Energy chemical analysis laboratory ventilation system with updraft and downblast variable air volume system

Abstract

The application discloses an energy chemical analysis laboratory ventilation up exhaust down air supply variable air volume system and relates to the technical field of ventilation control. The system comprises a multi-source sensing module, a hierarchical evaluation module, a working condition diagnosis module, an air volume decision module, a collaborative optimization module and a dynamic updating module. The application obtains multi-dimensional real-time state data of the laboratory, calculates a thermal stratification effectiveness evaluation index and a pollutant aggregation intensity index, identifies a system working condition mode, calculates a reference speed adjustment amount of a supply fan and an exhaust fan, finely adjusts the reference speed adjustment amount according to a thermal buoyancy correction factor and a negative pressure compensation coefficient, generates a final variable frequency drive instruction, quantizes a thermal stratification state into a control basis, couples thermal buoyancy demand and pressure stability constraints in air volume regulation, realizes collaborative control of directional pollutant removal and laboratory negative pressure precise stability, and solves the problems of low pollutant removal efficiency, large negative pressure fluctuation and high energy consumption of the laboratory.

Description

Technical Field

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

[0002] In energy and chemical analysis laboratories, experimental operations involving hazardous substances such as volatile organic compounds and acidic gases place extremely high demands on the ventilation system. It is necessary to rapidly and effectively remove contaminants from the breathing zone of personnel and maintain a stable negative pressure relative to the outside environment at all times to prevent contaminant leakage.

[0003] In related technologies, traditional laboratory ventilation systems often employ mixed ventilation and constant air volume control, or rely solely on single-parameter variable air volume control based on differential pressure sensors. These methods have inherent drawbacks. First, their airflow organization is not conducive to utilizing the principle of thermal stratification for the targeted capture and removal of pollutants, potentially leading to pollutant retention in the breathing zone. Second, when adjusting airflow according to experimental needs, the uncoordinated adjustment of supply and exhaust air can easily cause drastic fluctuations in negative pressure within the laboratory, or even temporary positive pressure leading to pollutant leakage. Finally, because the system cannot simultaneously address the strongly coupled goals of pollutant removal and pressure stability, it often faces a dilemma between safety and energy efficiency, necessitating the trade-off of extremely high energy consumption for basic safety assurance. Therefore, existing technologies struggle to meet the growing demands of modern energy and chemical engineering laboratories for safe, precise, and energy-efficient operation. Summary of the Invention

[0004] This application provides a variable air volume ventilation system for an energy and chemical analysis laboratory, which solves the problems of low pollutant removal efficiency, large negative pressure fluctuations, and high operating energy consumption caused by the disconnect between airflow organization and pressure control in the prior art. It achieves coordinated control of directional pollutant removal and precise and stable negative pressure in the laboratory.

[0005] This application provides a variable air volume system for ventilation in an energy and chemical analysis laboratory, comprising: a multi-source sensing module, a hierarchical evaluation module, an operating condition diagnosis module, an air volume decision module, a collaborative optimization module, and a dynamic update module;

[0006] Among them, the multi-source sensing module is used to acquire multi-dimensional real-time status data collected by a distributed sensor network, and extract feature information about personnel breathing zone, top exhaust zone, supply and exhaust ducts and pressure difference of laboratory partition walls. The stratification assessment module is used to calculate the thermal stratification effectiveness evaluation index and pollutant aggregation intensity index within the laboratory space based on the real-time temperature gradient value and pollutant concentration difference in the feature information. The operating condition diagnostic module is used to compare the thermal stratification effectiveness evaluation index and pollutant aggregation intensity index with the preset stable negative pressure range to identify the current operating condition mode of the system. The air volume decision module is used to calculate the reference speed adjustment amount of the supply fan and the exhaust fan based on the operating mode; wherein, the reference speed adjustment amount includes the exhaust reference speed adjustment amount and the supply fan reference speed adjustment amount; The collaborative optimization module is used to correct the exhaust reference speed adjustment amount based on the reference speed adjustment amount by using a thermal buoyancy correction factor, and to correct the supply reference speed adjustment amount and supply temperature setpoint by using a negative pressure compensation coefficient, thereby generating the final frequency conversion drive command and supply temperature setpoint. The dynamic update module is used to send the frequency converter drive command and the air supply temperature setpoint to the execution terminal, and simultaneously monitor the feedback data to dynamically update the reference speed adjustment.

[0007] Furthermore, the acquisition of multi-dimensional real-time status data collected by a distributed sensor network, and the extraction of feature information regarding the personnel breathing zone, the top exhaust zone, the supply and exhaust ducts, and the pressure difference of the laboratory partition walls, includes: Receives temperature data and pollutant concentration data from sensors in the breathing zone of the personnel activity area at the bottom of the laboratory; Simultaneously acquire temperature data and concentration data of accumulated pollutants in the exhaust area of ​​the laboratory top exhaust area sensor; Obtain the real-time pressure difference from sensors on the partition wall between the laboratory and the adjacent corridor; Extract the actual air supply flow rate data collected by the sensors in the air supply duct and the actual exhaust flow rate data collected by the sensors in the exhaust duct; Acquire the operating current signal, operating frequency signal, and fault status bit signal returned by the blower frequency converter and the exhaust fan frequency converter; The data, including breathing zone temperature data, pollutant concentration data, exhaust zone temperature data, accumulated pollutant concentration data, real-time pressure difference, actual supply air flow rate data, actual exhaust air flow rate data, operating current signal, operating frequency signal, and fault status bit signal, are synchronized and calibrated based on the unified system time according to the timestamp information carried by the data itself. They are then combined into a structured data set in a preset order as feature information.

[0008] Furthermore, the step of calculating the thermal stratification effectiveness evaluation index and pollutant aggregation intensity index within the laboratory space based on the real-time temperature gradient value and the pollutant concentration difference in the feature information includes: By subtracting the temperature data of the breathing zone from the temperature data of the exhaust zone, the real-time temperature gradient value in the vertical direction is obtained. The difference in pollutant concentration within a space is calculated by subtracting the pollutant concentration data from the aggregated pollutant concentration data. The thermal stratification effectiveness evaluation index is calculated by multiplying the real-time temperature gradient value with the pollutant concentration difference and dividing by the height constant preset in the laboratory. Based on the rate of change of pollutant concentration data over time, and combined with the deviation of exhaust zone temperature data from the set value, the pollutant accumulation intensity index is calculated by weighted summation.

[0009] Furthermore, the comparison of the thermal stratification effectiveness evaluation index, pollutant aggregation intensity index, and preset stable negative pressure range to identify the current operating mode of the system includes: Determine whether the real-time pressure difference is within the preset stable negative pressure range, and calculate the instantaneous rate of change of the real-time pressure difference from the center line of the stable negative pressure range; If the thermal stratification effectiveness evaluation index is higher than the first preset threshold and the pollutant aggregation intensity index is lower than the second preset threshold, the system is identified as being in normal operation mode. If the pollutant concentration data exceeds the safety setting range, it is identified that the current system is in the on-demand enhanced ventilation mode, and the target dilution ratio required to be achieved in this mode is calculated; If a fault status signal is received, or if the instantaneous rate of change continuously exceeds the preset fluctuation limit, the system is identified as being in a safety risk condition.

[0010] Furthermore, the calculation of the reference speed adjustment for the supply fan and exhaust fan based on the operating mode includes: The difference between the theoretical exhaust volume and the theoretical supply volume required to maintain the real-time pressure difference within the stable negative pressure range is calculated based on the identified operating mode, and the excess air volume set value is obtained. The difference between the actual exhaust air flow rate and the actual supply air flow rate is used as the measured value of the residual air volume, and the deviation between the residual air volume setpoint and the measured value of the residual air volume is calculated. Using the proportional-integral-differential algorithm, the adjustment amount of the exhaust reference speed of the exhaust fan inverter is calculated based on the deviation. Based on the exhaust reference speed adjustment, the supply fan inverter's supply reference speed adjustment under pressure balance constraints is simultaneously calculated using a preset air volume load characteristic mapping table.

[0011] Furthermore, the process for obtaining the thermal buoyancy correction factor is as follows: Based on the thermal stratification effectiveness evaluation index and the pollutant aggregation intensity index, the driving force demand value for pollutants driven by the thermal plume is calculated. The formula for calculating the driving force requirement is as follows: ; in, Indicators representing the intensity of pollutant aggregation The second preset threshold represents the intensity of pollutant aggregation. This represents the thermal stratification effectiveness evaluation index. This represents the first preset threshold for the thermal stratification effectiveness evaluation index. This represents the calculated driving force requirement value; Multiply the driving force demand value by the adjustment coefficient to obtain the thermal buoyancy correction factor; The formula for calculating the thermal buoyancy correction factor is as follows: ; in, This indicates the contribution ratio of the negative pressure compensation coefficient to the current control. This represents the thermal buoyancy gain coefficient determined by fitting historical data. This represents the final calculated thermal buoyancy correction factor.

[0012] Furthermore, the process for obtaining the negative pressure compensation coefficient is as follows: Obtain the calculated thermal buoyancy correction factor and analyze the disturbance of the indoor pressure field caused by the expected change in exhaust volume due to the thermal buoyancy correction factor. The basic compensation weight is calculated based on the degree to which the real-time pressure difference deviates from the stable negative pressure range; The disturbance is used as a feedback input to perform nonlinear correction on the basic compensation weight, thereby generating the negative pressure compensation coefficient.

[0013] Furthermore, the step of sending the variable frequency drive command and the supply air temperature setpoint to the execution terminal, and simultaneously monitoring the feedback data to dynamically update the reference speed adjustment, includes: Send the air supply frequency command to the air supply fan inverter and the exhaust frequency command to the exhaust fan inverter; Based on feedback from the pollutant accumulation intensity index, if the rate of decrease in the top concentration is found to be lower than expected, the supply air temperature setpoint will be reduced. Within the preset observation period after the command is executed, the multi-source sensing module, the hierarchical evaluation module, and the operating condition diagnosis module run synchronously. By comparing the real-time pressure difference, pollutant concentration data, and the evolution curve of the thermal stratification effectiveness evaluation index before and after the command is issued, the attenuation rate of the control deviation is calculated, and the adjustment amount of the reference speed is dynamically updated according to the attenuation rate.

[0014] Furthermore, an energy and chemical analysis laboratory ventilation system with top exhaust and bottom intake variable air volume also includes a transient disturbance feedforward suppression module; The transient disturbance feedforward suppression module is used to acquire the instantaneous personnel displacement vectors collected by the smart home visual nodes inside the laboratory; Based on the instantaneous personnel displacement vector, the moving velocity of the disturbance source and the spatial angle between the moving direction of the disturbance source and the axis of the dominant airflow of the system are extracted; The predicted value of transient dynamic pressure distortion is calculated based on the moving speed of the disturbance source and the spatial angle. The formula is as follows: ; in, This is the predicted value for transient dynamic pressure distortion. To preset the kinetic energy dissipation decay constant, air density, The moving speed of the disturbance source. Angle in space The windward area is the characteristic of the disturbance source. For spatial volume; Based on the transient dynamic pressure distortion prediction value, a feedforward air volume compensation base is generated, and the feedforward air volume compensation base is superimposed on the reference speed adjustment amount to trigger the exhaust fan to accelerate in advance before the real-time pressure difference fluctuates.

[0015] Furthermore, in an energy and chemical analysis laboratory ventilation system with top-exhaust and bottom-intake variable air volume, a transient disturbance feedforward suppression module is also used to execute an adaptive correction process, including: Within the observation time window after the pre-acceleration action is completed, the actual peak deviation of the real-time pressure difference from the center line of the stable negative pressure range is continuously recorded. The actual peak deviation is compared with the historical average peak deviation when the system does not introduce feedforward compensation, and the feedforward suppression effectiveness index is calculated. The formula is as follows: ; in, The feedforward inhibition efficiency index This represents the historical average peak deviation. This represents the actual peak deviation. The dimensionless delay time from the occurrence of the disturbance to the recovery of system pressure to stability; If the feedforward suppression efficiency index is lower than the set efficiency lower limit, the preset kinetic energy dissipation attenuation constant used in the next calculation of the transient dynamic pressure distortion prediction value is updated according to the magnitude of the actual peak deviation, so as to construct a closed-loop disturbance rejection system.

[0016] 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 variable air volume (VAV) ventilation system for an energy and chemical analysis laboratory, which acquires multi-dimensional real-time status data collected by a distributed sensor network and extracts feature information; calculates a thermal stratification effectiveness evaluation index and a pollutant aggregation intensity index based on the feature information; compares the above indices and indicators with a preset stable negative pressure range to identify the operating mode; calls a control algorithm set based on the excess air volume control method and combines it with the operating mode to calculate the reference speed adjustment of the supply and exhaust fans; based on the reference adjustment, introduces a thermal buoyancy correction factor and a negative pressure compensation coefficient for fine-tuning, and generates the final control command; sends the command to the execution layer and monitors the feedback to dynamically update the reference speed adjustment.

[0017] In this process, by calculating the thermal stratification effectiveness evaluation index and pollutant aggregation intensity index in real time, the airflow organization efficiency and pollutant spatial distribution risk are transformed into clear control parameters, enabling ventilation control to respond more accurately to the dynamic changes in the experimental process.

[0018] Furthermore, when generating exhaust fan speed adjustment commands, a thermal buoyancy correction factor is used to respond to the thermal stratification requirement and enhance the upward removal of pollutants. Simultaneously, when generating supply fan speed compensation commands, a negative pressure compensation coefficient is used to predict and offset disturbances to laboratory pressure caused by changes in airflow. This ensures that while enhancing the targeted removal of pollutants, the laboratory's negative pressure remains stable, avoiding the sacrifice of one objective for the sake of another.

[0019] Furthermore, by ensuring safety under high-risk operating conditions through the emergency execution module, and by combining real-time monitoring and dynamic adjustment of multi-source data, the entire ventilation system can simultaneously achieve efficient removal of pollutants, precise control of negative pressure, and reduction of operating energy consumption while ensuring safety, thereby improving the overall environmental control efficiency and economy of the energy and chemical analysis laboratory. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of a variable air volume ventilation system with top exhaust and bottom intake provided for an embodiment of this application in an energy and chemical analysis laboratory. Detailed Implementation

[0021] This application provides a variable air volume (VAV) ventilation system for an energy and chemical analysis laboratory, addressing the problems of low pollutant removal efficiency, large negative pressure fluctuations, and high operating energy consumption caused by the disconnect between airflow organization and pressure control in existing technologies. The system acquires multi-dimensional real-time status data of the laboratory through a multi-source sensing module. A stratified evaluation module calculates the thermal stratification effectiveness evaluation index and pollutant aggregation intensity index, which the operating condition diagnosis module uses to identify the system's operating mode. An airflow decision module calculates the baseline speed adjustment for the supply and exhaust fans. A collaborative optimization module further refines the baseline speed adjustment based on a thermal buoyancy correction factor and a negative pressure compensation coefficient, generating the final variable frequency drive command. A dynamic update module issues commands and monitors feedback to dynamically update the baseline speed adjustment, thereby quantifying the thermal stratification state as a control basis. It couples thermal buoyancy requirements and pressure stability constraints into airflow regulation, achieving coordinated control of directional pollutant removal and precise, stable negative pressure in the laboratory.

[0022] 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.

[0023] like Figure 1 As shown in the embodiment of this application, a variable air volume system for ventilation in an energy and chemical analysis laboratory with top exhaust and bottom intake is provided, including: a multi-source sensing module, a hierarchical evaluation module, an operating condition diagnosis module, an air volume decision module, a collaborative optimization module, and a dynamic update module.

[0024] Among them, the multi-source sensing module is used to acquire multi-dimensional real-time status data collected by a distributed sensor network, and extract feature information about personnel breathing zone, top exhaust zone, supply and exhaust ducts and pressure difference of laboratory partition walls.

[0025] The stratification assessment module is used to calculate the thermal stratification effectiveness evaluation index and pollutant aggregation intensity index within the laboratory space based on the real-time temperature gradient value and the pollutant concentration difference in the feature information.

[0026] The operating condition diagnostic module is used to compare the thermal stratification effectiveness evaluation index and pollutant aggregation intensity index with the preset stable negative pressure range to identify the current operating condition mode of the system.

[0027] The air volume decision module is used to call a set of control algorithms based on the excess air volume control method, and calculate the base speed adjustment of the supply fan and exhaust fan in combination with the operating mode.

[0028] The collaborative optimization module is used to correct the exhaust reference speed adjustment amount based on the reference speed adjustment amount by using a thermal buoyancy correction factor, and to correct the supply reference speed adjustment amount and supply air temperature setpoint by using a negative pressure compensation coefficient, thereby generating the final frequency conversion drive command and supply air temperature setpoint.

[0029] The specific implementation method of the fine-tuning is as follows: the collaborative optimization module first utilizes the thermal buoyancy correction factor. Adjustment amount of exhaust reference speed Perform multiplication correction to obtain the final incremental command for the exhaust fan inverter drive. Simultaneously utilizing the negative pressure compensation coefficient Adjustment amount of air supply reference speed Perform multiplication correction to obtain the increment of the blower frequency converter drive command. In addition, the negative pressure compensation coefficient It is also used for the nominal supply air temperature setpoint. Linear correction is performed to generate the final supply air temperature setpoint. ,in This is the preset temperature compensation coefficient.

[0030] The dynamic update module is used to send the variable frequency drive command and the supply air temperature setpoint to the execution terminal, and synchronously monitor feedback data to dynamically update the reference speed adjustment. In this embodiment, an energy and chemical analysis laboratory ventilation top-exhaust-bottom-in variable air volume system also includes an emergency execution module, which is used to run a safety monitoring thread in parallel in the background and override the current control logic when an emergency condition is triggered. This includes: the monitoring thread continuously scanning gas detector alarm signals, fire alarm system status signals, and manual emergency button trigger level signals; once any alarm signal is detected, immediately interrupting the current normal operation mode or the logic execution of the on-demand enhanced ventilation mode; forcibly sending a shutdown command to the supply fan inverter to shut down the supply air unit to prevent fire spread or air backflow; forcibly sending a full-frequency operation command to the exhaust fan inverter to implement emergency ventilation with maximum air volume, while activating the audible and visual alarm devices in the laboratory and blocking modification permissions for all supply air temperature fine-tuning programs.

[0031] Furthermore, the acquisition of multi-dimensional real-time status data collected by the distributed sensor network, and the extraction of characteristic information regarding the personnel breathing zone, the top exhaust zone, the supply and exhaust ducts, and the pressure difference of the laboratory partition walls, includes: receiving temperature data and pollutant concentration data of the breathing zone from sensors deployed in the personnel activity area at the bottom of the laboratory via a communication interface; simultaneously acquiring temperature data and accumulated pollutant concentration data of the exhaust zone from sensors deployed in the top exhaust zone of the laboratory; acquiring the real-time pressure difference value fed back by a high-precision micro-differential pressure sensor installed on the partition wall between the laboratory and the adjacent corridor; and extracting the actual airflow rate collected by the airflow sensor installed in the supply duct. According to the actual exhaust flow data collected by the exhaust volume sensor installed in the exhaust duct; the operating current signal, operating frequency signal and fault status signal returned by the supply fan inverter and the exhaust fan inverter are obtained; and the breathing zone temperature data, pollutant concentration data, exhaust zone temperature data, accumulated pollutant concentration data, real-time pressure difference, actual supply air flow data, actual exhaust air flow data, operating current signal, operating frequency signal and fault status signal are synchronized and calibrated according to the timestamp information carried by the data itself, with a unified system time as the benchmark, and combined into a structured data set in a preset order as feature information.

[0032] Furthermore, the step of calculating the thermal stratification effectiveness evaluation index and pollutant aggregation intensity index within the laboratory space based on the real-time temperature gradient value and pollutant concentration difference in the feature information includes: obtaining the real-time temperature gradient value in the vertical direction by subtracting the breathing zone temperature data from the exhaust zone temperature data; calculating the pollutant concentration difference within the space by subtracting the pollutant concentration data from the aggregated pollutant concentration data; multiplying the real-time temperature gradient value and the pollutant concentration difference and dividing by the laboratory's preset height constant to calculate the thermal stratification effectiveness evaluation index; and calculating the pollutant aggregation intensity index reflecting the degree of air quality deterioration in the top exhaust zone by weighted summation based on the evolution rate of the aggregated pollutant concentration data over time and the deviation of the exhaust zone temperature data from the set value, wherein the weight allocation is determined based on the pollutant removal time constant in the historical operation records.

[0033] In this embodiment, the formula for calculating the thermal stratification effectiveness evaluation index is as follows: ; in, Temperature data for the exhaust area. For respiratory zone temperature data, In order to collect pollutant concentration data, For pollutant concentration data, The vertical height difference is a constant determined based on measurements taken from the laboratory building drawings. It serves as an index for evaluating the effectiveness of thermal stratification.

[0034] The formula for calculating the pollutant aggregation intensity index is as follows: ; in, Pollutant concentration in the exhaust area The rate of change over time, i.e., the rate of evolution, is determined by... The historical data sequence is obtained by first-order difference calculation; This indicates the reference value for the expected temperature in the exhaust area, preset according to seasonal and process requirements; Indicates temperature data in the exhaust area Relative to its set value The absolute value of the deviation is used to reflect the possible impact of temperature anomalies on pollutant behavior (such as volatilization and diffusion rates). This is an indicator of pollutant accumulation intensity. The higher the pollutant accumulation intensity index, the faster the pollutants accumulate at the top, and the higher the risk of air quality deterioration.

[0035] and These represent weighting coefficients, with units of minutes and degrees Celsius, respectively. These two coefficients are determined through analysis of historical system operating data: specifically, by collecting pollutant removal time constants under different events during historical operation. That is, the time required for the concentration to decay from its peak to a safe level, and the corresponding... Average and The average value was fitted using multiple linear regression analysis. and The value of makes and Strongly correlated, for example, The larger, Generally, the shorter the length, the higher the risk. This reflects the weighting of the concentration change rate in relation to the risk of clustering. This reflects the weighting of temperature deviation in the risk of clustering.

[0036] Furthermore, the comparison of the thermal stratification effectiveness evaluation index, the pollutant aggregation intensity index, and the preset stable negative pressure range to identify the current operating mode of the system includes: determining whether the real-time pressure difference is within the preset stable negative pressure range, and calculating the instantaneous rate of change of the real-time pressure difference from the center line of the stable negative pressure range; if the thermal stratification effectiveness evaluation index is higher than a first preset threshold and the pollutant aggregation intensity index is lower than a second preset threshold, the system is identified as being in a normal operating mode; if the pollutant concentration data exceeds the safety setting range, the system is identified as being in an on-demand enhanced ventilation mode, and the target dilution ratio required to be achieved in this mode is calculated; if a fault status bit signal is received from the execution terminal, or the instantaneous rate of change continuously exceeds the preset fluctuation limit value, the system is identified as being in a safety risk condition.

[0037] In this embodiment, the specific numerical range of the preset stable negative pressure range is determined based on the negative pressure requirements in the general safety design specifications for laboratories involving hazardous substances. The first preset threshold, namely the thermal stratification effectiveness evaluation index threshold, is obtained through statistical analysis of operating data during the initial system commissioning phase. The second preset threshold, namely the pollutant aggregation intensity index threshold, is set based on the permissible concentration specified in the occupational exposure limit standards for hazardous substances in the workplace, combined with empirical values ​​of the concentration rise rate acceptable in engineering. The safe setting range for pollutant concentration in the breathing zone is directly adopted from the highest permissible concentration value or short-term exposure permissible concentration value specified in occupational health standards for this type of pollutant. The target dilution ratio is a dynamic value calculated in real time, obtained by dividing the measured value of the current pollutant concentration in the breathing zone by the aforementioned safety limit value, and does not need to be preset. The preset fluctuation limit value is determined by long-term monitoring of pressure change rate data under normal, uninterrupted laboratory operation, and statistical analysis of the data sequence, with the high-order value in the statistical results used as a reference benchmark.

[0038] Furthermore, the calculation of the reference speed adjustment of the supply fan and exhaust fan based on the operating mode includes: calculating the difference between the theoretical exhaust volume and the theoretical supply volume required to maintain the real-time pressure difference within the stable negative pressure range according to the identified operating mode, and obtaining the residual air volume setpoint; using the difference between the actual exhaust flow rate data and the actual supply flow rate data as the measured residual air volume value, and calculating the deviation between the residual air volume setpoint value and the measured residual air volume value; using the proportional-integral-differential algorithm, calculating the exhaust reference speed adjustment of the exhaust fan inverter based on the deviation; and based on the exhaust reference speed adjustment, simultaneously calculating the supply reference speed adjustment of the supply fan inverter under the pressure balance constraint through a preset air volume load characteristic mapping table, to ensure that the supply and exhaust fans operate in a consistent manner at the reference level.

[0039] In this embodiment, the step of obtaining the reference speed adjustment amount specifically includes: Step 1: Determine the excess air volume setpoint: Calculate the target excess air volume setpoint based on the operating mode. It is used to maintain the target negative pressure.

[0040] Normal mode: .in The excess air volume coefficient per unit area is calculated based on the design air exchange rate and room volume. This represents the floor area of ​​the laboratory.

[0041] Enhanced ventilation mode: .in , for the measured concentration in the respiratory zone With safety limits The ratio of .

[0042] Step 2, Calculate the residual air volume deviation: Calculate the measured value of the residual air volume. ,in and These are the measured values ​​from the duct airflow sensor.

[0043] Calculate the deviation .

[0044] Step 3: Calculate the baseline adjustment of the exhaust fan using PID (Proportional-Integral-Derivative) formula: Calculate the baseline speed adjustment of the exhaust fan using the discrete PID formula. : .

[0045] in, The PID gain coefficient is obtained by tuning using the Ziegler-Nichols method during system debugging. To control the duration of the control cycle, j is the summation index of the control cycle, and t is the total number of control cycles.

[0046] Step 4: Calculate the baseline adjustment amount for the supply fan by referring to the table: Using a preset airflow load characteristic mapping table, calculate the adjustment amount for the exhaust fan. Determine the adjustment amount of the blower's reference speed. .

[0047] The preset airflow load characteristic mapping table was established during system commissioning through the following tests: The supply fan frequency was fixed, and the exhaust fan frequency was adjusted to stabilize the laboratory pressure difference at the target value. Multiple sets of corresponding values ​​were recorded. Frequency pairs are tabulated or fitted using a function. During runtime, the target frequency of the exhaust fan is used. The target frequency of the blower can be obtained by referring to the table. ,but When no corresponding value is found in the table, linear interpolation is used for calculation.

[0048] By combining calculation and table lookup, the reference speed adjustment amount for the coordinated operation of the supply and exhaust fans was determined.

[0049] Furthermore, based on the reference speed adjustment, a thermal buoyancy correction factor and a negative pressure compensation coefficient are introduced for further fine-tuning to generate the final variable frequency drive command and supply air temperature setpoint. The calculation process for the thermal buoyancy correction factor is as follows: obtain the current negative pressure compensation coefficient and calculate the contribution ratio of the negative pressure compensation coefficient to the total exhaust volume of the system; calculate the driving force requirement value for driving pollutants upward by the thermal plume according to the thermal stratification effectiveness evaluation index and pollutant aggregation intensity index; multiply the driving force requirement value by an adjustment coefficient that is negatively correlated with the contribution ratio to obtain the thermal buoyancy correction factor, which is used to characterize the exhaust gain caused by thermal effects in the exhaust fan speed adjustment; and perform weighted correction on the exhaust reference speed adjustment amount through the thermal buoyancy correction factor. If the driving force requirement value increases, the final frequency setting command of the exhaust fan is correspondingly increased.

[0050] In this embodiment, the formula for calculating the driving force requirement is as follows: ; in, Indicators representing the intensity of pollutant aggregation The second preset threshold represents the intensity of pollutant aggregation. This represents the thermal stratification effectiveness evaluation index. This represents the first preset threshold for the thermal stratification effectiveness evaluation index. This represents the calculated driving force demand value.

[0051] The formula for calculating the thermal buoyancy correction factor is as follows: ; in, This indicates the contribution ratio of the negative pressure compensation coefficient to the current control. This represents the thermal buoyancy gain coefficient determined by fitting historical data. This represents the final calculated thermal buoyancy correction factor.

[0052] Furthermore, based on the reference speed adjustment, the thermal buoyancy correction factor and negative pressure compensation coefficient are obtained for further fine-tuning to generate the final variable frequency drive command and supply air temperature setpoint. The calculation process of the negative pressure compensation coefficient is as follows: the calculated thermal buoyancy correction factor is obtained, and the disturbance of the indoor pressure field caused by the expected change in exhaust volume due to the thermal buoyancy correction factor is analyzed; the basic compensation weight is calculated according to the degree of deviation of the real-time pressure difference from the stable negative pressure range; the disturbance is used as feedback input to perform nonlinear correction on the basic compensation weight, thereby generating the negative pressure compensation coefficient, ensuring that the system can predict and offset the risk of excessive negative pressure when thermally driven exhaust is enhanced; the negative pressure compensation coefficient is used to fine-tune the supply air reference speed adjustment, and the pressure fluctuation is dynamically suppressed by changing the final frequency setting command of the supply fan.

[0053] In this embodiment, the formula for calculating the disturbance is as follows: ; in, This represents the laboratory permeability coefficient obtained through a door opening / closing test. This represents the expected change in exhaust volume due to thermal buoyancy correction. Indicates the volume of the laboratory. This represents the estimated pressure disturbance.

[0054] The formula for calculating the basic compensation weight is as follows: ; in, This represents the preset pressure deviation sensitivity coefficient. This represents the real-time pressure difference. This represents the center value of the preset stable negative pressure range. This represents the calculated basic compensation weight.

[0055] The formula for calculating the negative pressure compensation coefficient is as follows: ; in, This indicates the preset disturbance compensation gain. Represents a symbolic function. This indicates the preset maximum allowable predicted disturbance. This indicates the preset upper limit of the compensation coefficient. Represents a saturation function. This represents the final calculated negative pressure compensation coefficient.

[0056] Furthermore, the step of sending the frequency conversion drive command and the supply air temperature setpoint to the execution terminal, and simultaneously monitoring feedback data to dynamically update the reference speed adjustment, includes: sending a supply air frequency command to the supply fan frequency converter and an exhaust air frequency command to the exhaust fan frequency converter through the industrial control communication network; based on the feedback of the pollutant accumulation intensity index, if it is found that the rate of decrease in the top concentration is lower than expected, the supply air temperature setpoint is reduced and sent to the fresh air treatment unit to enhance the buoyancy driving force of the bottom fresh air lake by increasing the temperature difference between the supply air and the indoor air; within the preset observation period after the command is executed, the multi-source sensing module, the stratified evaluation module, and the operating condition diagnosis module are run simultaneously; by comparing the real-time pressure difference, pollutant concentration data, and the evolution curve of the thermal stratification effectiveness evaluation index before and after the command is issued, the attenuation rate of the control deviation is calculated, and the reference speed adjustment is dynamically updated according to the attenuation rate.

[0057] In this embodiment, if the pollutant removal effect is found to be unsatisfactory and the thermal stratification is poor, an additional supply air temperature reduction command will be generated to physically enhance the thermal buoyancy effect by increasing the temperature difference between the supply air and the room.

[0058] Furthermore, a variable air volume (VAV) ventilation system for an energy and chemical analysis laboratory, with top exhaust and bottom intake, also includes a transient disturbance feedforward suppression module. This module acquires instantaneous personnel displacement vectors collected by smart home visual nodes within the laboratory. Based on these instantaneous personnel displacement vectors, it extracts the moving velocity of the disturbance source and the spatial angle between the moving direction of the disturbance source and the system's dominant airflow axis. Based on the moving velocity of the disturbance source and the spatial angle, it calculates the predicted value of transient dynamic pressure distortion, using the following formula: ; in, This is the predicted value for transient dynamic pressure distortion. To preset the kinetic energy dissipation decay constant, air density, The moving speed of the disturbance source. Angle in space The windward area is the characteristic of the disturbance source. For spatial volume.

[0059] Based on the transient dynamic pressure distortion prediction value, a feedforward air volume compensation base is generated, and the feedforward air volume compensation base is superimposed on the reference speed adjustment amount to trigger the exhaust fan to accelerate in advance before the real-time pressure difference fluctuates.

[0060] In this embodiment, the predicted value of transient dynamic pressure distortion is input into a preset feedforward compensation mapping table or linear gain function, and converted into the required increase in Hertz frequency value for the exhaust fan. When it is sensed that a person is rapidly approaching the fume hood or laboratory door, before the differential pressure sensor generates a data jump, the Hertz frequency value is directly fed forward and superimposed into the exhaust fan reference speed adjustment command, achieving proactive "disturbance resistance".

[0061] Furthermore, in an energy and chemical analysis laboratory ventilation system with top-exhaust and bottom-intake variable air volume, the transient disturbance feedforward suppression module is also used to execute an adaptive correction process, including: continuously recording the actual peak deviation of the real-time pressure difference from the center line of the stable negative pressure range within the observation time window after the pre-increase execution action is completed; comparing the actual peak deviation with the historical average peak deviation when the system does not introduce feedforward compensation, and calculating the feedforward suppression effectiveness index, the formula of which is: ; in, The feedforward inhibition efficiency index This represents the historical average peak deviation. This represents the actual peak deviation. The dimensionless delay time from the occurrence of the disturbance to the recovery of system pressure stability; if the feedforward suppression efficiency index is lower than the set efficiency lower limit, the preset kinetic energy dissipation attenuation constant used in the next calculation of the transient dynamic pressure distortion prediction value is updated according to the magnitude of the actual peak deviation, so as to construct a closed-loop disturbance rejection system.

[0062] In this embodiment, if the actual peak deviation shows a tendency for positive pressure overflow, indicating insufficient compensation, then the preset kinetic energy dissipation attenuation constant will be used. Multiply by the gain factor (e.g., 1.05); conversely, if excessive negative pressure suction is observed, indicating overcompensation, multiply by the attenuation factor (e.g., 0.95). This is to allow for flexibility in parameter settings. The update sets physical upper and lower limit protection zones to prevent infinite divergence caused by abnormal noise data (such as foreign objects blocking smart home visual nodes), ensuring that the exhaust system still has a safety baseline under extreme conditions.

[0063] All the above formulas use dimensionless numerical calculations. The formulas are derived from software simulations based on a large amount of collected data, and the preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0064] 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, as a program product.

[0065] 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 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.

[0066] 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.

[0067] 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.

[0068] 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 variable air volume (VAV) ventilation system for an energy and chemical analysis laboratory, characterized in that, include: Multi-source sensing module, hierarchical evaluation module, operating condition diagnosis module, air volume decision module, collaborative optimization module, dynamic update module; Among them, the multi-source sensing module is used to acquire multi-dimensional real-time status data collected by a distributed sensor network, and extract feature information about personnel breathing zone, top exhaust zone, supply and exhaust ducts and pressure difference of laboratory partition walls. The stratification assessment module is used to calculate the thermal stratification effectiveness evaluation index and pollutant aggregation intensity index within the laboratory space based on the real-time temperature gradient value and pollutant concentration difference in the feature information. The operating condition diagnostic module is used to compare the thermal stratification effectiveness evaluation index and pollutant aggregation intensity index with the preset stable negative pressure range to identify the current operating condition mode of the system. The air volume decision module is used to calculate the reference speed adjustment amount of the supply fan and the exhaust fan based on the operating mode; wherein, the reference speed adjustment amount includes the exhaust reference speed adjustment amount and the supply fan reference speed adjustment amount; The collaborative optimization module is used to correct the exhaust reference speed adjustment amount based on the reference speed adjustment amount by using a thermal buoyancy correction factor, and to correct the supply reference speed adjustment amount and supply temperature setpoint by using a negative pressure compensation coefficient, thereby generating the final frequency conversion drive command and supply temperature setpoint. The dynamic update module is used to send the frequency converter drive command and the air supply temperature setpoint to the execution terminal, and simultaneously monitor the feedback data to dynamically update the reference speed adjustment.

2. The variable air volume ventilation system for an energy and chemical analysis laboratory as described in claim 1, characterized in that, The acquisition of multi-dimensional real-time status data collected by a distributed sensor network, and the extraction of feature information regarding the personnel breathing zone, the top exhaust zone, the supply and exhaust ducts, and the pressure difference of the laboratory partition walls, includes: Receives temperature data and pollutant concentration data from sensors in the breathing zone of the personnel activity area at the bottom of the laboratory; Simultaneously acquire temperature data and concentration data of accumulated pollutants in the exhaust area of ​​the laboratory top exhaust area sensor; Obtain the real-time pressure difference from sensors on the partition wall between the laboratory and the adjacent corridor; Extract the actual air supply flow rate data collected by the sensors in the air supply duct and the actual exhaust flow rate data collected by the sensors in the exhaust duct; Acquire the operating current signal, operating frequency signal, and fault status bit signal returned by the blower frequency converter and the exhaust fan frequency converter; The data, including temperature data of the breathing zone, pollutant concentration data, temperature data of the exhaust zone, concentration data of accumulated pollutants, real-time pressure difference, actual air supply flow rate data, actual exhaust flow rate data, operating current signal, operating frequency signal, and fault status bit signal, are synchronized and calibrated based on the timestamp information carried by the data itself, using a unified system time as a reference. They are then combined into a structured data set in a preset order as feature information.

3. The variable air volume ventilation system for an energy and chemical analysis laboratory as described in claim 1, characterized in that, The calculation of the thermal stratification effectiveness evaluation index and pollutant aggregation intensity index within the laboratory space based on the real-time temperature gradient value and pollutant concentration difference in the feature information includes: By subtracting the temperature data of the breathing zone from the temperature data of the exhaust zone, the real-time temperature gradient value in the vertical direction is obtained. The difference in pollutant concentration within a space is calculated by subtracting the pollutant concentration data from the aggregated pollutant concentration data. The thermal stratification effectiveness evaluation index is calculated by multiplying the real-time temperature gradient value with the pollutant concentration difference and dividing by the height constant preset in the laboratory. Based on the rate of change of pollutant concentration data over time, and combined with the deviation of exhaust zone temperature data from the set value, the pollutant accumulation intensity index is calculated by weighted summation.

4. The variable air volume ventilation system for an energy and chemical analysis laboratory as described in claim 1, characterized in that, The process of comparing the thermal stratification effectiveness evaluation index and pollutant aggregation intensity index with a preset stable negative pressure range to identify the current operating mode of the system includes: Determine whether the real-time pressure difference is within the preset stable negative pressure range, and calculate the instantaneous rate of change of the real-time pressure difference from the center line of the stable negative pressure range; If the thermal stratification effectiveness evaluation index is higher than the first preset threshold and the pollutant aggregation intensity index is lower than the second preset threshold, the system is identified as being in normal operation mode. If the pollutant concentration data exceeds the safety setting range, it is identified that the current system is in the on-demand enhanced ventilation mode, and the target dilution ratio required to be achieved in this mode is calculated; If a fault status signal is received, or if the instantaneous rate of change continuously exceeds the preset fluctuation limit, the system is identified as being in a safety risk condition.

5. The variable air volume ventilation system for an energy and chemical analysis laboratory as described in claim 1, characterized in that, The calculation of the reference speed adjustment for the supply fan and exhaust fan based on the operating mode includes: The difference between the theoretical exhaust volume and the theoretical supply volume required to maintain the real-time pressure difference within the stable negative pressure range is calculated based on the identified operating mode, and the excess air volume set value is obtained. The difference between the actual exhaust air flow rate and the actual supply air flow rate is used as the measured value of the residual air volume, and the deviation between the residual air volume setpoint and the measured value of the residual air volume is calculated. Using the proportional-integral-differential algorithm, the adjustment amount of the exhaust reference speed of the exhaust fan inverter is calculated based on the deviation. Based on the exhaust reference speed adjustment, the supply fan inverter's supply reference speed adjustment under pressure balance constraints is simultaneously calculated using a preset air volume load characteristic mapping table.

6. The variable air volume ventilation system for an energy and chemical analysis laboratory as described in claim 1, characterized in that, The process for obtaining the thermal buoyancy correction factor is as follows: Based on the thermal stratification effectiveness evaluation index and the pollutant aggregation intensity index, the driving force demand value for pollutants driven by the thermal plume is calculated. The formula for calculating the driving force requirement is as follows: ； in, Indicators representing the intensity of pollutant aggregation The second preset threshold represents the intensity of pollutant aggregation. This represents the thermal stratification effectiveness evaluation index. This represents the first preset threshold for the thermal stratification effectiveness evaluation index. This represents the calculated driving force requirement value; Multiply the driving force demand value by the adjustment coefficient to obtain the thermal buoyancy correction factor; The formula for calculating the thermal buoyancy correction factor is as follows: ； in, This indicates the contribution ratio of the negative pressure compensation coefficient to the current control. This represents the thermal buoyancy gain coefficient determined by fitting historical data. This represents the final calculated thermal buoyancy correction factor.

7. The variable air volume ventilation system for an energy and chemical analysis laboratory as described in claim 1, characterized in that, The process for obtaining the negative pressure compensation coefficient is as follows: Obtain the calculated thermal buoyancy correction factor and analyze the disturbance of the indoor pressure field caused by the expected change in exhaust volume due to the thermal buoyancy correction factor. The basic compensation weight is calculated based on the degree to which the real-time pressure difference deviates from the stable negative pressure range; The disturbance is used as a feedback input to perform nonlinear correction on the basic compensation weight, thereby generating the negative pressure compensation coefficient.

8. The variable air volume ventilation system for an energy and chemical analysis laboratory as described in claim 1, characterized in that, The step of sending the variable frequency drive command and the supply air temperature setpoint to the execution terminal, and simultaneously monitoring the feedback data to dynamically update the reference speed adjustment, includes: Send the air supply frequency command to the air supply fan inverter and the exhaust frequency command to the exhaust fan inverter; Based on feedback from the pollutant accumulation intensity index, if the rate of decrease in the top concentration is found to be lower than expected, the supply air temperature setpoint will be reduced. Within the preset observation period after the command is executed, the multi-source sensing module, the hierarchical evaluation module, and the operating condition diagnosis module run synchronously. By comparing the real-time pressure difference, pollutant concentration data, and the evolution curve of the thermal stratification effectiveness evaluation index before and after the command is issued, the attenuation rate of the control deviation is calculated, and the adjustment amount of the reference speed is dynamically updated according to the attenuation rate.

9. The variable air volume ventilation system for an energy and chemical analysis laboratory as described in claim 1, characterized in that, It also includes a transient disturbance feedforward suppression module; The transient disturbance feedforward suppression module is used to acquire the instantaneous personnel displacement vectors collected by the smart home visual nodes inside the laboratory; Based on the instantaneous personnel displacement vector, the moving velocity of the disturbance source and the spatial angle between the moving direction of the disturbance source and the axis of the dominant airflow of the system are extracted; The predicted value of transient dynamic pressure distortion is calculated based on the moving speed of the disturbance source and the spatial angle. The formula is as follows: ； in, This is the predicted value for transient dynamic pressure distortion. To preset the kinetic energy dissipation decay constant, air density, The moving speed of the disturbance source. Angle in space The windward area is the characteristic of the disturbance source. For spatial volume; Based on the transient dynamic pressure distortion prediction value, a feedforward air volume compensation base is generated, and the feedforward air volume compensation base is superimposed on the reference speed adjustment amount to trigger the exhaust fan to accelerate in advance before the real-time pressure difference fluctuates.

10. The variable air volume ventilation system for an energy and chemical analysis laboratory as described in claim 9, characterized in that, The transient disturbance feedforward suppression module is also used to perform an adaptive correction process, including: Within the observation time window after the pre-acceleration action is completed, the actual peak deviation of the real-time pressure difference from the center line of the stable negative pressure range is continuously recorded. The actual peak deviation is compared with the historical average peak deviation when the system does not introduce feedforward compensation, and the feedforward suppression effectiveness index is calculated. The formula is as follows: ； in, The feedforward inhibition efficiency index This represents the historical average peak deviation. This represents the actual peak deviation. The dimensionless delay time from the occurrence of the disturbance to the recovery of system pressure to stability; If the feedforward suppression efficiency index is lower than the set efficiency lower limit, the preset kinetic energy dissipation attenuation constant used in the next calculation of the transient dynamic pressure distortion prediction value is updated according to the magnitude of the actual peak deviation, so as to construct a closed-loop disturbance rejection system.

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