entrance of the metal box and is detachably installed at the entrance of the metal box.

[0007] Furthermore, the flue gas dust removal box includes a filter screen and an activated carbon box that are fixedly connected to each other, with the filter screen fixedly disposed on one side near the fan.

[0008] Furthermore, the catalytic metal mesh includes at least two strip metal meshes, conductive copper sheets, and conductive contacts. Adjacent strip metal meshes are fixedly connected by conductive copper sheets and form a serpentine arrangement. The conductive contacts are fixedly connected to the two outermost strip metal meshes respectively.

[0009] Furthermore, the combined overcurrent catalytic metal mesh also includes a heat-resistant insulating plate grid, which cooperates with the catalytic metal mesh, and each layer of the catalytic metal mesh is fixedly disposed between two layers of the heat-resistant insulating plate grid.

[0010] Furthermore, the reaction temperature control system includes a gas temperature probe, a gas flow rate probe, a metal mesh temperature probe, a CO concentration probe, a PLC controller, and an adjustable power supply. The PLC controller is electrically connected to the gas temperature probe, the gas flow rate probe, the metal mesh temperature probe, and the adjustable power supply. The gas temperature probe and the gas flow rate probe are positioned between the flue gas dust collector and the combined overcurrent catalytic metal mesh. The metal mesh temperature probe is positioned on the catalytic metal mesh. The adjustable power supply is electrically connected to the combined overcurrent catalytic metal mesh and the fan.

[0011] Secondly, this application provides a method for catalytic purification of CO in fire flue gas, comprising:

[0012] Acquire first information and second information. The first information is the physical parameters of the area to be purified, including the size of the site and material properties. The second information is the fire smoke development data collected from the on-site fire pre-experiment.

[0013] Based on the first information, dynamic simulation processing is performed to generate a preliminary simulation dataset by simulating fire conditions under different working conditions.

[0014] Based on the second information, the preliminary simulation dataset is optimized to obtain an optimized dataset;

[0015] The model is constructed based on the optimized dataset. By training and validating the preset neural network model, the relationship between key influencing parameters and fire development is established to obtain the fire smoke situation development model.

[0016] Real-time sensor data collected on-site is acquired and input into the fire smoke situation development model for prediction processing. The prediction result is obtained by predicting the current CO concentration and the subsequent fire development trend.

[0017] An optimized device parameter setting scheme is calculated based on the prediction results. The device parameter setting scheme includes the start-up of the axial flow fan, the number of catalytic metal mesh layers, and the temperature setting.

[0018] The beneficial effects of this invention are as follows:

[0019] This invention significantly increases the contact area between flue gas and catalyst by designing a multi-layer structure in the combined overcurrent catalytic metal mesh, with each layer consisting of serpentine strip metal mesh connected in series and parallel, thereby improving the catalytic purification efficiency. The voltage regulation device of this invention can adjust the voltage signal of the metal mesh in real time according to the temperature, flow rate and CO concentration predicted by the fire flue gas situation development model.

[0020] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing embodiments of the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings. Attached Figure Description

[0021] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0022] Figure 1 This is a schematic diagram of the structure of the CO catalytic purification device for fire flue gas described in an embodiment of the present invention;

[0023] Figure 2 This is an internal schematic diagram of the CO catalytic purification device for fire flue gas described in an embodiment of the present invention;

[0024] Figure 3 This is a schematic diagram of the combined overcurrent catalytic metal mesh structure described in an embodiment of the present invention;

[0025] Figure 4 This is a schematic diagram of the catalytic metal mesh structure described in an embodiment of the present invention;

[0026] Figure 5 This is a schematic diagram of the reaction temperature control system described in an embodiment of the present invention;

[0027] Figure 6 This is a schematic diagram of a series combination of several single-layer catalytic metal meshes;

[0028] Figure 7 This is a schematic diagram of a parallel combination of several single-layer catalytic metal meshes;

[0029] Figure 8 This is a schematic diagram of a series-parallel combination of several monolayer catalytic metal meshes;

[0030] Figure 9 This is a schematic diagram of the elongated grid resistor described in an embodiment of the present invention;

[0031] Figure 10 This is a control flowchart of the reaction temperature control system described in the embodiments of the present invention;

[0032] Figure 11 This is a flowchart of the CO catalytic purification method for fire flue gas described in an embodiment of the present invention.

[0033] The diagram shows the following components: 1. Housing; 11. Baffle grille; 12. Metal housing; 2. Combined overcurrent catalytic metal mesh; 21. Catalytic metal mesh; 211. Strip metal mesh; 212. Conductive copper sheet; 213. Conductive contact; 22. Heat-resistant insulating board grille; 3. Flue gas dust collector box; 31. Filter screen; 32. Activated carbon box; 4. Fan; 5. Reaction temperature control system; 51. Gas temperature probe; 52. Gas flow rate probe; 53. Metal mesh temperature probe; 54. CO concentration probe; 55. PLC controller; 56. Adjustable power supply. Detailed Implementation

[0034] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0035] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this invention, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0036] Example 1:

[0037] This embodiment provides a CO catalytic purification device for fire flue gas, such as... Figure 1 As shown, the system includes a housing 1, a combined overcurrent catalytic metal mesh 2, a flue gas dust collector 3, a fan 4, and a reaction temperature control system 5. The housing 1 has a hollow structure, with an air inlet at one end. The combined overcurrent catalytic metal mesh 2 is housed within the housing 1 and comprises at least two layers of catalytic metal mesh 21. All catalytic metal meshes 21 are arranged in parallel, and several single-layer catalytic metal meshes 21 can be freely combined in series and parallel according to different heating powers. Figure 7 As shown, if the resistance of the single-layer catalytic metal mesh 21 is too high and it is necessary to reduce the total resistance, a parallel combination is preferred; such as Figure 6 As shown, if the resistance value of the single-layer catalytic metal mesh 21 is too small, a higher total resistance is required, which tends to favor a series combination; such as Figure 8 As shown, a hybrid series-parallel combination can also be selected according to actual needs to achieve overcurrent heating catalytic purification. The flue gas dust collector 3 is fixedly installed between the air inlet of the housing 1 and the combined overcurrent catalytic metal mesh 2; the fan 4 is fixedly installed between the air inlet of the housing 1 and the flue gas dust collector 3 to collect the flue gas from the fire scene as the airflow power source for the subsequent purification device; the reaction temperature control system 5 is electrically connected to the combined overcurrent catalytic metal mesh 2 and the fan 4 respectively.

[0038] Preferably, such as Figure 2 As shown, the housing 1 includes a baffle grille 11 and a metal box 12. The metal box 12 has a hollow structure and an entrance at one end. The baffle grille 11 cooperates with the entrance of the metal box 12, and the baffle grille 11 is detachably installed at the entrance of the metal box 12. The baffle grille 11 is used to block foreign objects from entering the box and prevent interference with the normal operation of the device. The metal box 12 is used to protect and support the internal structure.

[0039] Preferably, such as Figure 2 As shown, the flue gas dust removal box 3 includes a filter screen 31 and an activated carbon box 32 that are fixedly connected to each other. The filter screen 31 is fixedly installed on the side near the fan 4.

[0040] Preferably, such as Figure 4As shown, the catalytic metal mesh 21 includes at least two strip-shaped metal meshes 211, conductive copper sheets 212, and conductive contacts 213. Adjacent strip-shaped metal meshes 211 are fixedly connected by conductive copper sheets 212 to form a serpentine arrangement, and the two strip-shaped metal meshes are separated by an insulating and heat-resistant material. The conductive contacts 213 are fixedly connected to the two outermost strip-shaped metal meshes 211 respectively. Further, this embodiment discloses a specific design method for the strip-shaped metal meshes 211: it is known that the heating power per unit area of ​​the metal mesh is determined by the current passing through it; therefore, it is assumed that the resistance of the elongated strip mesh is as follows: Figure 9 As shown, the grid resistor consists of two first resistance wires and several second resistance wires disposed between the two first resistance wires, and is derived from the following formula:

[0041]

[0042]

[0043] Among them, R 总 R1 represents the total resistance of the grid resistor; R2 represents the resistance of the first resistance wire; and N represents the number of resistance wires.

[0044] When N is sufficiently large, the value of (R1-R2) can be ignored. Therefore, R 总 We can assume that it consists of N second resistance wires connected in parallel. Based on the current relationship in parallel circuits, we can deduce that:

[0045] I 总 =I²*N;

[0046] Among them, I 总 I0 represents the total current; I2 represents the current in the second resistance wire. That is, in practical applications, the sum of the currents in the N R2 wires does not exceed the rated current I0. 总 .

[0047] Based on the width determination criterion: to ensure that the heating power of a single second resistance wire meets the requirements, the current requirement through the second resistance wire is 0.068~0.120A. This is combined with the actual overload current I. 总 The number of R2 can be calculated as N = I. 总 / I2. Then we have:

[0048] A = N*(D+d);

[0049] Where A represents the width of the strip metal mesh; D represents the diameter of the second resistance wire; and d represents the aperture.

[0050] Based on the length determination criterion: Given the actual flue gas flow cross-section S, and using strips of metal mesh of width A to piece together metal mesh of the same area, the total length L is then determined. 总=S / A. Then cut several appropriate lengths and connect them in a serpentine series using copper sheets, ensuring that there is a gap between each strip of metal mesh to prevent short circuits.

[0051] This design allows for the creation of serpentine strip metal meshes tailored to the required rated power and gas purification cross-section. Furthermore, the number of catalytic metal mesh layers can be freely increased based on the actual purification effect, enhancing purification efficiency and providing flexible and versatile combinations for practical applications.

[0052] Furthermore, this embodiment discloses the steps for coating the strip metal mesh 211 with catalyst and protective layer: First, soak the strip metal mesh 211 in alkali to remove surface oil; then, mix the catalyst and binder in proportion and adhere them to the surface of the metal mesh through a high-temperature sintering process; finally, coat the surface with a protective layer to complete the fabrication of the strip catalytic metal mesh 21. The preferred material for the strip metal mesh is readily available resistance wire mesh (80-120 mesh aperture), such as nickel-chromium alloy 2080 mesh, iron-chromium-aluminum alloy mesh, tungsten wire mesh, copper-nickel alloy mesh, stainless steel mesh (304 and 316 types), or nickel-iron alloy mesh; the catalyst material includes single-atom catalysts containing transition metal oxides and precious metals such as copper, nickel, aluminum, titanium, cobalt, and iron; the protective layer material includes materials with similar functions and applications, such as carrageenan, agar, pectin, xanthan gum, guar gum, carboxymethyl cellulose, gelatin, locust bean gum, and sodium alginate.

[0053] Preferably, such as Figure 3 As shown, the combined overcurrent catalytic metal mesh 2 also includes a heat-resistant insulating plate grid 22. The heat-resistant insulating plate grid 22 and the catalytic metal mesh 21 cooperate with each other, and each layer of catalytic metal mesh 21 is fixedly arranged between two layers of heat-resistant insulating plate grid 22.

[0054] Preferably, such as Figure 5 As shown, the reaction temperature control system 5 includes a gas temperature probe 51, a gas flow rate probe 52, a metal mesh temperature probe 53, a CO concentration probe 54, a PLC controller 55, and an adjustable power supply 56. The PLC controller 55 is electrically connected to the gas temperature probe 51, the gas flow rate probe 52, the metal mesh temperature probe 53, and the adjustable power supply 56. The gas temperature probe 51 and the gas flow rate probe 52 are positioned between the flue gas dust collector 3 and the combined overcurrent catalytic metal mesh 2. The metal mesh temperature probe 53 is positioned on the catalytic metal mesh 21. The adjustable power supply 56 is electrically connected to the combined overcurrent catalytic metal mesh 2 and the fan 4. Based on the collected data and the control target, the PLC controller 55 generates a control signal for the adjustable power supply 56 to control the number of layers and heating power of the catalytic metal mesh 21, ensuring that the CO purification device operates as required.

[0055] The purification process of the aforementioned CO purification device for fire smoke is as follows: When the CO concentration exceeds the safety threshold, the device automatically turns on the axial flow fan 4 and activates the corresponding number of catalytic metal mesh layers 21 according to the CO concentration. Simultaneously, based on real-time sensor data, the fire smoke situation development model can predict when the CO concentration will exceed the safety threshold, thus allowing for advance control of the fan 4 and catalytic metal mesh 21. During the preheating stage, the protective layer of the metal mesh will detach automatically at 60°C, exposing the highly catalytically active metal mesh surface. The fan 4 is responsible for collecting the fire smoke and providing the airflow power source. The collected smoke passes through the smoke dust collector 3, removing fine particles and dust from the fire area. Simultaneously, the device collects the smoke temperature, flow rate, metal mesh temperature, and CO concentration. The PLC controller 55 analyzes and processes these parameters, outputting control signals to the adjustable power supply 56 to optimize the number of layers of the catalytic metal mesh 21 and control its surface reaction temperature within the optimal reaction temperature range of the catalyst. Finally, the flue gas from the fire site (mainly CO) after dust suppression is catalytically purified by a combined overcurrent catalytic metal mesh 2 that reaches the optimal reaction temperature, so that the toxic CO gas is converted into non-toxic carbon dioxide (CO2).

[0056] Example 2:

[0057] This embodiment provides a method for catalytic purification of CO in fire flue gas.

[0058] See also Figure 11 The figure shows that the method includes steps S100 to S500.

[0059] Step S100: Obtain first information and second information. The first information is the physical parameters of the area to be purified, including the size of the site and material properties. The second information is the fire smoke development data collected during the on-site fire pre-experiment.

[0060] Understandably, the size of the site determines the space for smoke diffusion, while material properties (such as flammability and thermal conductivity) affect the combustion characteristics of the fire and the generation of smoke. These factors directly influence the concentration and distribution of CO. The second piece of information provides actual data on the development of the smoke situation. This data reflects the generation, flow, and changes of smoke under specific conditions, and is the basis for effective prediction and response.

[0061] Step S200: Perform dynamic simulation processing based on the first information, and generate a preliminary simulation dataset by simulating fire conditions under different working conditions.

[0062] Further, step S200 includes steps S210 to S240.

[0063] Step S210: Perform preliminary scene modeling based on the first information. By modeling the site size and material properties, use the finite element analysis method to simulate the dynamic characteristics of fire propagation and smoke flow to obtain a preliminary fire scene model.

[0064] It should be noted that this modeling method can simulate the dynamic characteristics of fire propagation paths and smoke flow, capture the influence of materials on flame propagation and smoke diffusion, and provide the necessary geometric and physical basis for subsequent fluid dynamics simulations.

[0065] Step S220: Perform fluid dynamics simulation processing based on the preliminary fire scene model. Simulate the movement and diffusion of smoke in the fire scene using computational fluid dynamics algorithms. Combine the working conditions of different wind speeds, temperature gradients and fire source intensities to obtain a preliminary smoke flow dataset.

[0066] Understandably, this simulation incorporates various environmental factors, such as wind speed, temperature gradient, and ignition source intensity, to reflect the behavior of smoke under actual fire conditions. Through this process, the preliminary smoke flow dataset obtained includes the velocity field, temperature field, and concentration field of the smoke, providing crucial data for subsequent analysis.

[0067] Step S230: Analyze and process the fire development status based on the preliminary smoke flow dataset. By applying time series analysis and state transition model, and combining the actual combustion rate and smoke composition changes, analyze the changes in the fire state at different time points to obtain dynamic data on fire development.

[0068] Understandably, this step of fire development status analysis can reveal the dynamic patterns of fire development, including changes in smoke composition and their impact on overall fire behavior, helping to identify critical moments in fire development.

[0069] Step S240: Based on the dynamic data of fire development, integrate and process the simulation results. By integrating the fluid dynamics results and the state transition analysis results, a preliminary simulation dataset is generated.

[0070] It should be noted that the integration process ensures that data from different sources (such as fluid flow and changes in fire status) are complementary, providing comprehensive predictions of fire smoke behavior.

[0071] Step S300: Optimize the preliminary simulation dataset based on the second information to obtain the optimized dataset;

[0072] Further, step S300 includes steps S310 to S340.

[0073] Step S310: Adjust the model parameters based on the actual fire pre-experiment data. By comparing the preliminary simulation dataset with the fire smoke situation data, use the least squares optimization algorithm to adjust the combustion efficiency and heat release rate in the fire model to obtain the improved fire model parameters.

[0074] Understandably, using the least squares optimization algorithm to adjust key parameters in the fire model (such as combustion efficiency and heat release rate) can effectively reduce the error between model predictions and actual observations.

[0075] Step S320: Perform sensitivity analysis based on the improved model parameters. Use a global sensitivity analysis algorithm to evaluate the influence of each input parameter on the fire state and smoke characteristic output, and identify the parameter that has the greatest impact on the model results to obtain the sensitivity analysis results.

[0076] Understandably, this analysis helps identify the parameters that have the greatest impact on model results, thereby allowing resources to be focused on optimizing these key factors and improving the effectiveness of the model.

[0077] Step S330: Perform data regression processing based on the sensitivity analysis results. Use a multiple linear regression model to fit the relationship between key influencing parameters and flue gas concentration and temperature to obtain an optimized mathematical model.

[0078] It should be noted that this step aims to establish an optimized mathematical model that accurately describes the relationships between various influencing factors, facilitating subsequent analysis and prediction.

[0079] Step S340: Perform dataset augmentation processing based on the optimized mathematical model, generate new sample data based on the existing preliminary simulation dataset, and obtain the optimized dataset.

[0080] Preferably, based on the existing preliminary simulation dataset, new sample data is created using Generative Adversarial Networks (GANs) or other data generation techniques to enhance the diversity and coverage of the dataset. This supplements the deficiencies in the original dataset and improves the robustness and generalization ability of the model.

[0081] Step S400: Based on the optimized dataset, perform model construction processing, and establish the relationship between key influencing parameters and fire development status by training and validating the preset neural network model to obtain the fire smoke situation development model.

[0082] Further, step S400 includes steps S410 to S440.

[0083] Step S410: Perform feature selection processing based on the optimized dataset. By applying the recursive feature elimination algorithm, evaluate the impact of each feature on the fire development status, and gradually remove features that have a small impact on model performance to obtain a simplified feature set.

[0084] Understandably, this step improves the model's efficiency and effectiveness by gradually removing features that have a smaller impact on model performance, ensuring that the most informative features are retained.

[0085] Step S420: Based on the simplified feature set, construct a neural network model by designing a multi-layer feedforward neural network and configuring the ReLU activation function and mean squared error loss function to establish a preliminary neural network model.

[0086] It should be noted that the ReLU activation function can effectively handle nonlinear relationships, enhance the expressive power of the model, and is suitable for complex prediction tasks of fire development.

[0087] Step S430: Perform model training based on the preliminary neural network model. Iteratively train the model using the input features of the optimized dataset and the corresponding fire development output. Adjust the model weights to minimize the loss function to obtain the trained neural network model.

[0088] Step S440: Perform model validation processing based on the trained neural network model. Use cross-validation to evaluate the generalization ability of the model, compare the error between the prediction results and the actual fire development status, and obtain the fire smoke situation development model.

[0089] This process identifies the model's performance on different datasets, ensuring its reliability and stability in practical applications. The resulting fire smoke situation development model possesses high predictive power and practicality, providing effective support for fire emergency response.

[0090] Step S500: Acquire real-time sensor data collected on-site and input the real-time sensor data into the fire smoke situation development model for prediction processing. The prediction result is obtained by predicting the current CO concentration and the subsequent fire development trend.

[0091] Further, step S500 includes steps S510 to S530.

[0092] Step S510: Perform time series analysis processing based on real-time sensing data. Divide the collected time series data into multiple time periods of preset length using the sliding window method to obtain time series features.

[0093] Understandably, this step can extract dynamic features from time series data, reflecting the trend of smoke concentration changes during a fire. The obtained time series features provide structured data for subsequent model input, which helps to capture instantaneous changes during the fire's development.

[0094] Step S520: Perform input format conversion processing based on time series characteristics. By using standardization and normalization techniques, the time series data is converted into a format suitable for model input to obtain the converted time series data.

[0095] It should be noted that standardization can eliminate the influence between different units of measurement, allowing the model to learn input features more effectively. Normalization ensures that the data is within the same range, which helps improve the stability of model training.

[0096] Step S530: Perform model prediction processing based on the converted time series data, and use the forward propagation algorithm to calculate the current CO concentration and the subsequent fire development trend to obtain the prediction results.

[0097] Understandably, the final prediction results provide an important basis for decision-making, helping to respond quickly to changes at the fire scene and optimize handling measures.

[0098] Step S600: Calculate the optimized device parameter setting scheme based on the prediction results. The device parameter setting scheme includes the start-up of the axial flow fan, the number of catalytic metal mesh layers, and the temperature setting.

[0099] Furthermore, based on the prediction results, a device parameter setting scheme is set, and the corresponding control process is implemented, such as... Figure 10 As shown, it includes a pre-regulation stage and a secondary optimization regulation stage.

[0100] Step S610: In the pre-control stage, if the fire smoke development model predicts that the CO concentration exceeds the safety standard threshold, the ventilation and smoke extraction equipment is immediately activated, and the PLC controller controls the number of catalytic metal mesh layers according to the CO concentration. If the predicted flue gas temperature does not exceed the lower limit of the optimal reaction temperature of the catalyst, the PLC controller outputs control information to the adjustable power supply based on the predicted flue gas temperature and flow rate, and preheats the catalytic metal mesh temperature to the lower limit of the optimal reaction temperature. If the predicted flue gas temperature exceeds the lower limit of the optimal reaction temperature of the catalyst, the catalytic metal mesh does not need to be heated in this stage, and the smoke stream is purified by dust suppression treatment and then passes through the catalytic metal mesh.

[0101] Step S620: In the secondary optimization and control stage, the dust-reduced flue gas passes through the catalytic metal mesh, and the flue gas temperature, flow rate, and CO concentration after purification are collected in real time to determine whether the CO concentration meets the safety emission standards. If the safety emission standards are met, the output voltage is maintained to control the temperature of the catalytic metal mesh to be constant. If the safety emission standards are not met, the PLC controller increases the output voltage signal and raises the temperature of the catalytic metal mesh according to the real-time flue gas temperature and flow rate until the CO concentration emission standards are met. If the maximum temperature of the metal mesh controlled by the output voltage exceeds the upper limit of the optimal reaction temperature of the catalyst, and the CO concentration still does not meet the safety emission standards, the number of catalytic metal mesh layers is increased, and the temperature of the secondary added catalytic metal mesh is increased until the CO concentration emission standards are met, and the maximum temperature of the catalytic metal mesh does not exceed the upper limit of the optimal reaction temperature of the catalyst.

[0102] It should be noted that in the above steps, the PLC controller involves three control relationships: the number of catalytic metal mesh layers, the heating control process, and the constant temperature control process.

[0103] Catalytic metal mesh layer number control: If the CO concentration is less than 1000ppm, the PLC controller will first turn on the first preset number of catalytic metal mesh layers for controlled heating; if the CO concentration is greater than 1000ppm, the PLC controller will turn on the second preset number of catalytic metal mesh layers.

[0104] Heating control process: Based on the smoke parameters (temperature, flow rate) collected by the detection probe and combined with the set target temperature, the output voltage signal value is controlled. Using a 2080 nickel-chromium alloy mesh as the heating element, the following derivation is made: Heat generated by the electric heating of the nickel-chromium alloy mesh = external radiative heat transfer of the nickel-chromium alloy mesh + convective heat transfer between the nickel-chromium alloy mesh and air + increase in the internal energy of the nickel-chromium alloy mesh. The calculation formula includes:

[0105]

[0106] Q 内 =C×M(T) b -T a );

[0107] Q 对流 =h×B×(T) b -T c )×t;

[0108] Q 辐射 =h r ×B×(T b -T c )×t;

[0109]

[0110] Where Q represents the total heat generated by the electric heating of the nickel-chromium alloy mesh; Q内 This indicates an increase in the internal energy of the nickel-chromium alloy mesh; Q 对流 This indicates heat transfer via convection between the nickel-chromium alloy mesh and the air; Q 辐射 This indicates that the nickel-chromium alloy mesh undergoes external radiative heat transfer; h r U represents the radiation heat transfer coefficient; R represents the output voltage signal value; t represents the resistance value; C represents the heating time; M represents the specific heat capacity of the nickel-chromium alloy mesh; T represents the mass of the nickel-chromium alloy mesh. a Indicates the initial ambient (metal) temperature; T b The target temperature is indicated by h; the overall convective heat transfer coefficient is h; the airflow velocity is v; the contact area between the metal mesh and the airflow is B; and the temperature T is T. c denoted by , where ∈ represents the flue gas temperature; ∈ represents the emissivity of nickel-chromium metal 2080, which is 0.75; σ represents the Stefan-Boltzmann constant, which is 5.67 × 10⁻⁶.

[0111] Thermostatic control process: When the heating mesh temperature needs to be maintained at a constant level, the PLC controller adjusts the output voltage signal in a timely manner according to the flue gas temperature and flow rate to control the heating mesh temperature to remain within a constant range. Taking 2080 nickel-chromium alloy mesh as an example, the following derivation is made: The heat generated by the electric heating of the nickel-chromium alloy mesh = radiative heat transfer from the nickel-chromium alloy mesh to the outside + convective heat transfer between the nickel-chromium alloy mesh and the air. The formula is:

[0112]

[0113] Based on the known parameters—the contact area between the metal mesh and the airflow, the set target temperature, the temperature and velocity of the collected flue gas—the output voltage signal value can be adjusted according to the above relationships, and the heating mesh temperature can be controlled in real time. Considering that the electric heating energy cannot be 100% converted, it is more appropriate for the overall electric heating power to be 125% of the theoretically calculated value.

[0114] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A CO catalytic purification device for fire smoke, characterized in that, include: The housing (1) is a hollow structure, and an air inlet is provided at one end of the housing (1); A combined overcurrent catalytic metal mesh (2) is disposed inside the housing (1). The combined overcurrent catalytic metal mesh (2) includes at least two layers of catalytic metal mesh (21), and all the catalytic metal mesh (21) are arranged in parallel. Flue gas dust collector (3), the flue gas dust collector (3) is fixedly disposed between the air inlet of the housing (1) and the combined overcurrent catalytic metal mesh (2); An axial flow fan (4) is fixedly disposed between the air inlet of the casing (1) and the flue gas dust collector (3); and A reaction temperature control system (5) is electrically connected to the combined overcurrent catalytic metal mesh (2) and the axial flow fan (4), respectively. The catalytic metal mesh (21) includes at least two strip metal meshes (211), conductive copper sheets (212), and conductive contacts (213). Adjacent strip metal meshes (211) are fixedly connected by conductive copper sheets (212) and form a serpentine arrangement. The conductive contacts (213) are fixedly connected to the two outermost strip metal meshes (211) respectively. The combined overcurrent catalytic metal mesh (2) further includes a heat-resistant insulating plate grid (22), which cooperates with the catalytic metal mesh (21). Each layer of the catalytic metal mesh (21) is fixedly disposed between two layers of the heat-resistant insulating plate grid (22). The reaction temperature control system (5) includes a gas temperature probe (51), a gas flow rate probe (52), a metal mesh temperature probe (53), a CO concentration probe (54), a PLC controller (55), and an adjustable power supply (56). The PLC controller (55) is electrically connected to the gas temperature probe (51), the gas flow rate probe (52), the metal mesh temperature probe (53), and the adjustable power supply (56). The gas temperature probe (51) and the gas flow rate probe (52) are located between the flue gas dust collector (3) and the combined overcurrent catalytic metal mesh (2). The metal mesh temperature probe (53) is located on the catalytic metal mesh (21). The adjustable power supply (56) is electrically connected to the combined overcurrent catalytic metal mesh (2) and the axial flow fan (4).

2. The CO catalytic purification device for fire flue gas according to claim 1, characterized in that: The housing (1) includes a baffle grille (11) and a metal box (12). The metal box (12) is a hollow structure. An entrance is provided at one end of the metal box (12). The baffle grille (11) cooperates with the entrance of the metal box (12). The baffle grille (11) is detachably installed at the entrance of the metal box (12).

3. The CO catalytic purification device for fire flue gas according to claim 1, characterized in that: The flue gas dust removal box (3) includes a filter screen (31) and an activated carbon box (32) that are fixedly connected to each other. The filter screen (31) is fixedly arranged on one side close to the axial flow fan (4).

4. A method for catalytic purification of CO in fire smoke, characterized in that, The method uses the CO catalytic purification device for fire smoke according to any one of claims 1-3, and the method includes: Acquire first information and second information. The first information is the physical parameters of the area to be purified, including the size of the site and material properties. The second information is the fire smoke development data collected from the on-site fire pre-experiment. Based on the first information, dynamic simulation processing is performed to generate a preliminary simulation dataset by simulating fire conditions under different working conditions. Based on the second information, the preliminary simulation dataset is optimized to obtain an optimized dataset; The model is constructed based on the optimized dataset. By training and validating the preset neural network model, the relationship between key influencing parameters and fire development is established to obtain the fire smoke situation development model. Real-time sensor data collected on-site is acquired and input into the fire smoke situation development model for prediction processing. The prediction result is obtained by predicting the current CO concentration and the subsequent fire development trend. An optimized device parameter setting scheme is calculated based on the prediction results. The device parameter setting scheme includes the start-up of the axial flow fan, the number of catalytic metal mesh layers, and the temperature setting.

5. The method for catalytic purification of CO in fire flue gas according to claim 4, characterized in that, Based on the first information, dynamic simulation processing is performed to generate a preliminary simulation dataset by simulating fire conditions under different working conditions. Based on the first information, preliminary scene modeling is performed. By modeling the site size and material properties, the dynamic characteristics of fire propagation and smoke flow are simulated using the finite element analysis method to obtain a preliminary fire scene model. Based on the preliminary fire scene model, fluid dynamics simulation was performed. The movement and diffusion of smoke in the fire scene were simulated by computational fluid dynamics algorithm. Combined with working conditions of different wind speeds, temperature gradients and fire source intensities, a preliminary smoke flow dataset was obtained. Fire development status analysis is performed based on the preliminary flue gas flow dataset. By applying time series analysis and state transition model, combined with the actual combustion rate and flue gas composition changes, the fire status changes at different time points are analyzed to obtain dynamic data on fire development. The simulation results are integrated and processed based on the dynamic data of fire development. By integrating the fluid dynamics results and state transition analysis results, a preliminary simulation dataset is generated.

6. The method for catalytic purification of CO in fire flue gas according to claim 4, characterized in that, Based on the second information, the preliminary simulation dataset is optimized to obtain an optimized dataset, including: Based on the pre-experimental data of the actual fire, the model parameters were adjusted. By comparing the preliminary simulation dataset with the fire smoke situation data, the least squares optimization algorithm was used to adjust the combustion efficiency and heat release rate in the fire model, and the improved fire model parameters were obtained. Sensitivity analysis is performed based on the improved model parameters. The influence of each input parameter on the fire state and flue gas characteristics output is evaluated by a global sensitivity analysis algorithm. The parameter with the greatest impact on the model results is identified, and the sensitivity analysis results are obtained. Based on the sensitivity analysis results, data regression processing was performed. By using a multiple linear regression model, the relationship between key influencing parameters and flue gas concentration and temperature was fitted to obtain an optimized mathematical model. The optimized mathematical model is used to perform dataset augmentation processing, and new sample data is generated based on the existing preliminary simulation dataset to obtain the optimized dataset.

7. The method for catalytic purification of CO in fire flue gas according to claim 4, characterized in that, Based on the optimized dataset, a model is constructed. By training and validating a pre-set neural network model, the relationship between key influencing parameters and fire development is established to obtain a fire smoke situation development model, including: Feature selection processing is performed on the optimized dataset. By applying a recursive feature elimination algorithm, the impact of each feature on the fire development is evaluated, and features with less impact on model performance are gradually removed to obtain a simplified feature set. Based on the simplified feature set, a neural network model is constructed. A multi-layer feedforward neural network is designed, and the ReLU activation function and mean squared error loss function are configured to establish a preliminary neural network model. The model is trained based on the preliminary neural network model. The model is trained iteratively by using the input features of the optimized dataset and the corresponding fire development output. The model weights are adjusted to minimize the loss function, and the trained neural network model is obtained. The trained neural network model is validated by using cross-validation to assess its generalization ability and comparing the error between the prediction results and the actual fire development to obtain a fire smoke development model.

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