An energy chemical analysis laboratory top-outlet bottom-inlet ventilation air conditioning system

Abstract

The application discloses an energy chemical analysis laboratory up-exhaustion and down-inlet ventilation air conditioning system, and relates to the technical field of ventilation control. The system comprises a data mapping module, a matrix construction module, a diffusion analysis module, a reverse airflow analysis module and an instruction sending module. The application constructs a laboratory three-dimensional space grid model and maps sensor data in real time, calculates a pollutant migration trend vector, and calculates and generates a reverse airflow suppression parameter in the opposite direction, and finally dynamically adjusts the fan frequency and the air valve opening degree, so that the active prediction and accurate suppression of the harmful gas diffusion path are achieved, a stable and efficient vertical upward up-exhaustion and down-inlet airflow organization is forcedly formed, and the problems of control response lag, blind airflow organization and inability to actively suppress the diffusion source in the prior art are solved.

Description

Technical Field

[0001] This invention relates to the field of ventilation control technology, and in particular to a top-exhaust, bottom-intake ventilation and air conditioning system for an energy and chemical analysis laboratory. Background Technology

[0002] As the complexity and safety requirements of analytical experiments in the energy and chemical industry increase, laboratories face higher demands for the ability to control the diffusion of harmful gases in real time and with precision when handling flammable, explosive, toxic, or corrosive chemicals. Any control lag or airflow failure can lead to the spread of pollutants indoors, seriously endangering personnel health and equipment safety.

[0003] In related technologies, the control of laboratory ventilation mainly relies on fixed-frequency operation combined with manual damper adjustment, or the use of simple constant air volume / variable air volume (CAV / VAV) systems to maintain overall airflow and pressure differential balance. However, these methods can only respond to macroscopic state changes such as equipment start-up and shutdown, and cannot perceive and predict the specific diffusion paths and trends of pollutants in the space in real time. They are difficult to meet the stringent ventilation safety requirements of high-risk energy and chemical analysis laboratories, and suffer from problems such as delayed control response, blind airflow organization, and inability to actively suppress diffusion sources. Summary of the Invention

[0004] This application provides an upward exhaust and downward intake ventilation and air conditioning system for an energy and chemical analysis laboratory, which solves the problems of delayed control response, blind airflow organization, and inability to actively suppress diffusion sources in the prior art. It achieves active prediction and precise suppression of the diffusion path of harmful gases, and forces the formation of a stable and efficient vertical upward exhaust and downward intake airflow organization.

[0005] This application provides an energy and chemical analysis laboratory top-exhaust and bottom-intake ventilation and air conditioning system, including: a data mapping module, a matrix construction module, a diffusion analysis module, a reverse airflow analysis module, and an instruction sending module; The data mapping module is used to collect data from static pressure sensors, wind speed sensors, and gas concentration sensors deployed in the laboratory according to a preset time period, and map the data to a pre-constructed three-dimensional spatial grid model of the laboratory. The matrix construction module is used to calculate the pressure difference between adjacent nodes based on the static pressure values ​​of adjacent grid nodes in the three-dimensional spatial grid model, and to construct a regional pressure gradient matrix. The diffusion analysis module is used to combine gas concentration sensor data and regional pressure gradient matrix to calculate the diffusion weighting value of pollutants between grids and generate a pollutant migration trend vector describing the dynamic diffusion direction of pollutants. The reverse airflow analysis module is used to calculate the reverse airflow suppression parameters that can counteract the direction of pollutant diffusion based on the pollutant migration trend vector, and to calculate the target operating frequency of the supply fan and exhaust fan and the target opening degree of each air valve based on the reverse airflow suppression parameters. The instruction sending module is used to convert the target operating frequency and target opening degree into control instructions and send them to the execution device to drive air into the lower area of ​​the laboratory and guide the gas to be discharged from the top area of ​​the laboratory until the magnitude of the pollutant migration trend vector returns to zero.

[0006] Furthermore, mapping the data to a pre-built laboratory three-dimensional spatial mesh model specifically includes: The sensor values ​​are read from each discrete distribution via the communication bus; Based on the actual installation coordinates of the sensor, the values ​​are filled into the data domain of the coordinate nodes corresponding to the three-dimensional spatial grid model, and the area in the laboratory where the gas is generated is defined as the source node. Define the exhaust vent area at the top of the laboratory as the sink node; The lower air supply vent area of ​​the laboratory is defined as the supply node; A digital mapping grid containing node attributes and real-time status data is formed.

[0007] Furthermore, the specific steps for constructing the regional pressure gradient matrix include: Traverse each source node in the 3D spatial mesh model; Search for the six spatially adjacent neighboring nodes of the source node, and calculate the pressure difference between the static pressure value of the source node and the static pressure value of each neighboring node. All calculated pressure differences are arranged according to their spatial relationships to generate a regional pressure gradient matrix, which is used to reflect the airflow pressure imbalance between different local areas inside the laboratory at that moment.

[0008] Furthermore, the generation of the pollutant migration trend vector describing the dynamic diffusion direction of pollutants specifically includes: The concentration values ​​from the gas concentration sensor data are extracted as weighting coefficients. The weighted diffusion potential energy values ​​in each direction are obtained by multiplying the weighting coefficients with the pressure differences at the corresponding positions in the regional pressure gradient matrix. By vector synthesis of the weighted diffusion potential energy values ​​in each direction, a pollutant migration trend vector indicating the diffusion path and intensity of high-concentration gas is generated.

[0009] Furthermore, the calculation of the target operating frequencies of the supply and exhaust fans and the target opening degrees of each damper specifically includes: The pollutant migration trend vector is inverted to obtain the theoretical suppression vector. Based on the data logic of the fluid dynamics continuity equation, the required increase in exhaust suction at the sink node and the required adjustment in supply thrust at the supply node are calculated. An airflow field consistent with the theoretical suppression vector direction is constructed to obtain the target operating frequencies of the supply and exhaust fans.

[0010] Furthermore, the calculation of the required increase in exhaust suction at the sink node and the required adjustment in supply thrust at the replenishment node specifically includes: Determine whether the horizontal component magnitude of the pollutant migration trend vector exceeds a preset safety threshold. If the value is exceeded, the gain coefficient of the exhaust valve opening vertically above the source node is increased when calculating the exhaust suction value. At the same time, the air supply volume of the supply node in the same direction as the migration direction is reduced when calculating the supply thrust value. By adjusting the ratio of the airflow components in the vertical and horizontal directions, the airflow trajectory is forcibly corrected to be vertically upward.

[0011] Furthermore, the calculation of the target operating frequency of the supply fan and exhaust fan and the target opening degree of each air valve based on the reverse airflow suppression parameters specifically includes: Retrieve the pre-stored curve table showing the relationship between fan frequency and air volume; Interpolation algorithms are used to find frequency setpoints that match the reverse airflow suppression parameters. For exhaust valves arranged at different heights, different opening percentages are assigned based on the distribution weight of the pollutant migration trend vector on the vertical axis, so that the exhaust flow in the upper area of ​​the laboratory is greater than that in the lower area, forming a guiding airflow that is discharged from the top and enters from the bottom.

[0012] Furthermore, the step of converting the target operating frequency and target opening degree into control commands and sending them to the execution device specifically includes: Encapsulate the target operating frequency into a frequency converter control message; The target opening is encapsulated as an actuator adjustment message and distributed to the corresponding hardware controller by address through the industrial control network. Simultaneously, logical checks are performed before sending instructions to ensure that the start timestamp in the exhaust fan instruction is earlier than the start timestamp in the supply fan instruction, and that the stop timestamp in the exhaust fan instruction is later than the stop timestamp in the supply fan instruction.

[0013] Furthermore, the step of reducing the magnitude of the pollutant migration trend vector to zero specifically includes: In the next acquisition cycle after sending the control command, the pressure difference between adjacent nodes and the diffusion weighting of pollutants between grids are recalculated. Determine whether the magnitude of the updated pollutant migration trend vector is less than the preset zero-point judgment threshold; If the value is not less than the zero-point threshold, the adjustment step size is accumulated and the target operating frequency of the blower and exhaust fan is calculated repeatedly.

[0014] Furthermore, determining whether the magnitude of the updated pollutant migration trend vector is less than a preset zero-point determination threshold specifically includes: Compare the pollutant migration trend vector of the current period with the pollutant migration trend vector of the previous period, and calculate the vector deflection angle and modulus attenuation rate. If the modulus attenuation rate is lower than the preset efficiency value, the emergency data processing protocol is triggered, setting the target opening of the exhaust valves of all hub nodes to the maximum value, and locking the air supply data of all supply nodes to the minimum value to maintain a slight positive pressure.

[0015] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: This application provides a top-exhaust, bottom-intake ventilation and air conditioning system for an energy and chemical analysis laboratory. A data mapping module maps real-time sensor data to a three-dimensional spatial grid model of the laboratory; a matrix construction module calculates the regional pressure gradient matrix based on this; a diffusion analysis module combines gas concentration data to generate a pollutant migration trend vector; a reverse airflow analysis module calculates the reverse airflow suppression parameters based on this vector and determines the target frequency of the fan and the target opening degree of the damper; and a command sending module converts these into control commands to drive the execution equipment until the pollutant diffusion trend is suppressed.

[0016] In this process, the dynamic perception and quantitative analysis of airflow and pollutant diffusion in the laboratory have changed the traditional experience-based control mode based on fixed parameters.

[0017] Furthermore, by calculating the pollutant migration trend vector and generating reverse airflow suppression parameters to precisely counteract it, the diffusion direction and intensity of harmful gases can be identified, and control strategies to counteract them can be actively generated. This achieves a shift from passive uniform exhaust to active and precise suppression, thereby improving the speed and accuracy of controlling sudden leaks or diffusions.

[0018] Furthermore, by converting the reverse suppression parameters into specific fan frequency and stratified air valve opening commands, and forcibly executing the airflow organization logic of top exhaust and bottom intake, the ratio of vertical and horizontal airflow is dynamically adjusted to ensure that an effective vertical directional airflow can be formed and maintained under any operating condition. This reduces the horizontal diffusion and retention of pollutants in the breathing zone of personnel and improves the intrinsic safety level of the energy and chemical laboratory. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of a top-outlet, bottom-inlet ventilation and air conditioning system for an energy and chemical analysis laboratory, provided as an embodiment of this application. Detailed Implementation

[0020] This application provides an energy and chemical analysis laboratory's top-exhaust, bottom-intake ventilation and air conditioning system, which solves the problems of lagging control response, blind airflow organization, and inability to actively suppress diffusion sources in the prior art. By constructing a three-dimensional spatial grid model of the laboratory and mapping sensor data in real time, the system calculates the pollutant migration trend vector and calculates the reverse airflow suppression parameters in the opposite direction. Finally, it dynamically adjusts the fan frequency and the opening of the air valve, realizing the active prediction and precise suppression of the diffusion path of harmful gases, and forcibly forming a stable and efficient vertical upward top-exhaust, bottom-intake airflow organization.

[0021] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0022] like Figure 1 As shown in the figure, this application provides an energy and chemical analysis laboratory top-exhaust and bottom-intake ventilation and air conditioning system, including: a data mapping module, a matrix construction module, a diffusion analysis module, a reverse airflow analysis module, and a command sending module; The data mapping module is used to collect data from static pressure sensors, wind speed sensors, and gas concentration sensors deployed in the laboratory via industrial Ethernet or fieldbus according to a preset time period, and map the data to a pre-constructed three-dimensional spatial mesh model of the laboratory. Furthermore, mapping the data to a pre-built laboratory three-dimensional spatial mesh model specifically includes: The sensor values ​​are read from each discrete distribution via the communication bus; Based on the actual installation coordinates of the sensor, the values ​​are filled into the data domain of the coordinate nodes corresponding to the three-dimensional spatial grid model, and the area in the laboratory where the gas is generated is defined as the source node. Define the exhaust vent area at the top of the laboratory as the sink node; The lower air supply vent area of ​​the laboratory is defined as the supply node; A digital mapping grid containing node attributes and real-time status data is formed.

[0023] In this embodiment, by mapping sensor data to a three-dimensional mesh according to coordinates and defining node types such as source, sink, and supply, it is ensured that all analysis and control commands have a clear and consistent spatial basis. Filling in the values ​​according to the actual installation coordinates of the sensor means that there is a mapping table in the system database that records information such as "Sensor ID: S001, installation coordinates: (x=2.5m, y=3.0m, z=1.5m), grid node index: (5,6,3)". After reading the data of sensor S001, the corresponding attribute values ​​of the `LabSpace[5][6][3]` node are directly updated. Defining source nodes, sink nodes, and supply nodes is used to quickly identify airflow boundaries and key control points.

[0024] After data collection, based on the pre-stored sensor coordinate installation table, the filtered and denoised values ​​of each sensor are filled into the grid node with the best matching coordinates in the laboratory's three-dimensional spatial grid model.

[0025] For grid nodes without installed sensors, the static pressure value and gas concentration value It is obtained by performing three-dimensional linear interpolation on the values ​​of several nearest sensor nodes in its vicinity.

[0026] Source nodes refer to the set of grid nodes in a three-dimensional spatial grid model that are marked as potential or ongoing locations of harmful gas release.

[0027] A cluster node refers to the set of grid nodes in a three-dimensional spatial grid model that spatially coincide with the exhaust vent at the top of the laboratory.

[0028] A supply node refers to the set of grid nodes in a three-dimensional spatial grid model that spatially overlap with the air supply vents at the bottom of the laboratory.

[0029] The matrix construction module is used to calculate the pressure difference between adjacent nodes based on the static pressure values ​​of adjacent grid nodes in the three-dimensional spatial grid model, and to construct a regional pressure gradient matrix.

[0030] Furthermore, the specific steps for constructing the regional pressure gradient matrix include: Traverse each source node in the 3D spatial mesh model; Search for the six spatially adjacent neighboring nodes of the source node, and calculate the pressure difference between the static pressure value of the source node and the static pressure value of each neighboring node. All calculated pressure differences are arranged according to their spatial relationships to generate a regional pressure gradient matrix, which is used to reflect the airflow pressure imbalance between different local areas inside the laboratory at that moment.

[0031] In this embodiment, a regional pressure gradient matrix is ​​constructed by calculating the pressure difference between adjacent grid nodes, transforming the pressure field into structured data, thereby enabling the identification and quantification of local dynamic sources driving airflow.

[0032] Iterate through each grid node in the digitized mapping mesh. For each node, retrieve its location in... , , The nodes are directly adjacent in the six positive and negative directions of the axis. Based on the airflow from high pressure to low pressure, calculate the pressure difference between this node and each adjacent node. All calculated pressure differences are organized into a multidimensional array according to their source nodes and directions; this array is the regional pressure gradient matrix. The regional pressure gradient matrix is ​​a discretized pressure gradient field. The numerical representation is used to reflect the driving potential energy and potential flow direction of airflow at various points inside the laboratory.

[0033] The traversal refers to accessing each element of the three-dimensional array `LabSpace` using a loop procedure. Retrieving neighboring nodes in the six directions is equivalent to accessing the array index. , , Calculating pressure difference based on pressure difference-driven flow. The generated regional pressure gradient matrix is ​​the pressure gradient field. Discrete gradient: .

[0034] The node spacing, i.e. the grid resolution, is preset according to the size of the laboratory and the accuracy requirements, for example, 0.5 meters. For coordinate index.

[0035] The diffusion analysis module is used to combine gas concentration sensor data and regional pressure gradient matrix to calculate the diffusion weighting value of pollutants between grids and generate a pollutant migration trend vector describing the dynamic diffusion direction of pollutants.

[0036] Furthermore, the generation of the pollutant migration trend vector describing the dynamic diffusion direction of pollutants specifically includes: The concentration values ​​from the gas concentration sensor data are extracted as weighting coefficients. The weighted diffusion potential energy values ​​in each direction are obtained by multiplying the weighting coefficients with the pressure differences at the corresponding positions in the regional pressure gradient matrix. By vector synthesis of the weighted diffusion potential energy values ​​in each direction, a pollutant migration trend vector indicating the diffusion path and intensity of high-concentration gas is generated.

[0037] In this embodiment, by combining gas concentration data as weights with the pressure gradient matrix, a pollutant migration trend vector is calculated and generated, thereby quantitatively assessing the diffusion direction and intensity of pollutants. The inter-grid diffusion weighting calculation process is as follows: for each source node and its diffusion direction, the diffusion intensity is determined by both the concentration difference and the pressure difference. Therefore, the gas concentration value... As a weight, the pressure difference in the corresponding direction Multiplying them together yields a weighted diffusion potential value. This calculation can be expressed as: .

[0038] Generating a pollutant migration trend vector refers to weighting the diffusion potential energy values ​​of each source node in six directions. Vector synthesis is performed to obtain the local diffusion trend of the node. Then, the local diffusion trend vectors of all source nodes are summed to obtain the global pollutant migration trend vector. The pollutant migration trend vector reflects the direction and intensity of pollutant migration under the influence of concentration and airflow. The direction of the pollutant migration trend vector indicates the main diffusion path, and its magnitude... This represents the overall intensity of diffusion.

[0039] The reverse airflow analysis module is used to calculate the reverse airflow suppression parameters that can counteract the direction of pollutant diffusion based on the pollutant migration trend vector, and to calculate the target operating frequency of the supply fan and exhaust fan and the target opening degree of each air valve based on the reverse airflow suppression parameters.

[0040] Furthermore, the calculation of the target operating frequencies of the supply and exhaust fans and the target opening degrees of each damper specifically includes: The pollutant migration trend vector is inverted to obtain the theoretical suppression vector. Based on the data logic of the fluid dynamics continuity equation, the required increase in exhaust suction at the sink node and the required adjustment in supply thrust at the supply node are calculated. An airflow field consistent with the theoretical suppression vector direction is constructed to obtain the target operating frequencies of the supply and exhaust fans.

[0041] In this embodiment, by calculating the reverse vector based on the pollutant migration trend vector, and then using this to calculate the target parameters of the fan and damper, control commands can be directly targeted at the diffusion source to counteract it, thereby improving the efficiency and specificity of ventilation control. The calculation process for the reverse airflow suppression parameters is as follows: the reverse direction of the pollutant migration trend vector is directly taken as the theoretical suppression vector, i.e. .

[0042] Calculate the target value for equipment control: First, based on the theoretical suppression vector... Based on the magnitude of the vertical component, estimate the total exhaust volume that needs to be increased or decreased. and air volume The formula for estimating air volume is: ,in These are the empirical coefficients obtained through system identification. The cross-sectional area of ​​the laboratory. yes The vertical component.

[0043] Then, the pre-stored fan frequency vs. air volume relationship curve table is consulted, and interpolation is used to find the target operating frequencies of the supply and exhaust fans required to meet the target air volume. Simultaneously, based on... Based on the direction and proportional allocation strategy, calculate the target opening degree of each exhaust valve and supply valve.

[0044] According to the data logic of the continuity equation in fluid dynamics, for a steady-state incompressible fluid, the mass flowing into the control volume equals the mass flowing out. This is equivalent to offsetting a pollutant migration trend vector. This requires generating at least an equivalent airflow in the opposite direction. Therefore, according to By determining the modulus and direction, the required suction air volume at the sink node (exhaust outlet) and the required supply air volume at the replenishment node (supply outlet) are calculated, thereby constructing the required reverse airflow field.

[0045] Specifically, the calculation of the required increase in exhaust suction at the sink node and the required adjustment in supply thrust at the replenishment node includes: Determine whether the horizontal component magnitude of the pollutant migration trend vector exceeds a preset safety threshold. If the value is exceeded, the gain coefficient of the exhaust valve opening vertically above the source node is increased when calculating the exhaust suction value. At the same time, the air supply volume of the supply node in the same direction as the migration direction is reduced when calculating the supply thrust value. By adjusting the ratio of the airflow components in the vertical and horizontal directions, the airflow trajectory is forcibly corrected to be vertically upward.

[0046] In this embodiment, by determining whether the horizontal diffusion risk exceeds the limit and adjusting the ratio of the vertical and horizontal airflow control components accordingly, the vertical airflow can be forcibly strengthened when necessary, thereby reducing the risk of horizontal diffusion of pollutants in the breathing zone. This addresses the specific safety requirements for preventing the horizontal diffusion of harmful gases in energy and chemical laboratories. When a pollutant migration trend vector is detected... When the horizontal component is too large, it indicates a significant risk of horizontal diffusion. In this case, when calculating the exhaust suction, the calculation result involving the vertically upward exhaust valve is multiplied by a gain coefficient greater than 1 to forcibly increase the upward suction force. At the same time, the lower air supply volume on the same side as the diffusion direction is reduced, weakening the horizontal airflow driving force. This adjustment changes the ratio of the vertical to horizontal components in the airflow field, making the synthesized airflow more vertically upward and enhancing the effect of upward exhaust and downward intake.

[0047] Specifically, the calculation of the target operating frequency of the supply fan and exhaust fan and the target opening degree of each air valve based on the reverse airflow suppression parameters includes: Retrieve the pre-stored curve table showing the relationship between fan frequency and air volume; Interpolation algorithms are used to find frequency setpoints that match the reverse airflow suppression parameters. For exhaust valves arranged at different heights, different opening percentages are assigned based on the distribution weight of the pollutant migration trend vector on the vertical axis, so that the exhaust flow in the upper area of ​​the laboratory is greater than that in the lower area, forming a guiding airflow that is discharged from the top and enters from the bottom.

[0048] In this embodiment, the frequency is obtained by querying the fan characteristic curve, and the opening degree of the exhaust valves at different heights is allocated according to the vertical distribution weight, thus transforming the macroscopic control target into specific equipment parameters and maintaining the airflow organization of top exhaust and bottom intake. The opening percentage is obtained by querying the fan frequency and air volume relationship curve table. The pre-stored fan frequency and air volume relationship curve table is a discrete data table obtained from fan factory testing or on-site calibration. The interpolation algorithm can use piecewise linear interpolation: for the target air volume Find two adjacent points in the table. and Make The target wind turbine frequency .

[0049] The allocation of exhaust valve opening based on the weighted distribution of the pollutant migration trend vector on the vertical axis refers to: Suppose there are three exhaust valves at different heights, with elevations of respectively , Then the weights can be allocated according to The calculation is performed, where n is the index of the exhaust valve. This ensures that the exhaust valve at the highest position achieves its maximum opening, promoting airflow from bottom to top.

[0050] The instruction sending module is used to convert the target operating frequency and target opening degree into control instructions and send them to the execution device to drive air into the lower area of ​​the laboratory and guide the gas to be discharged from the top area of ​​the laboratory until the magnitude of the pollutant migration trend vector returns to zero.

[0051] In this embodiment, the target operating frequency and target opening degree are encapsulated into control command frames according to a prescribed industrial communication protocol format. Before transmission, a logic check is performed to ensure that the command sequence conforms to the hard safety interlock logic of the exhaust fan starting first and then stopping. After the check passes, the commands are distributed to the corresponding frequency converters and damper actuators through the industrial network.

[0052] Furthermore, the step of converting the target operating frequency and target opening degree into control commands and sending them to the execution device specifically includes: Encapsulate the target operating frequency into a frequency converter control message; The target opening is encapsulated as an actuator adjustment message and distributed to the corresponding hardware controller by address through the industrial control network. Simultaneously, logical checks are performed before sending instructions to ensure that the start timestamp in the exhaust fan instruction is earlier than the start timestamp in the supply fan instruction, and that the stop timestamp in the exhaust fan instruction is later than the stop timestamp in the supply fan instruction.

[0053] In this embodiment, by encapsulating control parameters into command messages and verifying the start-stop timing logic of the exhaust fan and supply fan before sending, the equipment operation meets the safety interlock requirements, thereby helping to maintain negative pressure in the laboratory and prevent airflow reversal. Encapsulating into inverter control messages means assembling the target frequency value (e.g., 45.0 Hz) according to the register address and format specified in the inverter manual (e.g., writing to holding register 40001).

[0054] The execution logic verification involves setting up a state machine within the software. Before each instruction is issued, it checks whether the timestamp of the exhaust fan start command in the current instruction set is earlier than the supply fan start command, and whether the timestamp of the exhaust fan stop command is later than the supply fan stop command. If these conditions are not met, the timestamps are automatically adjusted or an error is reported and the transmission is aborted to prevent airflow reversal.

[0055] Furthermore, the step of reducing the magnitude of the pollutant migration trend vector to zero specifically includes: In the next acquisition cycle after sending the control command, the pressure difference between adjacent nodes and the diffusion weighting of pollutants between grids are recalculated. Determine whether the magnitude of the updated pollutant migration trend vector is less than the preset zero-point judgment threshold; If the value is not less than the zero-point threshold, the adjustment step size is accumulated and the target operating frequency of the blower and exhaust fan is calculated repeatedly.

[0056] In this embodiment, by recalculating the pollutant migration trend vector in the next cycle and determining whether its magnitude converges, iterative adjustments can be made based on feedback, thereby enabling the control process to continuously adapt to changes in laboratory conditions. After sending a control command, the system does not wait but enters the next acquisition cycle, re-executing the entire process from data mapping to calculating the pollutant migration trend vector. The control effect is determined by comparing the magnitudes of the pollutant migration trend vector before and after the update.

[0057] Specifically, determining whether the magnitude of the updated pollutant migration trend vector is less than a preset zero-point threshold includes: Compare the pollutant migration trend vector of the current period with the pollutant migration trend vector of the previous period, and calculate the vector deflection angle and modulus attenuation rate. If the modulus attenuation rate is lower than the preset efficiency value, the emergency data processing protocol is triggered, setting the target opening of the exhaust valves of all hub nodes to the maximum value, and locking the air supply data of all supply nodes to the minimum value to maintain a slight positive pressure.

[0058] In this embodiment, by monitoring the attenuation efficiency of the diffusion trend vector and triggering an emergency protocol to force maximum ventilation when the efficiency is too low, the system can switch to a safe mode when conventional control is insufficient, thus providing additional protection for responding to emergencies. Vector deflection angle With modulus attenuation rate It is a key indicator for evaluating control efficiency. and These refer to the pollutant migration trend vectors calculated from two adjacent control cycles in time, where the subscript t represents the current moment and t-1 represents the previous moment.

[0059] If the modulus attenuation rate If the efficiency is below the preset minimum value for several consecutive cycles, such as 10%, it indicates that the conventional closed-loop algorithm may be unable to effectively cope with a sudden large leakage.

[0060] At this moment, the system immediately interrupts the existing algorithm and executes the hard-coded emergency data processing protocol: setting the target opening of the exhaust valves corresponding to all sink nodes to 100%, and setting the air supply volume corresponding to all supply nodes to the minimum value that can only maintain a slight positive pressure in the gaps of laboratory doors and windows to prevent external pollutants from seeping in, instantly maximizing the exhaust capacity and prioritizing safety.

[0061] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0062] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0063] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0064] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0065] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0066] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A top-exhaust, bottom-intake ventilation and air conditioning system for an energy and chemical analysis laboratory, characterized in that, include: Data mapping module, matrix construction module, diffusion analysis module, reverse airflow analysis module, command sending module; The data mapping module is used to collect data from static pressure sensors, wind speed sensors, and gas concentration sensors deployed in the laboratory according to a preset time period, and map the data to a pre-constructed three-dimensional spatial grid model of the laboratory. The matrix construction module is used to calculate the pressure difference between adjacent nodes based on the static pressure values ​​of adjacent grid nodes in the three-dimensional spatial grid model, and to construct a regional pressure gradient matrix. The diffusion analysis module is used to combine gas concentration sensor data and regional pressure gradient matrix to calculate the diffusion weighting value of pollutants between grids and generate a pollutant migration trend vector describing the dynamic diffusion direction of pollutants. The reverse airflow analysis module is used to calculate the reverse airflow suppression parameters that can counteract the direction of pollutant diffusion based on the pollutant migration trend vector, and to calculate the target operating frequency of the supply fan and exhaust fan and the target opening degree of each air valve based on the reverse airflow suppression parameters. The instruction sending module is used to convert the target operating frequency and target opening degree into control instructions and send them to the execution device to drive air into the lower area of ​​the laboratory and guide the gas to be discharged from the top area of ​​the laboratory until the magnitude of the pollutant migration trend vector returns to zero.

2. The top-exhaust, bottom-intake ventilation and air conditioning system for an energy and chemical analysis laboratory as described in claim 1, characterized in that, The process of mapping the data to a pre-constructed three-dimensional spatial mesh model of the laboratory specifically includes: The sensor values ​​are read from each discrete distribution via the communication bus; Based on the actual installation coordinates of the sensor, the values ​​are filled into the data domain of the coordinate nodes corresponding to the three-dimensional spatial grid model, and the area in the laboratory where the gas is generated is defined as the source node. Define the exhaust vent area at the top of the laboratory as the sink node; The lower air supply vent area of ​​the laboratory is defined as the supply node; A digital mapping grid containing node attributes and real-time status data is formed.

3. The top-exhaust, bottom-intake ventilation and air conditioning system for an energy and chemical analysis laboratory as described in claim 1, characterized in that, The specific steps for constructing the regional pressure gradient matrix include: Traverse each source node in the 3D spatial mesh model; Search for the six spatially adjacent neighboring nodes of the source node, and calculate the pressure difference between the static pressure value of the source node and the static pressure value of each neighboring node. All calculated pressure differences are arranged according to their spatial relationships to generate a regional pressure gradient matrix, which is used to reflect the airflow pressure imbalance between different local areas inside the laboratory at that moment.

4. The top-exhaust, bottom-intake ventilation and air conditioning system for an energy and chemical analysis laboratory as described in claim 1, characterized in that, The generation of the pollutant migration trend vector describing the dynamic diffusion direction of pollutants specifically includes: The concentration values ​​from the gas concentration sensor data are extracted as weighting coefficients. The weighted diffusion potential energy values ​​in each direction are obtained by multiplying the weighting coefficients with the pressure differences at the corresponding positions in the regional pressure gradient matrix. By vector synthesis of the weighted diffusion potential energy values ​​in each direction, a pollutant migration trend vector indicating the diffusion path and intensity of high-concentration gas is generated.

5. The top-exhaust, bottom-intake ventilation and air conditioning system for an energy and chemical analysis laboratory as described in claim 1, characterized in that, The calculation of the target operating frequency of the supply fan and exhaust fan and the target opening degree of each air valve specifically includes: Invert the pollutant migration trend vector to obtain the theoretical suppression vector, and calculate the exhaust suction value that needs to be increased at the sink node and the supply thrust value that needs to be adjusted at the supply node. An airflow field consistent with the theoretical suppression vector direction is constructed to obtain the target operating frequencies of the supply and exhaust fans.

6. The top-exhaust, bottom-intake ventilation and air conditioning system for an energy and chemical analysis laboratory as described in claim 5, characterized in that, The calculation of the required increase in exhaust suction at the sink node and the required adjustment in supply thrust at the replenishment node specifically includes: Determine whether the horizontal component magnitude of the pollutant migration trend vector exceeds a preset safety threshold. If the value is exceeded, the gain coefficient of the exhaust valve opening vertically above the source node is increased when calculating the exhaust suction value. At the same time, the air supply volume of the supply node in the same direction as the migration direction is reduced when calculating the supply thrust value. By adjusting the ratio of the airflow components in the vertical and horizontal directions, the airflow trajectory is forcibly corrected to be vertically upward.

7. The top-exhaust, bottom-intake ventilation and air conditioning system for an energy and chemical analysis laboratory as described in claim 5, characterized in that, The calculation of the target operating frequency of the supply fan and exhaust fan and the target opening degree of each air valve based on the reverse airflow suppression parameters specifically includes: Retrieve the pre-stored curve table showing the relationship between fan frequency and air volume; Find the frequency setpoint that matches the reverse airflow suppression parameters, and for exhaust valves arranged at different heights, allocate different opening percentages according to the distribution weight of the pollutant migration trend vector on the vertical axis, so that the exhaust flow in the upper area of ​​the laboratory is greater than that in the lower area, forming an upward exhaust and downward intake guiding airflow.

8. The top-exhaust, bottom-intake ventilation and air conditioning system for an energy and chemical analysis laboratory as described in claim 1, characterized in that, The step of converting the target operating frequency and target opening degree into control commands and sending them to the execution device specifically includes: Encapsulate the target operating frequency into a frequency converter control message; The target opening is encapsulated as an actuator adjustment message and distributed to the corresponding hardware controller by address through the industrial control network. Simultaneously, logical checks are performed before sending instructions to ensure that the start timestamp in the exhaust fan instruction is earlier than the start timestamp in the supply fan instruction, and that the stop timestamp in the exhaust fan instruction is later than the stop timestamp in the supply fan instruction.

9. The top-exhaust, bottom-intake ventilation and air conditioning system for an energy and chemical analysis laboratory as described in claim 1, characterized in that, The process of ensuring that the magnitude of the pollutant migration trend vector returns to zero specifically includes: In the next acquisition cycle after sending the control command, the pressure difference between adjacent nodes and the diffusion weighting of pollutants between grids are recalculated. Determine whether the magnitude of the updated pollutant migration trend vector is less than the preset zero-point judgment threshold; If the value is not less than the zero-point threshold, the adjustment step size is accumulated and the target operating frequency of the blower and exhaust fan is calculated repeatedly.

10. The top-exhaust, bottom-intake ventilation and air conditioning system for an energy and chemical analysis laboratory as described in claim 9, characterized in that, The determination of whether the magnitude of the updated pollutant migration trend vector is less than a preset zero-point threshold specifically includes: Compare the pollutant migration trend vector of the current period with the pollutant migration trend vector of the previous period, and calculate the vector deflection angle and modulus attenuation rate. If the modulus attenuation rate is lower than the preset efficiency value, the emergency data processing protocol is triggered, setting the target opening of the exhaust valves of all hub nodes to the maximum value, and locking the air supply data of all supply nodes to the minimum value to maintain a slight positive pressure.

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