Intelligent ventilation cabinet and control system thereof

Abstract

The invention relates to the technical field of automatic control, in particular to an intelligent ventilation cabinet and a control system thereof, and the system comprises a pollution trend identification module, a trend deviation judgment module, a pre-control response setting module, a risk weight rearrangement module and a linkage trigger mechanism module. According to the invention, through correlation analysis and abrupt change feature extraction of pollution monitoring point concentration data, accurate tracking of a pollution diffusion trend and dynamic positioning of a boundary space position are realized, angle conversion is completed by combining a space proportion of a boundary and an air valve, and a driving signal is generated. The opening degree of the air valve can be adjusted in real time according to the pollution diffusion speed and the air speed change, meanwhile, efficient distribution of ventilation resources is achieved by combining priority dynamic rearrangement, a control signal is automatically triggered at a key node, and air valve state switching is completed. The pollution change identification precision, the space control sensitivity, the linkage response coordination and the ventilation efficiency are effectively improved, and the risks of uneven resource distribution, air exchange delay and local environment imbalance are reduced.

Description

Technical Field

[0001] This invention relates to the field of automatic control technology, and in particular to an intelligent fume hood and its control system. Background Technology

[0002] Automatic control technology is an important branch of the intersection of information technology and mechatronics. Its core lies in achieving stable, efficient, and safe system operation through real-time monitoring and adjustment of process parameters such as temperature, pressure, flow rate, and speed. This technology encompasses several key aspects, including sensor information acquisition, actuator control strategies, control logic programming, and system feedback adjustment. It is widely used in industrial production, building automation, traffic control, environmental monitoring, and many other scenarios, playing a fundamental supporting role, especially in intelligent manufacturing and green energy conservation. Automatic control systems typically rely on embedded controllers, PLCs, or computer-based control platforms, combined with specific control algorithms to perform closed-loop or open-loop control of target equipment. Traditional fume hood control systems refer to the control methods used in laboratory or industrial environments to remove harmful gases and regulate airflow. They primarily address technical aspects such as ventilation efficiency control, safety interlock mechanism management, and airflow detection inside and outside the hood. Traditional fume hood control typically employs mechanical or relay logic control methods, adjusting fan operation status through timed or manual adjustments, supplemented by wind speed sensors for simple alarms or activation linkages. However, it is difficult to automatically match ventilation modes according to real-time operating conditions, the control logic relies on fixed parameter settings, and the system's scalability is limited.

[0003] Existing technologies use fixed parameters and passive logic for control. When there are significant fluctuations in the spatial distribution of pollution concentration, they lack the ability to perceive dynamic changes in pollution boundaries and cannot effectively identify diffusion paths and offset trends. This results in insufficient matching between damper adjustment and pollution changes, a lack of adjustment mechanisms based on real-time spatial conditions for ventilation control, limited response speed, and the inability to dynamically update priority ranking with changes in operating conditions. In scenarios of sudden pollution diffusion or localized accumulation and aggravation, this can easily lead to unreasonable damper opening, delayed air exchange, and a decrease in the overall utilization rate of ventilation resources. Summary of the Invention

[0004] To address the technical problems existing in the prior art, embodiments of the present invention provide an intelligent fume hood and its control system. The technical solution is as follows: On the one hand, an intelligent fume hood and its control system are provided, the system including: The pollution trend identification module collects the concentration of monitoring points in the main exhaust channel and the side intake zone, extracts three sets of continuous points, judges concentration abrupt changes, constructs spatial change paths, marks the coordinates of the largest abrupt change, and generates a set of pollution boundary line locations. The trend offset judgment module, based on the pollution boundary line location set, compares the boundary line coordinates of the continuous monitoring period, calculates the distance difference between the boundary and the center of the air valve, analyzes whether the direction is consistent, records the vector and measures the offset, and generates boundary offset vector information. The pre-control response setting module calculates the angle by converting the boundary distance ratio based on the direction and magnitude of the boundary offset vector information and the opening range of the air valve, outputs the air valve drive signal, and obtains the pre-response angle command. The risk weight rearrangement module, based on the pre-response angle command, wind speed, and concentration growth rate, adjusts the control priority and generates a priority response ranking list if the concentration growth rate is faster than the wind speed. The linkage triggering mechanism module determines the distance between the nearest point in the priority response sorting list and the pollution boundary line location set. If the distance reaches the warning range, it triggers the air valve to open fully and outputs an intelligent fume hood control signal.

[0005] As a further embodiment of the present invention, the pollution boundary line location set includes the coordinates of the maximum abrupt change point, spatial change path nodes, and boundary line boundary point coordinates; the boundary offset vector information includes the boundary direction vector, boundary offset distance, and boundary center position; the pre-response angle command includes the target angle value, damper control parameters, and drive output signal; the priority response sorting list includes the response priority, sorting sequence number, and corresponding control strategy; and the intelligent fume hood control signal includes the full-open command, linkage control signal, and early warning trigger status.

[0006] As a further aspect of the present invention, the concentration mutation is defined as the concentration change exceeding a set threshold in three consecutive monitoring points.

[0007] As a further aspect of the present invention, the definition of the opening range of the air valve refers to the adjustable opening angle range of the air valve.

[0008] As a further aspect of the present invention, the warning range is defined as the minimum safe distance threshold between the pollution boundary line and the air valve.

[0009] As a further aspect of the present invention, the pollution trend identification module includes: The concentration data extraction submodule collects the pollution concentration monitoring points set up in the main exhaust duct section and the side intake guide area, extracts three sets of continuous points in the order of arrangement, obtains the pollution concentration value corresponding to each set of points, forms three sets of ternary pollution data sequences, and generates a set of continuous point concentration values. The difference fluctuation judgment submodule calculates the concentration difference between the same numbered points in the first group and the second group, and between the second group and the third group, based on the continuous point concentration value set, obtains two sets of difference sequences, calculates the increase in the difference between corresponding points and compares it with the concentration change judgment threshold, extracts the points where the increase changes, and obtains the concentration change position sequence. The boundary line coordinate calibration submodule locates the index coordinates of the mutation points in the monitoring layout map according to the concentration mutation location sequence, calls the layout coordinate information to extract the corresponding spatial location, selects the point with the largest mutation amplitude as the spatial turning reference point, records the coordinates of all mutation points one by one, and generates a pollution boundary line location set.

[0010] As a further aspect of the present invention, the trend offset determination module includes: The boundary change extraction submodule extracts the coordinates of periodic boundary points based on the pollution boundary line location set and converts them into a unified coordinate format. It then calculates the geometric center position of the boundary within the period and generates a set of periodic boundary center coordinates. The center distance calculation submodule obtains the Euclidean distance between the center point of the cycle and the center coordinates of the damper based on the set of center coordinates of the cycle boundary, calculates the distance difference sequence between adjacent cycles, and obtains the boundary center offset. The spatial offset output submodule determines whether the angle between the boundary center movement direction and the valve direction is less than a direction threshold based on the boundary center offset. If the condition is met, the boundary center vector difference is calculated and recorded as a spatial vector to generate boundary offset vector information.

[0011] As a further aspect of the present invention, the pre-control response setting module includes: The damper parameter extraction submodule obtains the direction consistency result and offset amplitude value in the boundary offset vector information, calls the damper structure parameter table, extracts the opening amplitude range and position reference ratio corresponding to the current damper, establishes the damper control boundary, and generates the damper control parameter set. The angle conversion submodule calculates the linear relationship between the offset value and the control ratio of the valve based on the valve position ratio range of the valve control parameters and the offset distance in the boundary offset vector information. The result is then input into the angle conversion sequence to obtain the valve angle conversion result. The response signal generation submodule extracts the corresponding air valve number based on the air valve angle conversion result and calls the drive channel encoder to convert the angle value into a drive signal. It then combines the period identifier with the air valve control channel data, outputs control commands, and generates a pre-response angle command.

[0012] As a further aspect of the present invention, the risk weight rearrangement module includes: The rate of change extraction submodule calls the pre-response angle command, wind speed monitoring data and pollution concentration monitoring data to obtain the wind speed change amplitude and pollution concentration growth rate value at the time point corresponding to the current air valve angle, calculates the average rate of change within the period, and generates the pollution wind speed change rate. The proportional relationship judgment submodule calculates the proportional coefficient between the pollution concentration increase value and the wind speed increase value in the pollution wind speed change rate. If the proportional value is greater than the pollution response threshold proportional standard, the pollution response priority is determined to be higher than the wind speed response, and the priority judgment result is obtained. The response list generation submodule adjusts the position of pollution control associated instructions in the task sorting list based on the priority judgment result. If the priority is high, it will be moved to the first position of the task, and the task order data structure will be reorganized to generate a priority response sorting list.

[0013] As a further aspect of the present invention, the linkage triggering mechanism module includes: The boundary distance calculation submodule obtains the first instruction item in the priority response sorting list and the location set of the pollution boundary line, extracts the coordinates of the point closest to the air valve in the boundary line and calls the air valve location coordinates, calculates the Euclidean distance value between the two, and generates the boundary distance measurement value. The condition comparison and verification submodule compares the measured boundary distance value with the set early warning activation boundary distance threshold to determine whether the current distance is less than the threshold. If the threshold is met, a control transition flag is generated to obtain the joint control trigger judgment result. Based on the joint control trigger judgment result being in the start state, the joint control signal output submodule replaces the pre-response control state with the air valve fully open command, combines the air valve number with the control status code to form a control command signal data packet, and generates an intelligent fume hood control signal.

[0014] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following: By analyzing the correlation of pollution monitoring point concentrations and extracting abrupt change characteristics, the system achieves accurate tracking of pollution diffusion trends and dynamic boundary positioning. Combining the spatial ratio between the boundary and the air valve, it completes angle conversion and outputs drive signals, enabling the air valve opening to be adjusted in real time according to changes in pollution diffusion speed and wind speed. Combined with dynamic priority rearrangement, it achieves efficient allocation of ventilation resources. At key nodes, it triggers control signals to complete the air valve state switching, effectively improving pollution identification accuracy, spatial control sensitivity, linkage response coordination, and ventilation efficiency, while reducing resource waste and the risk of local air imbalance. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a system schematic diagram of the present invention; Figure 2 This is a schematic diagram of the system framework of the present invention; Figure 3 This is a flowchart of the pollution trend identification module in this invention; Figure 4 This is a flowchart of the trend offset judgment module in this invention; Figure 5 This is a flowchart of the pre-control response setting module in this invention; Figure 6 This is a flowchart of the risk weight rearrangement module in this invention; Figure 7 This is a flowchart of the linkage triggering mechanism module in this invention. Detailed Implementation

[0017] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0018] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0019] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, their intended meanings are consistent. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, their intended meanings are consistent.

[0020] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0021] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0022] This invention provides an intelligent fume hood and its control system, such as... Figure 1-2 The diagram shown is of an intelligent fume hood. The system includes: The pollution trend identification module collects the concentration values ​​of pollution concentration monitoring points arranged in the main exhaust duct section and the side air intake guide area. It extracts three sets of continuous points according to the arrangement of the points, judges the degree of change in concentration difference between adjacent two sets, constructs the spatial change path of concentration based on the magnitude of change, marks the location of the maximum change and records the corresponding coordinates, and generates a set of pollution boundary line locations. The trend offset judgment module obtains the boundary coordinate change information of the pollution boundary line location set in two consecutive monitoring cycles, calculates the Euclidean distance difference between the boundary center point and the center of the air valve, extracts the continuous cycle difference results for trend analysis, and judges whether the boundary direction is consistent with the air valve direction. If they are consistent, the vector value is recorded and the degree of spatial offset is measured to form boundary offset vector information. The pre-control response setting module obtains the opening range of the current air valve structure based on the direction consistency judgment result and the offset amplitude value in the boundary offset vector information, inputs the ratio of the air valve position to the boundary distance into the angle conversion sequence, outputs the angle conversion value and converts it into an air valve drive action signal, and obtains the pre-response angle command. The risk weight rearrangement module calls the pre-response angle command, the monitored wind speed change magnitude and the pollution concentration growth rate value, compares the change ratio between the current wind speed value growth rate and the concentration change value, and if the concentration growth is faster than the wind speed increase, it determines that the pollution control priority needs to be upgraded and adds it to the first position of the sorting list to generate a priority response sorting list. The linkage triggering mechanism module determines whether the air valve is within the early warning activation boundary range based on the current first priority response sorting result and the measured value of the nearest point in the pollution boundary location. If the linkage conditions are met, the air valve is triggered to switch from the pre-response state to the full-open command process, and an intelligent fume hood control signal is output.

[0023] The pollution boundary location set includes the coordinates of the maximum abrupt change point, spatial change path nodes, and boundary point coordinates. The boundary offset vector information includes the boundary direction vector, boundary offset distance, and boundary center position. The pre-response angle command includes the target angle value, damper control parameters, and drive output signal. The priority response sorting list includes the response priority, sorting sequence number, and corresponding control strategy. The intelligent fume hood control signals include the full-open command, linkage control signal, and early warning trigger status.

[0024] Specifically, such as Figure 2 , 3 As shown, the pollution trend identification module includes: The concentration data extraction submodule collects the pollution concentration monitoring points set up in the main exhaust duct section and the side intake guide area, extracts three sets of continuous points in the order of arrangement, obtains the pollution concentration value corresponding to each set of points, forms three sets of ternary pollution data sequences, and generates a set of continuous point concentration values. Before collecting pollution concentration monitoring data from the main exhaust duct section and the side intake guide zone, the concentration data extraction submodule first needs to determine the sensor numbering order and distribution density in each area according to the layout diagram. For example, if 10 monitoring points are set up in the main exhaust duct section, numbered P1 to P10 sequentially from the air inlet to the air outlet, and 6 monitoring points are set up in the side intake guide zone, numbered S1 to S6 from the point closest to the main exhaust outlet, the real-time concentration sampling values ​​of each monitoring point are read and uniformly aligned to form a structured dataset of time-location-concentration. Then, three sets of continuous points are extracted from the sorted points according to the set extraction method. Taking P1 to P5 as an example, three sets of continuous points are extracted according to the point sequence. The first set is P1, The first group consists of P2 and P3, the second group consists of P2, P3, and P4, and the third group consists of P3, P4, and P5. The pollution concentration values ​​of the three points in each group are retrieved from the dataset and combined into a triplet concentration set. During the operation, the extraction step size can be set to 1, 2, or a higher integer. If the step size is set to 2, the three groups of points are P1, P2, P3; P3, P4, P5; and P5, P6, P7, respectively. Changing the step size adjusts the extraction coverage. After extraction, the concentration values ​​of the three points in each group form an independent sequence. For example, the first group is 1.10, 1.20, and 1.30; the second group is 1.20, 1.30, and 1.25; and the third group is 1.30, 1.25, and 1.15. Finally, a continuous set of point concentration values ​​is constructed for subsequent analysis.

[0025] The difference fluctuation judgment submodule is based on the continuous point concentration value set. It calculates the concentration difference between the first group and the second group, and between the second group and the third group of the same number points, respectively, obtains two sets of difference sequences, calculates the difference increase between the corresponding points and compares it with the concentration change judgment threshold, extracts the increase change points, and obtains the concentration change position sequence. The difference fluctuation judgment submodule is based on the three sets of extracted ternary pollution concentration data. It performs difference calculations on the concentration values ​​of the same serial number points in the first and second groups, and the second and third groups respectively. In the calculation, the concentration of the points at the same position in the three groups needs to be compared one by one. For example, if the first point in the first and second groups is 1.10 and 1.20, the difference is calculated to be 0.10. Then, the second point is compared with 1.20 and 1.30, and the difference is 0.10. The third point is 1.30 and 1. The difference is found to be 0.05, forming the first set of differences. Then, the points with the same index in the second and third sets are compared sequentially. For example, the first point (1.20 vs. 1.30) has a difference of 0.10, the second point (1.30 vs. 1.25) has a difference of 0.05, and the third point (1.25 vs. 1.15) has a difference of 0.10, forming the second set of differences. After obtaining two sets of differences, the fluctuation range of the differences at corresponding positions is compared, and the absolute change between adjacent differences is calculated. If the difference between the first and second groups is 0.10 and 0.10 respectively, the fluctuation increase at that point is 0. If the second group is 0.10 and the third group is 0.05, the fluctuation increase at that point is 0.05. This operation is performed sequentially to identify points with abnormal fluctuations. Next, a comparison is made based on the concentration mutation judgment threshold. The threshold is preset and is set based on the historical concentration fluctuation data of the monitoring area over the past month. The average value and maximum fluctuation range of the concentration difference sequence are calculated. For example, if the average concentration difference between consecutive adjacent monitoring points over the past month is 0.08 and the maximum fluctuation is 0.22, then the threshold can be set to 80% of the maximum fluctuation, i.e., 0.176, as the mutation judgment benchmark value. When the fluctuation increase of a certain point exceeds 0.18, it is marked as a mutation point. In the above example, if the fluctuation increase of a certain comparison point is 0.22, it is determined to be a mutation point, and its position in the point sequence is recorded. Finally, a concentration mutation location sequence is formed for location.

[0026] The boundary line coordinate calibration submodule locates the index coordinates of the mutation points on the monitoring layout map according to the concentration mutation location sequence, calls the layout coordinate information to extract the corresponding spatial location, selects the point with the largest mutation amplitude as the spatial turning reference point, records the coordinates of all mutation points one by one, and generates a pollution boundary line location set. Upon receiving the sequence of abrupt change locations, the boundary line coordinate calibration submodule first retrieves the spatial coordinates corresponding to each abrupt change location based on the one-to-one mapping between monitoring points and coordinates on the layout map. For example, if the abrupt change location is numbered P3, its three-dimensional spatial coordinates are extracted based on the location information of sensor P3 on the layout map, such as (x=8.0m, y=2.5m, z=3.0m). This mapping relationship is pre-generated into a coordinate index table by importing data from the layout map, facilitating rapid retrieval of the corresponding coordinates for each number. The spatial coordinate information of each abrupt change location is extracted sequentially, and all abrupt change locations are then calibrated. The coordinates are summarized. During the process of recording the coordinate set, it is also necessary to compare the fluctuation increase of each mutation point and identify the point with the largest fluctuation value as the key reference point of the pollution boundary line. For example, if the mutation points are recorded as P3, P4, and P5, and their corresponding increase values ​​are 0.18, 0.25, and 0.20, then P4 is selected as the reference point, and its coordinates are (x=10.0m, y=3.0m, z=3.2m). Finally, the coordinate set corresponding to all mutation points is output, and the coordinates of the largest mutation point are marked as the spatial turning reference point of the boundary line, thus completing the generation of the pollution boundary line location set.

[0027] Specifically, such as Figure 2 , 4 As shown, the trend deviation judgment module includes: The boundary change extraction submodule extracts the coordinates of periodic boundary points based on the pollution boundary line location set, converts them into a unified coordinate format, calculates the geometric center position of the boundary within the period, and generates a set of periodic boundary center coordinates. The boundary change extraction submodule, based on the pollution boundary line location set, needs to segment and organize the pollution boundary line location data according to a preset time period before execution. Specifically, it extracts the timestamp information of each point on each boundary line and divides the data into independent periodic segments according to the set sampling period. For example, if the period length is set to 10 minutes, the pollution boundary point set formed within each 10-minute period is grouped into a periodic boundary point set. In each period, the spatial coordinate information of all pollution boundary points is extracted from this set and uniformly converted into a three-dimensional spatial coordinate format. The format unification process must ensure that all point data is output in (x, y, z) format. If the original data is in two-dimensional plane coordinates or local coordinate system coordinates, coordinate system transformation processing is required in conjunction with sensor deployment drawings and calibration information. For example, the two-dimensional coordinates (5.0, 3.0) of a point in the local coordinate system are converted into global three-dimensional coordinates (15.0, 9.0, 0.0) using a set scaling ratio. For example, after converting the reference origin offset, and unifying the coordinate format of all period points, the geometric center position of the boundary of each period is calculated for the boundary point set of each period. The calculation process involves calling the x, y, and z coordinate values ​​of all points within the period, averaging them, that is, summing all x values ​​and dividing by the number of points to obtain the x-axis center position. The y and z axes are calculated similarly. In actual operation, if there are 6 boundary points in a certain period, namely (12, 3, 2), (13, 3, 2), (... The x-axis center values ​​of (12+13+14+13+12+11) / 6=12.5, the y-axis center value is 4.0, and the z-axis center value is 2.0. Therefore, the geometric center position is (12.5, 4.0, 2.0). This value is recorded as the coordinate of the boundary center of this period. All period boundary point data are processed in sequence to finally generate a set of period boundary center coordinates containing multiple period center positions.

[0028] The center distance calculation submodule is based on the periodic boundary center coordinate set. It obtains the Euclidean distance between the periodic center point and the valve center coordinates, calculates the distance difference sequence between adjacent periods, and obtains the boundary center offset. After obtaining the center coordinate set of the cycle boundary, the center distance calculation submodule needs to read the center point coordinates cycle by cycle and calculate the spatial distance between them and the center position of the damper. The damper center coordinates are preset to fixed values, such as (10.0, 5.0, 2.0). After reading the three-dimensional coordinates of the center point for each cycle, it calculates the spatial offset values ​​of the center point relative to the damper center in the x, y, and z directions. The coordinate differences in these three directions are used as the basic quantity for calculating the distance. The Euclidean distance value is obtained by taking the square of each difference, summing them, and then taking the square root. For example, if the center of a certain cycle is (12.0, 4.0, 2.0), the offset in the x direction is +2.0 meters, in the y direction is -1.0 meters, and in the z direction is 0. The distance between the center point of each cycle and the center of the air valve is recorded, with a corresponding distance value of 2.24 meters. The distance between the center point of each cycle and the center of the air valve is recorded and summarized to obtain the distance sequence between the center of the cycle and the center of the air valve. Then, the difference between the distances of adjacent cycles is extracted, that is, the difference between the distance values ​​of the current cycle and the previous cycle is calculated to obtain the center offset during the cycle. For example, the distance sequence from cycle 1 to cycle 5 is [2.0, 2.3, 2.5, 2.7, 2.4] meters, then the adjacent difference sequence is [0.3, 0.2, 0.2, -0.3] meters. This difference sequence directly reflects the movement range and direction of the boundary center in the continuous cycle, forming a boundary center offset dataset, which provides input data basis for subsequent determination of the spatial offset direction.

[0029] The spatial offset output submodule determines whether the angle between the boundary center movement direction and the valve direction is less than the direction threshold based on the boundary center offset. If the condition is met, the boundary center vector difference is calculated and recorded as a spatial vector to generate boundary offset vector information. After receiving the boundary center offset data, the spatial offset output submodule first determines whether the angle between the boundary center movement direction and the valve direction is less than a preset direction threshold. During execution, it first calculates the direction vector of the center point for each cycle. That is, by comparing the coordinate difference between the current cycle center point and the previous cycle center point, the movement direction vector of the boundary center is obtained. For example, if the center point of the previous cycle is (11.0, 5.0, 2.0) and the center point of the current cycle is (12.0, 6.0, 2.0), then its direction vector is (+1.0, +1.0, 0.0). The valve direction is preset to a fixed upward vector, for example, set to (+1.0, +2.0, 0.0). The angle between the two vectors is determined by the formula for the angle between three-dimensional coordinate vectors. The direction angle value is calculated. If the direction angle is less than the direction threshold, the offset action is recorded. The direction threshold is set according to the control offset angle range allowed by the design of the air valve. Generally, the value is set between 30 and 45 degrees according to the structural layout and wind direction adjustment characteristics. The middle value, such as 35 degrees, is used for judgment. That is, when the angle between the boundary movement direction and the direction of the air valve is less than 35 degrees, it is considered to be the same direction. The vector difference recording operation is continued. The actual offset vector of the boundary center is recorded and saved in periodic order. For example, if the current vector is (+1.0, +1.0, 0.0), the three-dimensional vector is saved as the boundary offset vector of the current period. All periodic offset data that meet the angle judgment condition are processed in this way to finally form the boundary offset vector information sequence.

[0030] Specifically, such as Figure 2 , 5 As shown, the pre-control response setting module includes: The damper parameter extraction submodule obtains the direction consistency result and offset amplitude value in the boundary offset vector information, calls the damper structure parameter table, extracts the opening amplitude range and position reference ratio corresponding to the current damper, establishes the damper control boundary, and generates the damper control parameter set. The damper parameter extraction submodule obtains the direction consistency result and offset amplitude value from the boundary offset vector information. During execution, it first iterates through the offset vector records for each cycle, reading the direction consistency field. This field is a Boolean type, indicating whether the boundary movement direction and the damper direction meet the set angle threshold requirement. For example, the currently set direction threshold is 35 degrees. This threshold is set based on the damper structure's response capability and the allowable deflection angle of the on-site wind flow. Typically, half of the damper mechanism's maximum responsive angle is used as the judgment benchmark. If the designed damper's maximum response direction angle is 70 degrees, then the angle threshold can be set to 35 degrees. After obtaining the cycle record with "yes" direction consistency, it retrieves the corresponding offset amplitude value. This value is the actual three-dimensional spatial offset distance between the boundary center within the cycle and the previous cycle. Subsequently, it calls the damper structure parameter table, which stores the unique number of each damper and its structural parameter information, including the damper's maximum openable angle, minimum openable angle, and the current mechanical position ratio of the damper blades. The parameters include the control dead zone and position response resolution. For example, for valve number V03, the maximum angle is 90 degrees, the minimum is 10 degrees, the control ratio range is [0.2, 0.8], and the unit control step size is 0.05. Then, the control ratio range of this valve is used as the current response range, and a range matching operation is performed with the boundary offset amplitude. During the matching process, it is necessary to determine whether the current offset amplitude is within the preset controllable range. The preset boundary offset range is usually set to 0.5 meters to 2.0 meters. This range is determined by the actual exhaust channel layout size and the pollutant movement rate. If the current cycle offset amplitude is 1.2 meters, it is located in the middle of the responsive range. Based on the position ratio within the range, the mapping relationship between it and the valve control ratio can be estimated, and a linkage boundary between the boundary movement amplitude and the valve control displacement is established. Finally, the control boundary within this cycle is generated under the current valve number, and the valve control parameter set is generated, which includes information such as valve number, direction consistency, offset amplitude, lower and upper limits of control ratio, and response cycle number.

[0031] The angle conversion submodule calculates the linear relationship between the offset value and the control ratio of the air valve based on the air valve position ratio range in the air valve control parameter set and the offset distance in the boundary offset vector information. The result is then input into the angle conversion sequence to obtain the air valve angle conversion result. After receiving the set of control parameters for the damper, the angle conversion submodule first reads the damper position ratio range contained in each set of parameters. This range is used to calibrate the adjustment capability of the damper under controlled conditions. For example, the control ratio range for damper number V03 is 0.2 to 0.8, indicating that the effective control range achievable by the damper blades from closed to fully open is 20% to 80%. The physical angle corresponding to this ratio value is calculated by interpolation using the difference between the maximum and minimum angles set in the structural parameter table. Subsequently, the module extracts the actual offset distance value recorded by the boundary offset vector in the current cycle and establishes a linear mapping relationship between this offset distance and the damper control ratio based on the preset boundary offset response range. If the boundary response range is set to 0.5 meters to 2.0 meters, then with an offset value of 1.2 meters, the corresponding damper control ratio is 0.48. Next, this ratio value is mapped to the damper control angle range for conversion. Taking a damper with a maximum angle of 90 degrees and a minimum angle of 10 degrees as an example, the calculated control angle is 48.4 degrees. This angle represents the target opening value that the valve should achieve under the current boundary movement range. The system will perform this conversion calculation in all cycles and bind the results with the valve number to form a complete set of valve angle conversion results.

[0032] The response signal generation submodule extracts the corresponding air valve number based on the air valve angle conversion result and calls the drive channel encoder to convert the angle value into a drive signal. It combines the period identifier with the air valve control channel data, outputs control commands, and generates a pre-response angle command. After obtaining the valve angle conversion result, the response signal generation submodule further processes it to generate executable control commands. First, it extracts the valve number and converted angle value item by item from the angle conversion result. Then, it calls the built-in drive channel encoder, which contains the correspondence between the valve and the control channel, and the conversion relationship between angle commands and control signals. For example, valve number V03 corresponds to control channel number CH03, which can receive angle control signals. The conversion rules are set according to the valve's structural drive characteristics. If the valve uses a stepper motor drive, each angle corresponds to a certain number of drive pulses. The damper's resolution is set to 1 degree corresponding to 10 control pulses. Therefore, when the current converted angle is 52.4 degrees, 524 drive pulses should be output. This conversion relationship has been configured in the encoder. Then, the damper number, control channel number, and the converted control signal value are combined to form a control command frame. At the same time, the current cycle number is packaged as a control identifier. For example, if the current cycle is 38, the command frame contains the cycle number 38, the damper number V03, the control channel CH03, and the control signal 524. This command frame is recorded and output to the control command bus, and finally, a pre-response angle command for the damper operation in the next cycle is generated.

[0033] Specifically, such as Figure 2 , 6 As shown, the risk weight rearrangement module includes: The rate of change extraction submodule calls the pre-response angle command, wind speed monitoring data and pollution concentration monitoring data to obtain the wind speed change amplitude and pollution concentration growth rate value at the time point corresponding to the current air valve angle, calculates the average rate of change within the period, and generates the pollution wind speed change rate. First, determine the time period corresponding to the pre-response angle command based on the cycle number. For example, cycle number 36 corresponds to 11:00 to 11:05. Then, extract the wind speed readings for this time period from the wind speed monitoring data. If monitoring point A records a wind speed of 2.8 m / s at 11:00 and 3.5 m / s at 11:05, the wind speed change is calculated to be 0.7 m / s. Next, extract the pollution concentration data for the same monitoring point within the same time period. If the concentration is 0.95 mg / m³ at 11:00 and 1.30 mg / m³ at 11:05, the concentration increase is 0.35 mg / m³. Finally, analyze the wind speed change and pollution concentration increase values. Dividing by the period length (5 minutes here), we get a wind speed change rate of 0.14 m / s / min and a pollution concentration increase rate of 0.07 mg / m³ / min. This calculation process requires that all monitoring values ​​come from the same monitoring point and that the sampling time is strictly aligned. This operation is repeated for each period. The sampling frequency of wind speed and pollution value in the data should be consistent. If there is an inconsistency in the interval, the data needs to be linearly interpolated before the difference is extracted. The wind speed change rate and pollution concentration increase rate obtained in all periods are recorded as one item in the pollution wind speed change rate set. Finally, the result set with the structure {period number: wind speed change rate, pollution concentration increase rate} is obtained.

[0034] The proportional relationship judgment submodule calculates the proportional coefficient between the increase value of pollution concentration and the increase value of wind speed in the rate of change of pollution wind speed. If the proportional value is greater than the pollution response threshold proportional standard, the pollution response priority is determined to be higher than the wind speed response, and the priority judgment result is obtained. Based on data from the pollution wind speed change rate set, the ratio of the pollution concentration growth rate to the wind speed growth rate is calculated sequentially for each cycle. Specifically, the two rate values ​​corresponding to the current cycle are retrieved. For example, in cycle 37, the pollution concentration growth rate is 0.09 mg / m³ / min, and the wind speed growth rate is 0.05 m / s / min; therefore, the ratio is calculated to be 1.8. This ratio represents the relative intensity of pollution change compared to wind speed change. Subsequently, this ratio needs to be compared with a set pollution response threshold standard. This threshold standard is set with reference to the environmental control response level classification results for pollution changes, and in conjunction with the damper opening response efficiency and pipeline... The inertial hysteresis effect is set to 1.4. This value means that when the rate of change of pollution concentration exceeds 1.4 times the rate of change of wind speed, pollution control should be prioritized. The threshold setting process is based on the statistical analysis of historical data over a period of time. The average proportion of concentration change caused by wind speed change is 1.2. After considering a certain error coefficient, the threshold is set to 1.4. The proportion calculated in the current period is 1.8, which is greater than the threshold. Therefore, it is determined that the pollution response priority is higher than the wind speed response in this period, and it is marked as pollution priority. This judgment result is recorded together with the period number and processed sequentially in all periods to finally obtain the set of response priority judgment results for each period.

[0035] The response list generation submodule adjusts the position of pollution control associated instructions in the task sorting list based on the priority judgment result. If the priority is high, it will be moved to the first position of the task, and the task order data structure will be reorganized to generate a priority response sorting list. After obtaining the priority judgment results for all cycles, the task sorting list is dynamically adjusted. First, the initial task structure for the current cycle is read from the task scheduling list according to the cycle number. This structure typically arranges operation items such as wind speed adjustment, pollution control, and equipment inspection in sequence. If the original task order for cycle 38 is [wind speed adjustment → pollution control → filter inspection], then if the priority judgment result for this cycle is pollution priority, a position adjustment operation is performed. In this operation, the original index position of the pollution control task is first located, and then it is determined whether it is lower than other tasks. If there are tasks with lower priority at the front, then... The task exchange process is performed, for example, moving the pollution control task from index 1 to index 0. After the exchange, the position of each task in the sequence is renumbered, the task list index field is updated, and a new task order is formed as [pollution control → wind speed adjustment → filter inspection]. The task list is marked as adjusted. If the judgment result of a certain period is wind speed priority or no difference, the task order is not adjusted and the original structure remains unchanged. This judgment and structure adjustment operation is performed in all periods, and finally a set of response task sorting list arranged by period is formed, which contains the adjusted task order, period number and task content information for each period.

[0036] Specifically, such as Figure 2 , 7 As shown, the linkage triggering mechanism module includes: The boundary distance calculation submodule obtains the first instruction item in the priority response sorting list and the location set of the pollution boundary line, extracts the coordinates of the point closest to the air valve in the boundary line and calls the air valve location coordinates, calculates the Euclidean distance value between the two, and generates the boundary distance measurement value. The process retrieves the first instruction in the priority response sorting list and the pollution boundary location set. First, it reads the instruction at the top of the task sorting list for the current cycle. This instruction is typically generated by the preceding priority judgment module and identifies the valve number corresponding to the controlled object. For example, the task item points to valve number FV_05. Next, it calls the pollution boundary location set to extract the 3D coordinates of all boundary points in the current cycle, forming a point location list. Each point location is recorded in (x, y, z) format. For example, the boundary point locations are (13.5, 5.5, 2.0), (12.8, 4.9, 2.0), (11.0, 4.2, 2.0), etc. Then, it calls the coordinates of the corresponding installation location of valve FV_05, for example, (10.0, 5.0, 2.0), and executes each point in the pollution boundary point set. The spatial distance calculation operation between the line and the valve coordinates is performed by calculating the numerical differences between each point and the valve coordinates in the x, y, and z directions. These differences are then squared, summed, and squared to extract the three-dimensional straight-line distance from each boundary point to the valve. For example, for the point (11.0, 4.2, 2.0) and the valve (10.0, 5.0, 2.0), the x-axis difference is 1.0 meter, the y-axis difference is 0.8 meters, and the z-axis difference is 0 meters, resulting in a distance of approximately 1.28 meters. This operation is performed on all boundary point locations, and the results are recorded. Finally, the smallest distance is selected from all the obtained distances and determined as the closest distance between the pollution boundary and the valve. The corresponding point coordinates are recorded as the "nearest pollution point," and this minimum distance value is used as the boundary distance measurement value for subsequent conditional comparison operations.

[0037] The condition comparison and verification submodule compares the measured boundary distance value with the set early warning start boundary distance threshold to determine whether the current distance is less than the threshold. If the threshold is met, a control transition flag is generated to obtain the joint control trigger judgment result. First, the minimum boundary distance value calculated in the previous submodule is called, for example, this value is 1.28 meters. Then, the preset boundary distance threshold in the parameter configuration file is called. This threshold is determined based on the pollution diffusion speed, the damper response lag time, and the physical channel safety margin in the actual ventilation scenario. The specific setting process is as follows: combining the time required for pollutants to propagate from the boundary line to the damper in historical data, assuming a maximum diffusion speed of 0.4 meters / minute and a response delay of 2 minutes, and considering a redundancy safety factor of 0.1 meters, the threshold can be set to 0.9 meters. This value represents that if the pollution boundary distance to the damper is less than 0.28 meters, the threshold will be set to 0.9 meters. If the distance is 0.9 meters, pollutants may reach the air valve area in the next cycle, entering a high-risk state. Therefore, during the comparison, it is determined whether the boundary distance value of 1.28 meters is less than 0.9 meters. If the result is yes, the joint control flag is not triggered. If the boundary distance value is less than or equal to 0.9 meters, a control transition flag is generated. The flag is assigned the value of "starting state", usually represented by a Boolean value of 1. If the condition is not met, it is assigned the value of 0. The flag will serve as the triggering basis for the air valve control output, ensuring that the switching preparation is completed before the actual pollution approaches the critical value, and finally outputting the joint control trigger judgment result for this cycle.

[0038] The joint control signal output submodule, based on the joint control trigger judgment result being in the start state, replaces the pre-response control state with the air valve fully open command, combines the air valve number with the control status code to form a control command signal data packet, and generates an intelligent fume hood control signal; First, read the angle value set by the damper in the pre-response control state of the current cycle and the corresponding damper number. For example, the current pre-response angle of damper FV_05 is 60 degrees. If the judgment result is a joint control trigger state, that is, the status flag is 1, then execute the instruction overwrite operation, replacing all the original pre-response angle values ​​with the maximum opening angle supported by the damper. The maximum angle information comes from the damper structure parameter table. For example, the maximum opening angle of FV_05 is 90 degrees, so the updated control state is set to 90 degrees, and the status type is marked as "forced full open". Then, the damper number and control... The control angle is encoded and bound, and the control channel configuration table is called to find the control channel identifier corresponding to the air valve FV_05, for example, CH_05. Then, the instruction signal content is generated. This instruction signal contains four fields: cycle number, air valve number, target angle and channel identifier. It is encapsulated in an identification format to form a control signal data packet. For example, if the cycle number is 43, the instruction is: cycle 43+FV_05+CH_05+90 degrees. Finally, this data packet is sent to the execution unit as a ventilation linkage control signal to complete the generation of the intelligent fume hood control signal for the current cycle.

[0039] 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. An intelligent fume hood, characterized in that, The fume hood includes a cabinet body, a fan, an operating console, a cabinet door, and a main unit. The fume hood is equipped with an intelligent fume hood control system, which includes: The pollution trend identification module collects the concentration of monitoring points in the main exhaust channel and the side intake zone, extracts three sets of continuous points, judges concentration abrupt changes, constructs spatial change paths, marks the coordinates of the largest abrupt change, and generates a set of pollution boundary line locations. The trend offset judgment module, based on the pollution boundary line location set, compares the boundary line coordinates of the continuous monitoring period, calculates the distance difference between the boundary and the center of the air valve, analyzes whether the direction is consistent, records the vector and measures the offset, and generates boundary offset vector information. The pre-control response setting module calculates the angle by converting the boundary distance ratio based on the direction and magnitude of the boundary offset vector information and the opening range of the air valve, outputs the air valve drive signal, and obtains the pre-response angle command. The risk weight rearrangement module, based on the pre-response angle command, wind speed, and concentration growth rate, adjusts the control priority and generates a priority response sorting list if the concentration growth rate is faster than the wind speed. The linkage triggering mechanism module determines the distance between the nearest point in the priority response sorting list and the pollution boundary line location set. If the distance reaches the warning range, it triggers the air valve to open fully and outputs an intelligent fume hood control signal.

2. The intelligent fume hood control system according to claim 1, characterized in that: The pollution boundary line location set includes the coordinates of the maximum abrupt change point, spatial change path nodes, and boundary line boundary point coordinates. The boundary offset vector information includes the boundary direction vector, boundary offset distance, and boundary center position. The pre-response angle command includes the target angle value, damper control parameters, and drive output signal. The priority response sorting list includes the response priority, sorting sequence number, and corresponding control strategy. The intelligent fume hood control signal includes the full-open command, linkage control signal, and early warning trigger status.

3. The intelligent fume hood control system according to claim 1, characterized in that: The concentration mutation is defined as a concentration change exceeding a set threshold across three consecutive monitoring points.

4. The intelligent fume hood control system according to claim 1, characterized in that: The definition of the opening range of the air valve refers to the range of adjustable opening angles of the air valve.

5. The intelligent fume hood control system according to claim 1, characterized in that: The warning range is defined as the minimum safe distance threshold between the pollution boundary line and the air valve.

6. The intelligent fume hood control system according to claim 1, characterized in that, The pollution trend identification module includes: The concentration data extraction submodule collects the pollution concentration monitoring points set up in the main exhaust duct section and the side intake guide area, extracts three sets of continuous points in the order of arrangement, obtains the pollution concentration value corresponding to each set of points, forms three sets of ternary pollution data sequences, and generates a set of continuous point concentration values. The difference fluctuation judgment submodule calculates the concentration difference between the same numbered points in the first group and the second group, and between the second group and the third group, based on the continuous point concentration value set, obtains two sets of difference sequences, calculates the increase in the difference between corresponding points and compares it with the concentration change judgment threshold, extracts the points where the increase changes, and obtains the concentration change position sequence. The boundary line coordinate calibration submodule locates the index coordinates of the mutation points in the monitoring layout map according to the concentration mutation location sequence, calls the layout coordinate information to extract the corresponding spatial location, selects the point with the largest mutation amplitude as the spatial turning reference point, records the coordinates of all mutation points one by one, and generates a pollution boundary line location set.

7. The intelligent fume hood control system according to claim 1, characterized in that, The trend deviation judgment module includes: The boundary change extraction submodule extracts the coordinates of periodic boundary points based on the pollution boundary line location set and converts them into a unified coordinate format. It then calculates the geometric center position of the boundary within the period and generates a set of periodic boundary center coordinates. The center distance calculation submodule obtains the Euclidean distance between the center point of the cycle and the center coordinates of the damper based on the set of center coordinates of the cycle boundary, calculates the distance difference sequence between adjacent cycles, and obtains the boundary center offset. The spatial offset output submodule determines whether the angle between the boundary center movement direction and the valve direction is less than a direction threshold based on the boundary center offset. If the condition is met, the boundary center vector difference is calculated and recorded as a spatial vector to generate boundary offset vector information.

8. The intelligent fume hood control system according to claim 1, characterized in that, The pre-control response setting module includes: The damper parameter extraction submodule obtains the direction consistency result and offset amplitude value in the boundary offset vector information, calls the damper structure parameter table, extracts the opening amplitude range and position reference ratio corresponding to the current damper, establishes the damper control boundary, and generates the damper control parameter set. The angle conversion submodule calculates the linear relationship between the offset value and the control ratio of the valve based on the valve position ratio range of the valve control parameters and the offset distance in the boundary offset vector information. The result is then input into the angle conversion sequence to obtain the valve angle conversion result. The response signal generation submodule extracts the corresponding air valve number based on the air valve angle conversion result and calls the drive channel encoder to convert the angle value into a drive signal. It then combines the period identifier with the air valve control channel data, outputs control commands, and generates a pre-response angle command.

9. The intelligent fume hood control system according to claim 1, characterized in that, The risk weight rearrangement module includes: The rate of change extraction submodule calls the pre-response angle command, wind speed monitoring data and pollution concentration monitoring data to obtain the wind speed change amplitude and pollution concentration growth rate value at the time point corresponding to the current air valve angle, calculates the average rate of change within the period, and generates the pollution wind speed change rate. The proportional relationship judgment submodule calculates the proportional coefficient between the pollution concentration increase value and the wind speed increase value in the pollution wind speed change rate. If the proportional value is greater than the pollution response threshold proportional standard, the pollution response priority is determined to be higher than the wind speed response, and the priority judgment result is obtained. The response list generation submodule adjusts the position of pollution control associated instructions in the task sorting list based on the priority judgment result. If the priority is high, it will be moved to the first position of the task, and the task order data structure will be reorganized to generate a priority response sorting list.

10. The intelligent fume hood control system according to claim 1, characterized in that, The linkage triggering mechanism module includes: The boundary distance calculation submodule obtains the first instruction item in the priority response sorting list and the location set of the pollution boundary line, extracts the coordinates of the point closest to the air valve in the boundary line and calls the air valve location coordinates, calculates the Euclidean distance value between the two, and generates the boundary distance measurement value. The condition comparison and verification submodule compares the measured boundary distance value with the set early warning activation boundary distance threshold to determine whether the current distance is less than the threshold. If the threshold is met, a control transition flag is generated to obtain the joint control trigger judgment result. Based on the joint control trigger judgment result being in the start state, the joint control signal output submodule replaces the pre-response control state with the air valve fully open command, combines the air valve number with the control status code to form a control command signal data packet, and generates an intelligent fume hood control signal.

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