Self-adaptive air volume adjusting method and system for dust removal tail end

Abstract

The invention discloses a self-adaptive air volume adjusting method and system for a dust removal tail end. The method comprises the steps that the real-time smoke dust emission condition of a dust source is obtained; real-time analysis, judgment and signal output of smoke dust collection air volume are carried out through a smoke dust diffusion flow field algorithm and a dust hood collection flow field algorithm built in the end processor; the air volume of a dust suction port is adaptively adjusted based on a control signal through an adaptive dust removal system tail end device, and the method comprises the steps that the adaptive dust removal system tail end device monitors the actual air volume in a flue in real time, and the opening degree of a valve body is automatically adjusted according to the received control signal, so that the air volume of the dust suction port reaches the optimal target air volume value; feeding back and evaluating the control effect, namely judging whether the dust control requirement is met or not according to the real-time emission condition of the smoke dust obtained in real time, and if so, entering stable operation and continuously monitoring; if not, the second step and the third step are repeatedly executed to adjust the self-adaptive dust removal system tail end device. The invention further discloses a corresponding system, electronic equipment and a computer readable storage medium.

Description

Technical Field

[0001] This invention relates to the field of industrial ventilation and dust removal technology, specifically to an adaptive airflow adjustment method and system for dust removal terminals. Background Technology

[0002] Industrial production processes involve numerous points where pollutants are generated and emitted, such as blast furnace tapholes and converter tapholes. Pollutant emissions are intermittent and fluctuate significantly with different production processes. Throughout the emission process, peak emissions are 5-10 times the average, while the duration of these peaks is less than 10% of the total emission time. Furthermore, emissions are affected by changes in production operating parameters and material properties, leading to sudden fluctuations in emission rates. These characteristics result in fluctuating demands on dust collection systems throughout the production process. Insufficient airflow at the end of the dust collection system will cause particulate matter spillage and failure to meet environmental standards, while excessive airflow will lead to over-extraction and increased energy consumption of the dust collection system.

[0003] To address the aforementioned issues, current dust collection systems adjust the exhaust volume at the system's terminal by regulating the opening of dampers or adjusting the operating frequency / speed of the fans, thus matching the volume to the properties of the dust source. The relevant existing technologies are described below: Chinese patent application CN202310135168.2 (A digital debugging technology for ventilation systems combined with BIM models) discloses a digital debugging technology for ventilation systems combined with BIM models. By using computer modeling and collecting and processing the data of the system, the operation of the data model can provide a preliminary prediction of the operating status of the ventilation system, providing a reference for monitoring the operating status of the ventilation system and improving the system's regulation efficiency by 25%. Chinese patent application CN202311071704.3 (A Variable Air Volume Regulating Valve) discloses a variable air volume regulating valve that adjusts the air volume by using a limit adjustment method with a rod and a plate, and improves the sealing performance after the valve is closed by setting an annular rubber ring and a sealing gasket to reduce the air leakage rate. Chinese patent application CN202311071698.1 (A Novel Variable Air Volume Regulating Valve) discloses a novel variable air volume regulating valve that uses a push-pull self-locking mechanism to precisely limit the valve plate, so that the valve plate will not shift when the wind force is too strong, thus achieving precise variable air volume regulation and improving sealing performance. Chinese patent application CN202320800745.0 (An Intelligent Constant Air Volume Regulating Valve) discloses an intelligent constant air volume regulating valve that uses an external electric transmission mechanism to drive a screw to adjust the internal pressure plate up and down, thereby regulating the air volume and solving the problem of difficult maintenance caused by the regulating mechanism being located inside the pipeline.

[0004] However, the aforementioned existing technologies are limited to air volume adjustment and cannot solve the problem of excessive ventilation or energy waste caused by dust source fluctuations. Furthermore, these adjustment methods are based on known operating signals or timed operation control logic set according to the historical status of dust emissions. The adjustment methods are basically fixed and it is difficult to respond to changes in the dust source in a timely manner. Summary of the Invention

[0005] The purpose of this invention is to provide an adaptive airflow adjustment method and system for dust removal terminals. By using image recognition and flow field analysis technology, the terminal device of the adaptive dust removal system can be adjusted in real time to match the airflow required by the dust emission status of the dust source, thereby achieving optimal airflow matching under the premise of dust control. This solves the problem in the prior art of how dust removal systems can identify changes in pollution and adjust the terminal airflow accordingly.

[0006] A first aspect of the present invention is to provide an adaptive airflow adjustment method for a dust removal terminal, comprising: S1, Obtain the real-time emission status of smoke and dust from the dust source, wherein the real-time emission status of smoke and dust includes smoke and dust diffusion data and production data; S2, based on the smoke and dust diffusion data and production data, the smoke and dust diffusion flow field algorithm and the dust collection hood capture flow field algorithm built into the terminal processor are used to perform real-time analysis, judgment and control signal output of the smoke and dust capture air volume; S3, the air volume of the suction port is adaptively adjusted based on the control signal by the terminal device of the adaptive dust removal system, including: the terminal device of the adaptive dust removal system monitors the actual air volume in the flue in real time, and automatically adjusts the valve opening according to the received control signal so that the air volume of the suction port reaches the optimal target air volume value. S4, feedback and evaluation of the control effect, including: determining whether the dust control requirements are met based on the real-time emission status of the smoke and dust obtained in S1; if the dust control requirements are met, stable operation is entered and continuous monitoring is performed; if the dust control requirements are not met, steps S2 and S3 are repeated to adjust the terminal device of the adaptive dust removal system so that the control effect reaches the predetermined target.

[0007] Preferably, S1 includes: S11, acquire smoke and dust diffusion data based on image visual recognition, wherein the smoke and dust diffusion data includes the real-time diffusion range, diffusion direction, diffusion intensity and diffusion speed of smoke and dust at different times; S12, acquire production data based on data acquisition method, wherein the production data includes production signals and dust source location information.

[0008] Preferably, S11 includes: Multiple high-definition industrial cameras are installed around the dust source to cover the main area of ​​dust diffusion, wherein the high-definition industrial cameras are connected to the end processor via a network; Multiple high-definition industrial cameras are activated to acquire multiple video streams and images, and the multiple video streams and image data are preprocessed. The preprocessing includes denoising, enhancing and calibrating the acquired video streams to eliminate illumination changes and background interference, smoothing the image data using Gaussian filtering and median filtering, and extracting the smoke and dust movement area using background subtraction. The preprocessed video stream and image data are fused, and the fused data is subjected to multiple corresponding feature extraction algorithms to obtain the real-time diffusion range, diffusion direction, diffusion intensity, and diffusion speed of the smoke and dust at different times; including: The smoke and dust boundaries are identified using an edge detection algorithm, the pixel area covered by the smoke and dust is calculated, and then converted into the actual physical area as the diffusion range by combining camera calibration parameters. Based on the optical flow method, the motion vectors of smoke and dust pixels in consecutive frames are analyzed to generate a smoke and dust movement direction field. The direction of the smoke and dust movement direction field is represented by an angle, and the dominant direction is statistically used as the diffusion direction. The smoke concentration is estimated based on grayscale value analysis, and the total volume of smoke is calculated by combining the pixel area as the diffusion intensity; wherein the diffusion intensity is divided into three levels: low, medium and high based on the grayscale value threshold. Furthermore, the data fusion of the preprocessed video stream and image data includes fusing the preprocessed video stream and images using Kalman filtering to improve measurement accuracy; S12 includes acquiring production data based on industrial automation and Internet of Things technologies, including: The production signals are acquired in real time from the PLC of the production equipment, including equipment start / stop status, operating speed, output, and process parameters; the production data is transmitted to the end processor via Modbus or OPC UA protocol. For dynamic dust sources, the movement of the dust source equipment is tracked by RFID or UWB positioning systems, and the dust source coordinates are marked on a GIS map to obtain the location information of the dynamic dust source; for static dust sources, the location information of the static dust source is fixed by preset coordinates. The production data and image data are timestamped to ensure real-time performance, and the terminal processor establishes a data buffer that is updated every 100ms.

[0009] Preferably, S2 includes: S21, Based on the smoke and dust diffusion flow field algorithm, determine the diffusion parameters, which include the smoke and dust emission status and trajectory; wherein, the smoke and dust diffusion flow field algorithm is based on a simplified computational fluid dynamics model to simulate the diffusion behavior of smoke and dust in the air; S22, Based on the dust hood capture flow field algorithm, determine the optimal air volume required for the dust hood to achieve the set smoke and dust capture efficiency; wherein, the dust hood capture flow field algorithm is based on Bernoulli's equation and empirical formulas to calculate the air volume requirement of the dust hood; S23, based on the smoke emission status and movement trajectory, and the optimal airflow output control signal required for the dust collection hood to achieve the set smoke collection efficiency, includes: the end processor outputting a control signal to the adaptive dust removal system terminal device, the control signal including the optimal target airflow value. And the control command for the valve body opening degree.

[0010] Preferably, S21 includes: A diffusion model corresponding to the dust diffusion flow field algorithm is established based on the diffusion range, diffusion direction, diffusion intensity, ambient temperature, ambient humidity, and airflow velocity. The diffusion model is a Gaussian plume model, which treats the dust as a continuous point source. Based on the diffusion model, the concentration distribution formula of the dust is shown in equation (1): (1); in, This refers to the concentration of smoke and dust, expressed in mg / m³. The emission rate is expressed in mg / s. Wind speed, in m / s. and These are the horizontal and vertical diffusion coefficients. The height of the dust source, These are the three-dimensional coordinates of the smoke and dust. The concentration distribution of the smoke and dust is used to characterize the emission status of the smoke and dust; By using the particle tracking method, the smoke and dust are discretized into particles. Based on the diffusion model, the motion equations are solved to predict the motion trajectory of the smoke and dust. The motion equations are shown in equation (2): (2); in, For particle velocity, For airflow velocity, For particle relaxation time, It is the acceleration due to gravity; The diffusion parameters are recalculated and updated in real time every 200ms, and the diffusion model is corrected in conjunction with the image data.

[0011] Preferably, S22 includes: Based on smoke and dust concentration, diffusion velocity, dust source distance, and dust hood geometry, a collection efficiency model corresponding to the dust hood's collection flow field algorithm is established. This collection efficiency model defines the collection efficiency. Required airflow to achieve the target value The air volume is proportional to the amount of smoke and dust captured. The calculation formula is shown in equation (3): (3); in, Air volume, in m³ / h. This refers to the concentration of smoke and dust, expressed in mg / m³. This refers to the area of ​​the hood opening, in m². This refers to the approach or diffusion velocity of smoke and dust, measured in m / s. This is an empirical coefficient, related to the distance from the dust source, and ranges from 1.2 to 1.5. CFD flow field simulation was used to model the streamlines near the dust hood and determine the critical airflow in the simulation to ensure effective dust extraction. The critical airflow in the simulation was based on the Stokes number of the dust particles. Determined, the Stokes number The calculation formula is shown in equation (4): (4); in, Particle density, The particle diameter is air viscosity, The diameter of the cover opening; when When the value is less than 0.1, the collection efficiency is relatively high; Ensure Stokes number Optimize the airflow with the goal of minimizing energy consumption when the value is less than 0.1. The optimization function is shown in equation (5): (5); in, To achieve the target efficiency, iterative calculations are used to find the efficiency that satisfies the target. The minimum air volume is determined and identified as the optimal target air volume value. .

[0012] Preferably, S3 includes: S31, the terminal device of the adaptive dust removal system monitors the actual air volume in the flue in real time, and monitors the static pressure difference of the flue gas before and after the valve plate in real time through the pressure acquisition mechanism. Based on the static pressure difference of the flue gas before and after the valve plate Calculate the actual air volume As shown in equation (6): (6); in, For valve flow coefficient, The specific gravity of a gas is 1.0; S32, the control signal received by the processor of the valve body control mechanism drives the adjustable multi-hole valve plate to move through the actuator; the valve body opening of the adjustable multi-hole valve plate... The valve opening is linearly related to the air volume, and the PID controller adjusts the valve opening according to equation (7). : (7); in, For air volume error, , , These are the proportional coefficient, integral coefficient, and difference coefficient, respectively.

[0013] Preferably, step S4, which involves obtaining the operational status in real time based on S1, determining whether the dust control requirements are met, and if so, entering stable operation and continuously monitoring, includes: The high-definition industrial camera continuously captures the diffusion of smoke and dust and calculates the residual smoke and dust coverage rate, where: residual smoke and dust coverage rate = percentage of residual area / total area; A laser dust sensor is installed downstream of the dust collection hood, and the laser dust sensor is used to detect the emission concentration (mg / m³). Whether dust control requirements are met is determined based on dust control indicators; wherein the dust control indicators are: residual dust coverage rate ≤ 5% or emission concentration ≤ 10 mg / m³; The determination of whether a system has entered a stable operation is based on a stability judgment criterion; wherein the stability judgment criterion is: data fluctuation of less than 5% within 30 consecutive seconds is considered stable. Based on meeting the dust control requirements, the system enters a stable operation mode, checking data every 10 seconds. If the dust control requirements are not met in step S4, steps S2 and S3 are repeated to adjust the terminal device of the adaptive dust removal system so that the control effect reaches the predetermined target, including: If the dust control requirements are not met, the terminal processor re-executes steps S2 and S3 to adjust the air volume. The cycle of re-executing steps S2 and S3 is 5 seconds, until the control effect reaches the predetermined target. Historical data is recorded and parameters are stored for each adjustment, which is used to optimize algorithms and maintain predictions.

[0014] A second aspect of the present invention provides an adaptive airflow regulation system for a dust removal terminal, for implementing the method of the first aspect, comprising: The real-time emission status data acquisition module is used to acquire the real-time emission status of dust from the dust source (1). The real-time emission status includes dust diffusion data and production data. The real-time emission status data acquisition module includes an image visual recognition module (2) and a production data acquisition module (3). The production data acquisition module (3) is connected to the dust source (1). The terminal processor (4) is used to perform real-time analysis, judgment and control signal output of the smoke and dust collection air volume based on the smoke and dust diffusion data and production data through the built-in smoke and dust diffusion flow field algorithm and the dust collection hood capture flow field algorithm; wherein, the terminal processor (4) is connected to the image vision recognition module (2) and the production data acquisition module (3) respectively. The adaptive dust removal system terminal device (5) is used to adaptively adjust the air volume of the dust suction port based on the control signal. The device includes: placing the adaptive dust removal system terminal device (5) in the flue above the dust source (1), monitoring the actual air volume in the flue in real time, and automatically adjusting the valve opening according to the received control signal so that the air volume of the dust suction port reaches the optimal target air volume value. ; The feedback evaluation module is used to provide feedback and evaluation on the control effect, including: determining whether the dust control requirements are met based on the real-time emission status of the smoke and dust. If the dust control requirements are met, the system will enter stable operation and continue to monitor. If the dust control requirements are not met, the functions of the terminal processor (4) and the adaptive dust removal system terminal device (5) will be repeatedly executed so that the control effect reaches the predetermined target.

[0015] In a preferred embodiment, the adaptive dust removal system terminal device (5) comprises a valve body (51), a fixed perforated valve plate (52), an adjustable perforated valve plate (53), a valve body control mechanism (54), and a pressure acquisition mechanism (55); wherein, the valve body (51) is internally provided with a double-layer valve plate composed of the fixed perforated valve plate (52) and the adjustable perforated valve plate (53), with the fixed perforated valve plate (52) arranged in front and the adjustable perforated valve plate (53) behind along the air inlet direction; the fixed perforated valve plate (52) The size and arrangement of the air holes on the fixed multi-hole valve plate (52) and the adjustable multi-hole valve plate (53) are exactly the same. In the fully open state, the centers of the air holes at the same positions on the fixed multi-hole valve plate (52) and the adjustable multi-hole valve plate (53) coincide. When adjustment is required, the adjustable multi-hole valve plate (53) is pulled up by the valve body control mechanism (54), thereby blocking the air holes of the fixed multi-hole valve plate (52) to reduce the airflow channel area. The cross-sectional area of ​​the double-layer valve plate and the duct flow rate of the flue adopt a constant velocity duct design. The values ​​meet the relevant valve design standards; a set of pressure acquisition holes are respectively provided before and after the double-layer valve plate to collect the static pressure difference of flue gas before and after the valve plate. Each group of pressure acquisition holes has 4-12 holes, all arranged in a ring; the pressure acquisition mechanism (55) is used to transmit the acquired pressure signal to the terminal processor (4) via wireless or wired transmission.

[0016] A third aspect of the present invention provides an electronic device including a processor and a memory, the memory storing a plurality of instructions, the processor being configured to read the instructions and execute the method as described in the first aspect.

[0017] A fourth aspect of the present invention provides a computer-readable storage medium storing a plurality of instructions which can be read by a processor and executed as described in the first aspect.

[0018] The beneficial effects of the method and system of the present invention are as follows: 1) This invention is designed for the characteristics of intermittent or highly fluctuating dust emissions from dust sources. It can acquire and analyze the current pollution status in real time and adjust the air volume of the vents to automatically meet the dust control requirements and ensure the effectiveness of dust control. 2) This invention monitors the emission status and control effect of pollution sources in real time, and controls the air volume to the minimum while meeting the control effect, thereby significantly reducing the energy consumption required for dust control by the system. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the specific embodiments or related technologies of the present invention, the drawings used in the description of the specific embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0020] Figure 1 This is a flowchart of an adaptive airflow adjustment method for a dust removal terminal according to an embodiment of the present invention; Figure 2 This is a flowchart of step S1 of the adaptive airflow adjustment method for a dust removal terminal provided in an embodiment of the present invention; Figure 3 This is a flowchart of step S2 of the adaptive airflow adjustment method for a dust removal terminal provided according to an embodiment of the present invention; Figure 4 This is a flowchart of step S3 of the adaptive airflow adjustment method for a dust removal terminal provided in an embodiment of the present invention; Figure 5 This is a schematic diagram of the adaptive airflow regulation system for dust removal terminals provided in an embodiment of the present invention. Figure 6 This is a structural diagram of the terminal device of the adaptive dust removal system provided in an embodiment of the present invention; Figure 7 This is a structural diagram of an electronic device provided according to an embodiment of the present invention. Detailed Implementation

[0021] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0023] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0024] like Figure 1 As shown, this embodiment provides an adaptive airflow adjustment method for a dust removal terminal, including: S1, obtain the real-time emission status of dust from the dust source (1), the real-time emission status of dust includes dust diffusion data and production data.

[0025] like Figure 2 As shown, in a preferred embodiment, S1 includes: S11, acquire smoke and dust diffusion data based on image visual recognition, wherein the smoke and dust diffusion data includes the real-time diffusion range, diffusion direction, diffusion intensity and diffusion speed of smoke and dust at different times; In this embodiment, step S11 includes acquiring the smoke and dust diffusion data in real time using a high-definition industrial camera and image processing algorithms. The specific process of step S11 is as follows: (1) Install multiple high-definition industrial cameras around the dust source 1 to cover the main diffusion area of ​​the dust source 1, wherein the resolution of the high-definition industrial camera is ≥1080p and the frame rate is ≥30fps. The high-definition industrial camera adopts a dustproof and explosion-proof design and is connected to the terminal processor through a network. (2) Start multiple high-definition industrial cameras to obtain multiple video streams and images and preprocess the multiple video streams and image data. The preprocessing includes denoising, enhancing and calibrating the acquired video streams to eliminate illumination changes and background interference, smoothing the image data with Gaussian filtering and median filtering, and extracting the smoke and dust movement area by background subtraction.

[0026] (3) Perform data fusion on the preprocessed video stream and image data, and use multiple corresponding feature extraction algorithms on the fused data to obtain the real-time diffusion range (m²), diffusion direction (°), diffusion intensity (level), and diffusion velocity (m / s) of the smoke and dust at different times; including: The smoke and dust boundaries are identified using edge detection algorithms (such as the Canny operator), the pixel area covered by the smoke and dust is calculated, and then converted into the actual physical area (unit: m²) based on camera calibration parameters as the diffusion range. Based on optical flow methods (such as the Lucas-Kanade algorithm), the motion vectors of smoke pixels in consecutive frames are analyzed to generate a smoke movement direction field. The direction of the smoke movement direction field is represented by angles (0°~360°), and the dominant direction is statistically used as the diffusion direction. The smoke concentration is estimated based on grayscale value analysis, and the total volume of smoke is calculated based on pixel area as the diffusion intensity; wherein the diffusion intensity is divided into three levels: low, medium and high based on grayscale value threshold.

[0027] In a preferred embodiment, the data fusion of the preprocessed video stream and image data includes fusing the preprocessed video stream and images using Kalman filtering to improve measurement accuracy.

[0028] S12, acquire production data based on data acquisition, wherein the production data includes production signals and dust source location information; In a preferred embodiment, S12 includes acquiring production data based on industrial automation and Internet of Things (IoT) technologies. The specific process of S12 includes: (1) Obtain the real-time production signals from the PLC (Programmable Logic Controller) of the production equipment, wherein the production signals include the equipment start / stop status, running speed (e.g., conveyor belt speed), output (processing volume per unit time) and process parameters (e.g., temperature, pressure); the production data is transmitted to the end processor via Modbus or OPC UA protocol; (2) For dynamic dust sources, the movement of dust source equipment (such as crushers and conveyor belts) is tracked by RFID or UWB positioning system, and the dust source coordinates are marked by GIS map to obtain the dust source location information of dynamic dust sources; for static dust sources, the dust source location information of static dust sources is fixed by preset coordinates. (3) The production data and image data are timestamped to ensure real-time performance. The terminal processor establishes a data buffer and updates it every 100ms.

[0029] S2, based on the smoke and dust diffusion data and production data, the smoke and dust diffusion flow field algorithm and the dust collection hood capture flow field algorithm built into the terminal processor are used to perform real-time analysis, judgment and control signal output of the smoke and dust capture air volume; like Figure 3 As shown, in a preferred embodiment, S2 includes: S21, Determine diffusion parameters based on the smoke and dust diffusion flow field algorithm, the diffusion parameters including smoke and dust emission status and motion trajectory; As a preferred embodiment, the basic principle of the smoke and dust diffusion flow field algorithm is to simulate the diffusion behavior of smoke and dust in the air based on a simplified computational fluid dynamics (CFD) model.

[0030] In a preferred embodiment, S21 includes: (1) A diffusion model corresponding to the dust diffusion flow field algorithm is established based on the diffusion range, diffusion direction, diffusion intensity, ambient temperature, ambient humidity and airflow velocity. The diffusion model is a Gaussian plume model, and the dust is regarded as a continuous point source. Based on the diffusion model, the concentration distribution formula of the dust is as shown in Equation (1): (1); in, This refers to the concentration of smoke and dust, expressed in mg / m³. The emission rate is expressed in mg / s. Wind speed, in m / s. and These are the horizontal and vertical diffusion coefficients. The height of the dust source, These are the three-dimensional coordinates of the smoke and dust. The concentration distribution of the smoke and dust is used to characterize the emission status of the smoke and dust; (2) By using the particle tracking method, the smoke and dust are discretized into particles. Based on the diffusion model, the motion equations are solved to predict the motion trajectory of the smoke and dust. The motion equations are shown in equation (2): (2); in, For particle velocity, For airflow velocity, For particle relaxation time, This is the acceleration due to gravity.

[0031] (3) The diffusion parameters are recalculated and updated in real time every 200ms, and the diffusion model is corrected in combination with the image data.

[0032] S22, Based on the dust hood capture flow field algorithm, determine the optimal air volume required for the dust hood to achieve the set smoke and dust capture efficiency; As a preferred embodiment, the basic principle of the dust hood capture flow field algorithm is to calculate the air volume requirement of the dust hood based on Bernoulli's equation and empirical formulas.

[0033] In a preferred embodiment, S22 includes: (1) Based on the dust concentration, diffusion velocity, dust source distance, and dust hood geometry (such as hood opening area and shape), establish a collection efficiency model corresponding to the dust hood collection flow field algorithm. The collection efficiency model defines the collection efficiency. Required airflow to achieve the target value (typically ≥95%) The air volume is proportional to the amount of smoke and dust captured. The calculation formula is shown in equation (3): (3); in, Air volume, in m³ / h. This refers to the concentration of smoke and dust, expressed in mg / m³. This refers to the area of ​​the hood opening, in m². This refers to the approach or diffusion velocity of smoke and dust, measured in m / s. This is an empirical coefficient, related to the distance from the dust source, and is typically 1.2 to 1.5.

[0034] (2) CFD is used to simulate the flow field near the dust hood and determine the critical airflow in the flow field simulation to ensure that the smoke and dust are effectively sucked in. The critical airflow in the flow field simulation is based on the Stokes number of the smoke and dust particles. Determined, the Stokes number The calculation formula is shown in equation (4): (4); in, Particle density, The particle diameter is air viscosity, The diameter of the cover opening; when When the value is less than 0.1, the capture efficiency is relatively high.

[0035] (3) Ensure Stokes number Optimize the airflow with the goal of minimizing energy consumption when the value is less than 0.1. The optimization function is shown in equation (5): (5); in, To achieve the target efficiency, iterative calculations are used to find the efficiency that satisfies the target. The minimum air volume is determined and identified as the optimal target air volume value. ; S23, the optimal airflow output control signal based on the smoke emission status and movement trajectory, and the dust collection efficiency required for the dust collection hood to achieve the set smoke collection efficiency; In a preferred embodiment, S23 includes: the end processor outputting a control signal (4-20mA or digital signal) to the end device of the adaptive dust removal system, the control signal including the optimal target airflow value. And the control command for the valve body opening degree.

[0036] S3, the adaptive dust removal system terminal device adaptively adjusts the airflow at the suction port based on the control signal, including: the adaptive dust removal system terminal device monitors the actual airflow in the flue in real time, and automatically adjusts the valve opening according to the received control signal, so that the airflow at the suction port reaches the optimal target airflow value. ; like Figure 4 As shown, in a preferred embodiment, S3 includes: S31, the terminal device of the adaptive dust removal system monitors the actual air volume in the flue in real time, and monitors the static pressure difference of the flue gas before and after the valve plate in real time through the pressure acquisition mechanism. (Pa), and based on the static pressure difference of the flue gas before and after the valve plate. Calculate the actual air volume As shown in equation (6): (6); in, For valve flow coefficient, The specific gravity of a gas is 1.0; S32, the control signal received by the processor of the valve body control mechanism drives the adjustable multi-hole valve plate to move through the actuator; in this embodiment, the actuator adopts a stepper motor or pneumatic device with an accuracy of ±1%; the valve body opening of the adjustable multi-hole valve plate... (0%~100%) has a linear relationship with the air volume, and the PID controller adjusts the valve opening according to equation (7). : (7); in, For air volume error, , , These are the proportional coefficient, integral coefficient, and difference coefficient, respectively.

[0037] In this embodiment, the response time from signal reception to stable airflow is ≤2s, which is a fast adjustment speed and meets the adjustment requirements.

[0038] S4, feedback and evaluation of the control effect, including: determining whether the dust control requirements are met based on the real-time emission status of the smoke and dust obtained in S1; if the dust control requirements are met, stable operation is entered and continuous monitoring is performed; if the dust control requirements are not met, steps S2 and S3 are repeated to adjust the terminal device of the adaptive dust removal system so that the control effect reaches the predetermined target.

[0039] In a preferred embodiment, step S4, which involves obtaining the operational status in real time based on S1, determining whether the dust control requirements are met, and if so, entering stable operation and continuously monitoring, includes: The high-definition industrial camera continuously captures the diffusion of smoke and dust and calculates the residual smoke and dust coverage rate, where: residual smoke and dust coverage rate = percentage of residual area / total area; A laser dust sensor is installed downstream of the dust collection hood, and the laser dust sensor is used to detect the emission concentration (mg / m³). Whether dust control requirements are met is determined based on dust control indicators; wherein the dust control indicators are: residual dust coverage rate ≤ 5% or emission concentration ≤ 10 mg / m³; The determination of whether a system has entered a stable operation is based on a stability judgment criterion; wherein the stability judgment criterion is: data fluctuation of less than 5% within 30 consecutive seconds is considered stable. Based on meeting the dust control requirements, the system enters a stable operation mode, checking data every 10 seconds.

[0040] In a preferred embodiment, if the dust control requirements are not met in step S4, steps S2 and S3 are repeated to adjust the terminal device of the adaptive dust removal system so that the control effect reaches the predetermined target, including: If the dust control requirements are not met, the terminal processor re-executes steps S2 and S3 to adjust the air volume. The cycle of re-executing steps S2 and S3 is 5 seconds, until the control effect reaches the predetermined target. Historical data is recorded and parameters are stored for each adjustment, which is used to optimize algorithms and maintain predictions.

[0041] The second aspect of this embodiment provides an adaptive airflow regulation system for a dust removal terminal, comprising: The real-time emission status data acquisition module for smoke and dust is used to acquire the real-time emission status of smoke and dust from dust source 1. The real-time emission status of smoke and dust includes smoke and dust diffusion data and production data. The real-time emission status data acquisition module for smoke and dust includes an image visual recognition module 2 and a production data acquisition module 3. The production data acquisition module 3 is connected to the dust source 1. The terminal processor 4 is used to perform real-time analysis, judgment and control signal output of the smoke and dust collection air volume based on the smoke and dust diffusion data and production data, through the built-in smoke and dust diffusion flow field algorithm and dust collection hood capture flow field algorithm; wherein, the terminal processor 4 is connected to the image vision recognition module 2 and the production data acquisition module 3 respectively; The adaptive dust removal system terminal device 5 is used to adaptively adjust the airflow at the dust suction port based on the control signal. This includes: placing the adaptive dust removal system terminal device 5 inside the flue above the dust source 1; monitoring the actual airflow in the flue in real time; and automatically adjusting the valve opening according to the received control signal to achieve the optimal target airflow value at the dust suction port. ; The feedback and evaluation module is used to provide feedback and evaluation on the control effect, including: determining whether the dust control requirements are met based on the real-time emission status of the smoke and dust; if the dust control requirements are met, the system enters stable operation and is continuously monitored; if the dust control requirements are not met, the functions of the terminal processor 4 and the adaptive dust removal system terminal device 5 are repeatedly executed to ensure that the control effect reaches the predetermined target.

[0042] In a preferred embodiment, the adaptive dust removal system terminal device 5 comprises a valve body 51, a fixed perforated valve plate 52, an adjustable perforated valve plate 53, a valve body control mechanism 54, and a pressure acquisition mechanism 55. The valve body 51 contains a double-layer valve plate formed by the fixed perforated valve plate 52 and the adjustable perforated valve plate 53, with the fixed perforated valve plate 52 positioned in front and the adjustable perforated valve plate 53 behind along the air inlet direction. The size and arrangement of the air holes on the fixed and adjustable perforated valve plates 52 and 53 are identical. In the fully open state, the centers of the air holes at the same positions on the fixed and adjustable perforated valve plates 52 and 53 coincide. When adjustment is required, the adjustable perforated valve plate 53 is pulled upwards by the valve body control mechanism 54, thereby blocking the air holes of the fixed perforated valve plate 52 to reduce the airflow channel area. The cross-sectional area of ​​the double-layer valve plate and the duct flow rate of the flue are designed using a constant velocity duct system. The values ​​meet the relevant valve design standards; a set of pressure acquisition holes are respectively provided before and after the double-layer valve plate to collect the static pressure difference of flue gas before and after the valve plate. Each group of pressure acquisition holes has 4-12 holes, all arranged in a ring; the pressure acquisition mechanism 55 is used to transmit the acquired pressure signal to the terminal processor 4 via wireless or wired transmission.

[0043] The present invention also provides a memory that stores multiple instructions for implementing the method as described in Embodiment 1.

[0044] like Figure 7 As shown, the present invention also provides an electronic device, including a processor 301 and a memory 302 connected to the processor 301. The memory 302 stores a plurality of instructions, which can be loaded and executed by the processor to enable the processor to perform methods as described in Embodiments 2 and 3.

[0045] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. An adaptive airflow adjustment method for a dust collector terminal, characterized in that, include: S1, Obtain the real-time emission status of smoke and dust from the dust source, wherein the real-time emission status of smoke and dust includes smoke and dust diffusion data and production data; S2, based on the smoke and dust diffusion data and production data, the smoke and dust diffusion flow field algorithm and the dust collection hood capture flow field algorithm built into the terminal processor are used to perform real-time analysis, judgment and control signal output of the smoke and dust capture air volume; S3, the air volume of the suction port is adaptively adjusted based on the control signal by the terminal device of the adaptive dust removal system, including: the terminal device of the adaptive dust removal system monitors the actual air volume in the flue in real time, and automatically adjusts the valve opening according to the received control signal so that the air volume of the suction port reaches the optimal target air volume value. S4, feedback and evaluation of the control effect, including: determining whether the dust control requirements are met based on the real-time emission status of the smoke and dust obtained in S1; if the dust control requirements are met, stable operation is entered and continuous monitoring is performed; if the dust control requirements are not met, steps S2 and S3 are repeated to adjust the terminal device of the adaptive dust removal system so that the control effect reaches the predetermined target.

2. The adaptive airflow adjustment method for a dust collector terminal according to claim 1, characterized in that, S1 includes: S11, acquire smoke and dust diffusion data based on image visual recognition, wherein the smoke and dust diffusion data includes the real-time diffusion range, diffusion direction, diffusion intensity and diffusion speed of smoke and dust at different times; S12, acquire production data based on data acquisition method, wherein the production data includes production signals and dust source location information.

3. The adaptive airflow adjustment method for a dust collector terminal according to claim 2, characterized in that, S11 includes: Multiple high-definition industrial cameras are installed around the dust source (1) to cover the main diffusion area of ​​the dust source (1), wherein the high-definition industrial cameras are connected to the end processor via a network; Multiple high-definition industrial cameras are activated to acquire multiple video streams and images, and the multiple video streams and image data are preprocessed. The preprocessing includes denoising, enhancing and calibrating the acquired video streams to eliminate illumination changes and background interference, smoothing the image data using Gaussian filtering and median filtering, and extracting the smoke and dust movement area using background subtraction. The preprocessed video stream and image data are fused, and the fused data is subjected to multiple corresponding feature extraction algorithms to obtain the real-time diffusion range, diffusion direction, diffusion intensity, and diffusion speed of the smoke and dust at different times; including: The smoke and dust boundaries are identified using an edge detection algorithm, the pixel area covered by the smoke and dust is calculated, and then converted into the actual physical area as the diffusion range by combining camera calibration parameters. Based on the optical flow method, the motion vectors of smoke and dust pixels in consecutive frames are analyzed to generate a smoke and dust movement direction field. The direction of the smoke and dust movement direction field is represented by an angle, and the dominant direction is statistically used as the diffusion direction. The smoke concentration is estimated based on grayscale value analysis, and the total volume of smoke is calculated by combining the pixel area as the diffusion intensity; wherein the diffusion intensity is divided into three levels: low, medium and high based on the grayscale value threshold. Furthermore, the data fusion of the preprocessed video stream and image data includes fusing the preprocessed video stream and images using Kalman filtering to improve measurement accuracy; S12 includes acquiring production data based on industrial automation and Internet of Things technologies, including: The production signals are acquired in real time from the PLC of the production equipment, including equipment start / stop status, operating speed, output, and process parameters; the production data is transmitted to the end processor via Modbus or OPC UA protocol. For dynamic dust sources, the movement of the dust source equipment is tracked by RFID or UWB positioning systems, and the dust source coordinates are marked on a GIS map to obtain the location information of the dynamic dust source; for static dust sources, the location information of the static dust source is fixed by preset coordinates. The production data and image data are timestamped to ensure real-time performance, and the terminal processor establishes a data buffer that is updated every 100ms.

4. The adaptive airflow adjustment method for a dust collector terminal according to claim 3, characterized in that, S2 includes: S21, Based on the smoke and dust diffusion flow field algorithm, determine the diffusion parameters, which include the smoke and dust emission status and trajectory; wherein, the smoke and dust diffusion flow field algorithm is based on a simplified computational fluid dynamics model to simulate the diffusion behavior of smoke and dust in the air; S22, Based on the dust hood capture flow field algorithm, determine the optimal air volume required for the dust hood to achieve the set smoke and dust capture efficiency; wherein, the dust hood capture flow field algorithm is based on Bernoulli's equation and empirical formulas to calculate the air volume requirement of the dust hood; S23, based on the smoke emission status and movement trajectory, and the optimal airflow output control signal required for the dust collection hood to achieve the set smoke collection efficiency, includes: the end processor outputting a control signal to the adaptive dust removal system terminal device, the control signal including the optimal target airflow value. And the control command for the valve body opening degree.

5. The adaptive airflow adjustment method for a dust collector terminal according to claim 4, characterized in that, S21 includes: A diffusion model corresponding to the dust diffusion flow field algorithm is established based on the diffusion range, diffusion direction, diffusion intensity, ambient temperature, ambient humidity, and airflow velocity. The diffusion model is a Gaussian plume model, which treats the dust as a continuous point source. Based on the diffusion model, the concentration distribution formula of the dust is shown in equation (1): （1）； in, This refers to the concentration of smoke and dust, expressed in mg / m³. The emission rate is expressed in mg / s. Wind speed, in m / s. and These are the horizontal and vertical diffusion coefficients. The height of the dust source, These are the three-dimensional coordinates of the smoke and dust. The concentration distribution of the smoke and dust is used to characterize the emission status of the smoke and dust; By using the particle tracking method, the smoke and dust are discretized into particles. Based on the diffusion model, the motion equations are solved to predict the motion trajectory of the smoke and dust. The motion equations are shown in equation (2): （2）； in, For particle velocity, For airflow velocity, For particle relaxation time, It is the acceleration due to gravity; The diffusion parameters are recalculated and updated in real time every 200ms, and the diffusion model is corrected in conjunction with the image data.

6. The adaptive airflow adjustment method for a dust collector terminal according to claim 5, characterized in that, S22 includes: Based on smoke and dust concentration, diffusion velocity, dust source distance, and dust hood geometry, a collection efficiency model corresponding to the dust hood's collection flow field algorithm is established. This collection efficiency model defines the collection efficiency. Required airflow to achieve the target value The air volume is proportional to the amount of smoke and dust captured. The calculation formula is shown in equation (3): （3）； in, Air volume, in m³ / h. This refers to the concentration of smoke and dust, expressed in mg / m³. This refers to the area of ​​the hood opening, in m². This refers to the approach or diffusion velocity of smoke and dust, measured in m / s. This is an empirical coefficient, related to the distance from the dust source, and ranges from 1.2 to 1.

5. CFD flow field simulation was used to model the streamlines near the dust hood and determine the critical airflow in the simulation to ensure effective dust extraction. The critical airflow in the simulation was based on the Stokes number of the dust particles. Determined, the Stokes number The calculation formula is shown in equation (4): （4）； in, Particle density, The particle diameter is air viscosity, The diameter of the cover opening; when When the value is less than 0.1, the collection efficiency is relatively high; Ensure Stokes number Optimize the airflow with the goal of minimizing energy consumption when the value is less than 0.

1. The optimization function is shown in equation (5): （5）； in, To achieve the target efficiency, iterative calculations are used to find the efficiency that satisfies the target. The minimum air volume is determined and identified as the optimal target air volume value. .

7. The adaptive airflow adjustment method for a dust collector terminal according to claim 6, characterized in that, S3 includes: S31, the terminal device of the adaptive dust removal system monitors the actual air volume in the flue in real time, and monitors the static pressure difference of the flue gas before and after the valve plate in real time through the pressure acquisition mechanism. Based on the static pressure difference of the flue gas before and after the valve plate Calculate the actual air volume As shown in equation (6): （6）； in, For valve flow coefficient, The specific gravity of a gas is 1.0; S32, the control signal received by the processor of the valve body control mechanism drives the adjustable multi-hole valve plate to move through the actuator; the valve body opening of the adjustable multi-hole valve plate... The valve opening is linearly related to the air volume, and the PID controller adjusts the valve opening according to equation (7). : （7）； in, For air volume error, , , These are the proportional coefficient, integral coefficient, and difference coefficient, respectively.

8. The adaptive airflow adjustment method for a dust collector terminal according to claim 7, characterized in that, The step S4, which involves obtaining the real-time operating status from S1 and determining whether the dust control requirements are met, then proceeding to stable operation and continuous monitoring, includes: The high-definition industrial camera continuously captures the diffusion of smoke and dust and calculates the residual smoke and dust coverage rate, where: residual smoke and dust coverage rate = percentage of residual area / total area; A laser dust sensor is installed downstream of the dust collection hood, and the laser dust sensor is used to detect the emission concentration (mg / m³). Whether dust control requirements are met is determined based on dust control indicators; wherein the dust control indicators are: residual dust coverage rate ≤ 5% or emission concentration ≤ 10 mg / m³; The determination of whether a system has entered a stable operation is based on a stability judgment criterion; wherein the stability judgment criterion is: data fluctuation of less than 5% within 30 consecutive seconds is considered stable. Based on meeting the dust control requirements, the system enters a stable operation mode, checking data every 10 seconds. If the dust control requirements are not met in step S4, steps S2 and S3 are repeated to adjust the terminal device of the adaptive dust removal system so that the control effect reaches the predetermined target, including: If the dust control requirements are not met, the terminal processor re-executes steps S2 and S3 to adjust the air volume. The cycle of re-executing steps S2 and S3 is 5 seconds, until the control effect reaches the predetermined target. Historical data is recorded and parameters are stored for each adjustment, which is used to optimize algorithms and maintain predictions.

9. An adaptive airflow regulation system for a dust removal terminal, used to implement the method according to any one of claims 1-8, characterized in that: include: The real-time emission status data acquisition module is used to acquire the real-time emission status of dust from the dust source (1). The real-time emission status includes dust diffusion data and production data. The real-time emission status data acquisition module includes an image visual recognition module (2) and a production data acquisition module (3). The production data acquisition module (3) is connected to the dust source (1). The terminal processor (4) is used to perform real-time analysis, judgment and control signal output of the smoke and dust collection air volume based on the smoke and dust diffusion data and production data through the built-in smoke and dust diffusion flow field algorithm and the dust collection hood capture flow field algorithm; wherein, the terminal processor (4) is connected to the image vision recognition module (2) and the production data acquisition module (3) respectively. The adaptive dust removal system terminal device (5) is used to adaptively adjust the air volume of the dust suction port based on the control signal. The device includes: placing the adaptive dust removal system terminal device (5) in the flue above the dust source (1), monitoring the actual air volume in the flue in real time, and automatically adjusting the valve opening according to the received control signal so that the air volume of the dust suction port reaches the optimal target air volume value. ; The feedback evaluation module is used to provide feedback and evaluation on the control effect, including: determining whether the dust control requirements are met based on the real-time emission status of the smoke and dust. If the dust control requirements are met, the system will enter stable operation and continue to monitor. If the dust control requirements are not met, the functions of the terminal processor (4) and the adaptive dust removal system terminal device (5) will be repeatedly executed so that the control effect reaches the predetermined target.

10. The adaptive airflow regulation system for a dust removal terminal according to claim 9, characterized in that, The adaptive dust removal system terminal device (5) consists of a valve body (51), a fixed perforated valve plate (52), an adjustable perforated valve plate (53), a valve body control mechanism (54), and a pressure acquisition mechanism (55). The valve body (51) contains a double-layer valve plate composed of the fixed perforated valve plate (52) and the adjustable perforated valve plate (53). Along the air inlet direction, the fixed perforated valve plate (52) is positioned in front, and the adjustable perforated valve plate (53) is positioned behind. The size and arrangement of the air holes on the adjustable perforated valve plate (53) are exactly the same. In the fully open state, the centers of the air holes at the same positions on the fixed perforated valve plate (52) and the adjustable perforated valve plate (53) coincide. When adjustment is required, the adjustable perforated valve plate (53) is pulled upward by the valve body control mechanism (54), thereby blocking the air holes of the fixed perforated valve plate (52) to reduce the airflow channel area. The cross-sectional area of ​​the double-layer valve plate and the duct flow rate of the flue are designed with constant velocity air duct. The values ​​meet the relevant valve design standards; a set of pressure acquisition holes are respectively provided before and after the double-layer valve plate to collect the static pressure difference of flue gas before and after the valve plate. Each group of pressure acquisition holes has 4-12 holes, all arranged in a ring; the pressure acquisition mechanism (55) is used to transmit the acquired pressure signal to the terminal processor (4) via wireless or wired transmission.

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