Remote intelligent control method for smoke exhaust fireproof valve based on Internet of Things

Abstract

The invention discloses a remote intelligent control method for a smoke exhaust fireproof valve based on the Internet of Things, and the method comprises the steps: determining a to-be-closed valve set when a remote management platform receives a multi-valve closing request of the same air pipe section, the air pipe pressure difference measurement value of the position where each valve is located, the rated output torque of the electric actuating mechanism and the running state of the smoke exhaust fan are obtained; based on a pre-stored air pipe system pipe network model, pipe network steady-state air volume balance calculation is conducted in combination with the opening degree states of all the valves, aerodynamic loads borne by valve plates of all the valves are obtained, and the load ratio is calculated; the closing turns of all the valves are determined in a turn-by-turn iteration mode according to the load ratio from large to small; and finally, closing and starting delay parameters are generated according to the closing turns and the full-stroke closing time of all the valves and are issued to local controllers of all the valves so as to control all the valves to be closed in sequence. According to the method, the reliability and control reasonability of the multi-valve linkage closing process can be improved.

Description

Technical Field

[0001] This application relates to the field of intelligent smoke exhaust control technology, and more specifically, to a remote intelligent control method for smoke exhaust fire dampers based on the Internet of Things. Background Technology

[0002] In ventilation and smoke extraction systems of underground spaces such as subway stations, highway tunnels, and underground commercial complexes, smoke exhaust fire dampers are typically installed along the same main or branch pipes to isolate smoke from target duct sections in emergency situations such as fires. With the application of Internet of Things (IoT) technology in fire protection and HVAC systems, smoke exhaust fire dampers can establish connections with remote management platforms via local controllers and communication links. The remote management platform can obtain fan operating status and valve operating information, and issue linkage control commands to relevant valves.

[0003] In existing technologies, when multiple smoke exhaust fire dampers in the same duct section need to be shut down in a coordinated manner, a control method that simultaneously issues a shut-off command to all valves is typically used. While this method is simple to implement, during the near-simultaneous shut-off process, the valves that reach the fully closed position first alter the original duct flow pattern, causing a redistribution of airflow within the duct. This increases the pressure difference across the valves that are not yet fully closed, significantly increasing the aerodynamic load on the valve plates. When this load exceeds the output capacity of the electric actuator, the valves may stall during their closing stroke, failing to reach the fully closed position, thus affecting the smoke isolation effect and the reliability of the system linkage. These problems are particularly pronounced in scenarios with a large number of valves, complex duct network structures, and continuous fan operation within the same duct system.

[0004] Therefore, it is evident that existing technologies still lack a technical solution for reasonably controlling the closing process of multiple smoke exhaust fire dampers in multi-valve linkage closing scenarios, which can combine the airflow status of the duct, the load on the valves, and the capabilities of the actuators. Summary of the Invention

[0005] This application provides a remote intelligent control method for smoke exhaust fire dampers based on the Internet of Things, so as to at least solve some of the technical problems existing in the related technologies mentioned above.

[0006] According to a first aspect of the embodiments of this application, a remote intelligent control method for a smoke exhaust fire damper based on the Internet of Things is provided, including: When the remote management platform receives multiple valve closure requests in the same duct section, it determines the set of valves to be closed and obtains the duct pressure difference measurement value at the current location of each valve in the set, the rated output torque of the electric actuator of each valve, and the current operating status of the smoke exhaust fan. The remote management platform is based on a pre-stored duct system network model. It combines the duct differential pressure measurement value, the current opening status of each valve and the operating status of the smoke exhaust fan. Through steady-state air volume balance calculation of the network, it obtains the aerodynamic load borne by each valve plate and calculates the load ratio of each valve based on the aerodynamic load. The remote management platform determines the closing round of each valve in descending order of load ratio using an iterative method. In each round, the valve with the largest load ratio among the remaining valves is selected as the closing target for that round. After setting the closing target for that round to the closed state in the pipeline model, the pipeline steady-state air volume balance calculation is re-executed to update the load ratio of the remaining valves, and the next round of selection is entered until all valves are assigned to the corresponding round. The remote management platform generates a shutdown start delay parameter for each valve based on the order of each cycle and the full stroke closing time of each valve's electric actuator. The shutdown start delay parameter is then sent to the local controller of each valve via the communication link along with the shutdown command. Each local controller starts the electric actuator sequentially to perform the shutdown action according to the shutdown start delay parameter it receives.

[0007] As an optional approach, the load ratio is calculated as follows: multiply the pneumatic load of each valve by the lever arm length between the valve plate rotation center and the equivalent point of application of the pneumatic load to obtain the pneumatic resistance torque, and divide the pneumatic resistance torque by the rated output torque of the electric actuator of the valve to obtain the load ratio of the valve.

[0008] As an optional approach, in the iterative round-by-round method, after selecting the valve with the largest load ratio as the shut-off target for each round, the method further includes performing a parallel shut-off determination on the remaining valves: including valves with load ratios lower than a preset torque margin coefficient among the remaining valves in the current round as shut-off targets, and starting their shut-off simultaneously with the valve with the largest load ratio in the current round; after setting all shut-off targets in the pipeline model to the closed state simultaneously, the pipeline steady-state airflow balance calculation is re-executed to update the load ratios of the remaining valves, wherein the torque margin coefficient is a positive number between 0 and 1.

[0009] As an optional approach, the shutdown start delay parameter is generated as follows: the shutdown start delay parameter of the first round of shutdown objects is zero; from the second round onwards, the shutdown start delay parameter of each round of shutdown objects is equal to the cumulative value of the total shutdown time of the shutdown objects in the previous rounds.

[0010] As an optional approach, a stabilization waiting time is added between the shutdown start delay parameters of two adjacent shutdown objects. The stabilization waiting time is determined based on the time required for the airflow in the pipe to transition from a transient state to a steady state after the previous shutdown object is shut down.

[0011] As an optional solution, when issuing a shutdown command, the remote management platform sends the estimated differential pressure value for each valve corresponding to the cycle calculated by the steady-state airflow balance of the pipeline network to the local controller of each valve along with the shutdown command. After initiating the shutdown action, each local controller continuously collects the measured differential pressure value on both sides of the valve plate and compares the measured differential pressure value with the estimated differential pressure value. When the deviation of the measured differential pressure value from the estimated differential pressure value exceeds the preset deviation tolerance, a differential pressure deviation alarm is sent to the remote management platform.

[0012] As an optional solution, after receiving the differential pressure deviation alarm, the remote management platform uses the measured differential pressure value carried in the alarm as input to re-execute the steady-state air volume balance calculation of the pipeline network and update the load ratio of each valve in the subsequent rounds that have not yet been started and shut down. If the updated load ratio exceeds the preset torque margin coefficient, the remote management platform re-executes the shutdown round arrangement for the subsequent rounds and sends the updated shutdown start delay parameters to the local controller of the corresponding valve.

[0013] As an optional solution, when the measured differential pressure value of the local controller continuously exceeds the deviation tolerance and no updated shutdown / start delay parameters are received from the remote management platform within the preset safety waiting period, the local controller delays the shutdown action. After the safety waiting period ends, the local controller re-collects the measured differential pressure value. If the measured differential pressure value falls back to the deviation tolerance range, the shutdown action is initiated. If it still exceeds the deviation tolerance, the delay continues and a differential pressure deviation alarm is sent to the remote management platform again.

[0014] As an optional solution, the duct system network model includes the length, cross-sectional area, friction resistance characteristics, and local resistance characteristics of each pipe segment, the position coordinates of each smoke exhaust fire damper in the pipeline, and the connection relationship between each pipe segment; the steady-state airflow balance calculation of the network is based on the friction resistance and local resistance characteristics of each pipe segment, and the pressure distribution of each node is solved according to the pressure balance relationship of each node and the flow conservation relationship of each branch. The pressure difference value on both sides of the valve plate at each valve position is extracted from the pressure distribution, and the aerodynamic load of the valve is determined by combining the structural parameters of the corresponding valve.

[0015] According to a second aspect of the embodiments of this application, a remote intelligent control system for smoke exhaust fire dampers based on the Internet of Things is also provided, comprising: The remote management platform, the local controllers for multiple smoke exhaust fire dampers, and the communication links connected to the remote management platform and each of the local controllers, wherein: The remote management platform is used to determine the set of valves to be closed when it receives multiple valve closure requests in the same duct section, and to obtain the duct pressure difference measurement value at the current location of each valve in the set, the rated output torque of the electric actuator of each valve, and the current operating status of the smoke exhaust fan. The remote management platform is also used to calculate the aerodynamic load borne by each valve plate based on the pre-stored duct system network model, combined with the duct differential pressure measurement value, the current opening status of each valve and the operating status of the smoke exhaust fan, through steady-state air volume balance calculation of the network, and to calculate the load ratio of each valve based on the aerodynamic load. The remote management platform is also used to determine the closing round of each valve in descending order of the load ratio using an iterative method. In each round, the valve with the largest load ratio among the remaining valves is selected as the closing target for that round. After setting the closing target for that round to the closed state in the pipeline model, the pipeline steady-state air volume balance calculation is re-executed to update the load ratio of the remaining valves and proceed to the next round of selection until all valves are assigned to the corresponding round. The remote management platform is also used to generate a shutdown start delay parameter for each valve based on the order of each round and the full stroke closing time of each valve electric actuator, and to send the shutdown start delay parameter to the local controller of each valve along with the shutdown command via the communication link; Each of the local controllers is used to sequentially start the corresponding electric actuator to perform the shutdown action according to the shutdown start delay parameters received by each controller.

[0016] This application addresses the problem of sudden load increases on individual valves and potential shutdown during the coordinated closure of multiple smoke exhaust fire dampers in the same duct section due to airflow redistribution. Based on duct pressure difference, valve opening, smoke exhaust fan operating status, and duct network model, the load ratio of each valve under the current operating conditions is calculated. The closing cycles are iteratively arranged according to the load ratio change law to match the aerodynamic load borne by each valve during the closing process with the driving torque of the actuator, thereby improving the reliability and success rate of multi-valve coordinated closure. Meanwhile, by setting a parallel shutdown decision, the overall shutdown time can be shortened while meeting the torque margin requirements, taking into account both control safety and fire-fighting timeliness. Furthermore, by comparing the measured pressure difference with the estimated pressure difference, subsequent rounds of dynamic adjustment are triggered, and the local controller can implement delayed shutdown in the event of untimely remote response, which helps to improve the system's adaptability to complex operating conditions and communication anomalies.

[0017] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Furthermore, no embodiment in this disclosure is required to achieve all the effects described above. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0019] Figure 1 This is a schematic diagram of a remote intelligent control method for a smoke exhaust fire damper based on the Internet of Things, provided in an embodiment of this disclosure.

[0020] Figure 2 This is a schematic diagram of the valve load ratio calculation process provided in an embodiment of this disclosure.

[0021] Figure 3 This is a schematic diagram illustrating the process for determining the valve closing cycles in an embodiment of this disclosure.

[0022] Figure 4 This is a schematic diagram of the structure of a remote intelligent control system for a smoke exhaust fire damper based on the Internet of Things, provided in an embodiment of this disclosure.

[0023] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0024] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0025] This solution is applicable to scenarios in underground spaces such as subway stations, highway tunnels, and underground commercial complexes, where multiple smoke exhaust fire dampers are distributed along the ductwork of the same ventilation system. Each smoke exhaust fire damper is equipped with an electric actuator and a local controller. The local controller is connected to a micro differential pressure sensor, and each local controller maintains a data connection with the remote management platform via an IoT communication link. Smoke exhaust fans are installed in the ventilation system, and the remote management platform can obtain the operating status of each smoke exhaust fan. The remote management platform pre-stores a duct network model of the ventilation system. When the fire control center determines that multiple valves need to be closed in a certain duct section, the remote management platform generates a closure sequence arrangement plan according to the process described in this solution and sends it to each local controller for execution via the IoT communication link.

[0026] In the smoke exhaust ducts of large underground spaces, multiple smoke exhaust fire dampers are often arranged in series or parallel along the same main or branch pipe. When smoke isolation of this pipe section is required after a fire, the usual practice is to issue a closing command to all valves simultaneously. However, during the near-simultaneous closing of multiple valves, the valve that reaches the fully closed position first cuts off the airflow path of its pipe section. The airflow in the pipe is then redistributed towards the valves that have not yet fully closed, which causes a sudden increase in the wind pressure load on the valves still in the closing stroke. When this increased load exceeds the driving capacity of the electric actuator, the valve plate may stall during its stroke and fail to reach the fully closed position. This phenomenon is referred to as closing stall in this paper. This solution schedules the closing start time of each valve before the closing command is issued, so that the pneumatic load borne by each valve during the closing stroke remains within the safe driving range of its electric actuator.

[0027] The implementation process of the method described in this application will be described in detail below with reference to specific embodiments. It should be noted that this embodiment is only used to explain this application and is not intended to limit the scope of protection of this application. Conventional adjustments or substitutions of each step by those skilled in the art without departing from the concept of this application should be included in the scope of protection of this application.

[0028] Please see Figure 1 , Figure 1 This is a flowchart of a remote intelligent control method for smoke exhaust fire dampers based on the Internet of Things according to an embodiment of the present invention, such as... Figure 1 As shown, the method includes steps S1-S4: In step S1, when the remote management platform receives a request to close multiple valves in the same duct section, it determines the set of valves to be closed and obtains the duct pressure difference measurement value at the current location of each valve in the set, the rated output torque of the electric actuator of each valve, and the current operating status of the smoke exhaust fan.

[0029] When the remote management platform receives a request from the fire control center to close multiple valves in the same duct section, the remote management platform first determines the set of valves to be closed, which must contain at least two valves.

[0030] The remote management platform then sends a status query command to the local controller of each valve within the system. Each local controller returns two data points: the current opening status of the valve and the measured differential pressure value of the duct at the valve location. This value is collected in real time by a micro differential pressure sensor connected to the local controller, representing the static pressure difference across the valve plate under the current airflow conditions. Simultaneously, the remote management platform reads the current operating status of each smoke exhaust fan from the building automation system or fan controller, including whether the fan is running and its current operating speed or actual airflow. Additionally, the remote management platform retrieves the rated output torque of the electric actuator corresponding to each valve from the duct network model. This is a device parameter entered during system deployment, representing the maximum driving torque that the actuator can continuously output under normal operating conditions.

[0031] In step S2, the remote management platform, based on the pre-stored duct system network model, combined with the duct differential pressure measurement value, the current opening status of each valve and the operating status of the smoke exhaust fan, calculates the aerodynamic load borne by each valve plate through steady-state air volume balance calculation of the network, and calculates the load ratio of each valve based on the aerodynamic load.

[0032] According to embodiments of this disclosure, the duct system network model pre-stored in the remote management platform includes the length, cross-sectional area, friction resistance characteristics, and local resistance characteristics of each pipe segment, the position coordinates of each smoke exhaust fire damper in the pipeline, and the connection relationships between each pipe segment. The friction resistance characteristics are typically characterized by the frictional resistance coefficient of the pipe segment, and the local resistance characteristics are typically characterized by the local resistance coefficient. These parameters are derived from HVAC construction drawings or building information model data and are entered all at once during the system deployment phase.

[0033] In some embodiments, the duct network model may also include the rated air volume and air pressure characteristic curves of each exhaust fan to improve the accuracy of subsequent airflow distribution calculations. The duct network model generally remains unchanged during system operation and is only updated by maintenance personnel after duct modifications or equipment replacements.

[0034] Please see Figure 2 , Figure 2 A schematic diagram of the valve load ratio calculation process provided in an embodiment of this disclosure is shown. Figure 2 As shown, in step S201, the aerodynamic load borne by each valve plate is calculated based on the steady-state air volume balance of the pipeline network.

[0035] The remote management platform, based on the pipeline network model and combining the measured differential pressure values ​​of each valve and duct obtained in the preceding steps with the operating status of the exhaust fan, performs a steady-state airflow balance calculation for the pipeline network. This calculation method is a mature approach in the field of HVAC engineering. Its basic principle is: based on the friction resistance and local resistance characteristics of each pipe section, pressure balance equations for each node and flow conservation equations for each branch are established. These equations are then solved simultaneously under the current fan operating conditions and valve opening conditions to obtain the pressure distribution of each node in the pipeline network and the airflow distribution of each branch. The remote management platform extracts the differential pressure value on both sides of the valve plate at each valve location from the solution results and determines the current aerodynamic load borne by the valve based on the corresponding valve's structural parameters.

[0036] In step S202, after obtaining the pneumatic load of each valve, the remote management platform performs load ratio calculation for each valve.

[0037] The load ratio reflects the proportional relationship between the resistance torque generated by the pneumatic load on the valve plate and the rated output torque of the electric actuator under current airflow conditions. Specifically, the pneumatic load of each valve is multiplied by the lever arm length between the valve plate's rotation center and the equivalent point of application of the pneumatic load to obtain the pneumatic resistance torque. This pneumatic resistance torque is then divided by the rated output torque of the electric actuator for that valve; the quotient is the load ratio of that valve. This can be expressed by the formula: in For the first Pneumatic load of a valve This is the lever arm length between the valve plate's rotation center and the equivalent point of application of the pneumatic load. This is the rated output torque of the electric actuator of the valve. The load ratio is determined by the valve's structural parameters and is entered into the pipeline model during system deployment. The closer the value is to 1, the smaller the driving torque margin of the actuator; once... If the torque reaches or exceeds 1, the driving torque of the actuator will be insufficient to overcome the pneumatic drag torque, and the valve plate will experience shut-off.

[0038] In step S3, the remote management platform determines the closing round of each valve in descending order of the load ratio using an iterative method. In each round, the valve with the largest load ratio among the remaining valves is selected as the closing target for that round. After setting the closing target for that round to the closed state in the pipeline model, the pipeline steady-state air volume balance calculation is re-executed to update the load ratio of the remaining valves, and the next round of selection is entered until all valves are assigned to the corresponding round.

[0039] Please see Figure 3 , Figure 3A schematic diagram illustrating the process for determining the valve closing cycles provided in embodiments of this disclosure is shown. Figure 3 As shown, in step S301, based on the sorting of all valve load ratios, the valves arranged in descending order of load ratio and the first round of closure objects are selected.

[0040] The remote management platform will arrange all valves in descending order of load ratio. The reason for using descending order is that there is an airflow redistribution effect during the multi-valve linkage closure process: when a valve on a pipe section closes first, the airflow that originally flowed through the branch where that valve is located will be forced to turn to the other unclosed branches, which will increase the pressure difference and load ratio at the location of the unclosed valve.

[0041] If valves with lower loads are closed first, leaving those with higher loads to close last, each round of airflow redistribution will subject the already heavy-loaded valves to higher air pressure, accumulating the risk of stalling during closure and potentially exceeding the actuator's tolerance limit. Conversely, if the valve with the highest load is closed first, all other valves are open, the airflow path in the duct is not interrupted, and the pressure distribution within the duct is consistent with the initial calculation. The load faced by this valve during its closing stroke is the initially calculated load, with no additional superposition.

[0042] After the valve is completely closed, although the airflow will be redistributed to the other valves, the initial loads on these valves are relatively low. Even with the added increase from the airflow redistribution, there is usually enough torque margin to complete the closure. Based on this strategy, the remote management platform selects the valve with the highest load ratio from the sorted valve list as the first valve to be closed.

[0043] In step S302, the closing cycle of each valve is determined by a round-by-round iterative method and the pipeline network is recalculated.

[0044] The first round of valve closures is marked as closed in the pipeline model. Specifically, the flow resistance of the pipe segment containing that valve is set to a maximum value, or the boundary condition of that segment is set to zero flow. Then, a new steady-state airflow balance calculation for the pipeline network is performed. In the recalculated input conditions, the pipe segment corresponding to the closed valve is no longer allowed to flow through, the exhaust fan's operating status remains unchanged, and the remaining valves are still at their current opening degree. After the calculation is complete, the remote management platform extracts the pressure difference value across the valve plate at each remaining open valve location from the new node pressure distribution. Based on this, the aerodynamic loads of these valves are updated, and the load ratio is recalculated.

[0045] Among the remaining valves after the update, the valve with the highest load ratio is selected again as the second round of shut-off targets. The second round of shut-off targets are then set to the closed state in the pipeline model, and the pipeline steady-state airflow balance calculation is performed again to update the load ratios of the remaining valves, entering the third round of selection. This process is repeated iteratively until all valves have been assigned to their corresponding rounds.

[0046] Multi-valve closure is a process of gradually changing the pipeline topology. Each round of closure alters the airflow distribution within the pipe, and the load ratios of the remaining valves are not constant. If the valves are only sorted once based on the initial state without recalculation after each round of closure, the actual airflow redistribution may reverse the load ratio rankings of some valves. That is, a valve with an initial load ratio in the middle might become the valve with the highest load ratio among the remaining valves after several rounds of closure. Iterative selection ensures that the selection results in each round reflect the current actual airflow state of the pipeline network.

[0047] In step S303, in each iteration, after selecting the valve with the largest load ratio as the shut-off target for that round, the remote management platform also performs a parallel shut-off determination on the remaining valves.

[0048] In practical engineering, strictly closing all valves one by one sequentially can maximize the control of the load level of each valve, but the total closing time will increase linearly with the number of valves, which is detrimental to the timeliness of fire safety. Therefore, in each iteration, after selecting the valve with the largest load ratio as the closing target for that round, the remote management platform also performs a parallel closing determination on the remaining valves.

[0049] In some embodiments, the determination criterion is a preset torque margin coefficient, denoted as... Its value ranges from 0 to 1 and is a positive number. It is preset by the system integrator based on the performance parameters and safety margin requirements of the electric actuator. This indicates that when the load ratio of a certain valve is lower than At this time, its actuator has sufficient torque margin, so even if an additional pneumatic load increment is added during the closing stroke due to the simultaneous closing of adjacent valves in the same wheel, the closing can still be completed smoothly. For example, It can be configured to a value between 0.6 and 0.8.

[0050] The specific determination process includes, after selecting the valve with the highest load ratio for that wheel, checking whether any of the remaining valves have a load ratio lower than [the specified value]. Valves. If they exist, these valves are included in the shut-off objects of this round, and shut down simultaneously with the valve with the highest load ratio. In the pipeline model, all shut-off objects in this round are simultaneously set to the closed state, and then the pipeline steady-state airflow balance calculation is performed to update the load ratio of the remaining valves, before proceeding to the next iteration.

[0051] If none of the remaining valves currently have a load ratio lower than If a valve has a large load capacity, then the wheel will only close the valve with the largest load ratio, without parallel closure. This mechanism allows multiple valves to close in parallel to shorten the overall time when each valve has sufficient load margin, while tightening to single-valve closure to ensure safety when the margin is insufficient.

[0052] In step S4, the remote management platform generates a shutdown start delay parameter for each valve based on the order of each round and the full stroke closing time of each valve's electric actuator. The shutdown start delay parameter is then sent to the local controller of each valve via the communication link along with the shutdown command. Each local controller starts the electric actuator sequentially to perform the shutdown action according to the shutdown start delay parameter it receives.

[0053] Through the aforementioned iterative processing, all valves have been assigned to several rounds, each round containing one or more valves. The remote management platform generates a closing-start delay parameter for each valve based on the order of the rounds and the full-stroke closing time of each valve's electric actuator. The full-stroke closing time refers to the time required for the electric actuator to drive the valve plate from the fully open position to the fully closed position; this value is determined by the actuator's model and rotational speed and is entered during system deployment.

[0054] The shutdown start-up delay parameter is the waiting time for each valve relative to the shutdown start-up time of the first round of shutdown objects, using that time as the baseline. The shutdown start-up delay parameter for the first round of shutdown objects is zero, meaning it starts immediately upon receiving the command. From the second round onwards, the shutdown start-up delay parameter for each round of shutdown objects is equal to the cumulative value of the total shutdown time of all previous rounds of shutdown objects.

[0055] For example, if the total shutdown time of the first round of shutdown is... The shutdown startup delay parameter for the second round of object shutdown is: If the valve with the longest total closing time among the valves to be closed in the second round takes... The shutdown startup delay parameter for the third round of object shutdown is: And so on.

[0056] Based on the above calculations, when each round of closure begins, all valves in the previous round should have completed their closing stroke, the airflow in the pipe has been redistributed and tends to stabilize under the new topological conditions, and the actual aerodynamic load borne by the valves in the current round during the closing process is consistent with the estimated value in the aforementioned iterative calculations.

[0057] Optionally, a settling-off delay can be added between the closing start-up delay parameters of two adjacent closing objects. This settling-off delay allows the airflow in the pipe to transition from a transient to a steady state after the previous valve closure, and its duration is related to the pipe length and the airflow velocity in the pipe. In some embodiments, the settling-off delay can be configured as a certain proportion of the full-stroke closing time of the previous round.

[0058] The remote management platform packages the shut-off start-up delay parameters of each valve along with the shut-off execution command, and sends them to the corresponding local controllers via the Internet of Things communication link.

[0059] Upon receiving a closing command with a closing start delay parameter, each local controller starts a local timer based on the command reception time. When the timer reaches the waiting time specified by the valve's closing start delay parameter, the local controller activates the electric actuator to drive the valve plate to the fully closed position. For the first round of closing, the delay parameter is zero, and the operation starts immediately upon receiving the command; subsequent rounds start sequentially according to their respective delay parameters.

[0060] In some embodiments, the aerodynamic load calculation is based on a pipeline steady-state model, which is a simplified description of the actual pipeline. In the actual pipeline network, there may be branch leaks not fully included in the model, accidental opening of bypass valves, or changes in the fan operating state during the closure of multiple valves. These factors can cause the actual aerodynamic load borne by a valve during its closing stroke in a particular cycle to deviate from the expected value. To address this deviation, this embodiment incorporates a real-time pressure monitoring and time-series dynamic adjustment mechanism.

[0061] When the remote management platform issues a shutdown command to each local controller, it also sends the estimated differential pressure value for each valve in the corresponding cycle, obtained from the steady-state airflow balance calculation of the pipeline network, along with the command. The estimated differential pressure value refers to the expected pressure difference across the valve plate calculated according to the pipeline network model when the valve is started and closed in its respective cycle.

[0062] After activating the electric actuator, each local controller continuously collects the measured differential pressure value across the valve plate using a micro differential pressure sensor. The local controller compares the measured differential pressure value with the locally stored estimated differential pressure value and calculates the deviation. When the deviation exceeds a preset deviation tolerance, the local controller sends a differential pressure deviation alarm to the remote management platform. The alarm information includes the valve's identifier and the current measured differential pressure value.

[0063] Deviation tolerance refers to the maximum allowable deviation between the measured differential pressure and the estimated differential pressure. This value is obtained by the system integrator through actual testing during the commissioning phase, based on the calculation accuracy of the pipeline model and the measurement error of the micro differential pressure sensor. The calibration method typically involves actively triggering several fan start-ups and shutdowns or partial valve closures during system commissioning, recording the statistical distribution of the deviation between the measured differential pressure at each valve location and the model's calculated value, and taking the upper limit of its normal fluctuation range as the deviation tolerance. The deviation tolerance is written into the configuration parameters of each local controller after calibration and remains unchanged during system operation, only requiring recalibration after pipeline modifications or sensor replacements.

[0064] In some embodiments, after receiving a differential pressure deviation alarm from a local controller, the remote management platform determines the cycle to which the valve belongs. If the valve is currently in the cycle of closing, the remote management platform uses the measured differential pressure value carried in the alarm as input to re-execute the steady-state airflow balance calculation of the pipeline network and updates the load ratio of each valve in subsequent cycles that have not yet started closing.

[0065] After the update is complete, the remote management platform checks the new load ratio of each valve in subsequent cycles. If the new load ratio of a valve in a subsequent cycle does not exceed the preset torque margin coefficient... If the valve maintains its original closing and starting delay parameters, then the valve will remain unchanged. If the new load ratio of the valve in a subsequent cycle exceeds... This indicates that the valve is at risk of stalling when executed according to the original scheduling scheme. The remote management platform re-executes the shutdown cycle scheduling for the subsequent cycles, that is, according to the same sorting and iteration strategy as step S3 above, the remaining unclosed valves are reassigned to cycles and new shutdown start delay parameters are calculated. Then, the updated shutdown start delay parameters are sent to the local controller of the corresponding valve.

[0066] After receiving the updated shutdown / start delay parameters, the local controller uses the moment the update command is received as the new reference, and restarts the shutdown process according to the updated delay parameters.

[0067] In some embodiments, when the remote management platform fails to recalculate and update the command before the valve is scheduled to start or close due to communication delays or lengthy calculation times, the local controller can implement a fallback strategy. If the measured differential pressure value of the local controller continuously exceeds the deviation tolerance and the updated shut-off / start delay parameters are not received from the remote management platform within a preset safety waiting period, the local controller will not initiate the shut-off operation according to the original delay parameters, but will instead delay the shutdown action. The safety waiting period is a time length pre-written into the local controller's configuration parameters. Its value is determined based on the typical time required for the remote management platform to complete a full pipeline network calculation and issue commands, and can be configured to be on the order of several seconds.

[0068] After the safety waiting period ends, the local controller rereads the measured differential pressure value from the micro differential pressure sensor. If this value has fallen back to within the tolerance range, it indicates that the airflow in the pipe has stabilized or the remote management platform has adjusted the pipeline status through other means. At this time, the local controller activates the electric actuator to perform the shutdown. If the measured differential pressure value still exceeds the tolerance range, the local controller continues to delay the shutdown and sends a differential pressure deviation alarm to the remote management platform again, waiting for the next safety waiting period.

[0069] This yielding strategy ensures that the valve will not be forcibly closed under excessively high aerodynamic loads if the remote management platform does not respond in a timely manner. Instead, it will autonomously wait until the airflow conditions improve or a new instruction is received before taking action.

[0070] In some embodiments, after all valves have closed, each local controller reports the closure completion status to the remote management platform. The remote management platform aggregates the status information of each valve to confirm that all valves in the duct section have reached the fully closed position. If a valve fails to reach the fully closed position within the preset maximum closing stroke time after initiating the closure process, the local controller reports a closure timeout alarm to the remote management platform, which can then determine whether a retry command or maintenance notification is needed.

[0071] With the above scheme, before issuing multi-valve shut-off commands, the remote management platform calculates the load ratio of each valve based on the airflow distribution of the pipeline network. It determines the shut-off cycle of each valve in descending order of load ratio through iterative rounds. In each iteration, it achieves a balance between safety and shut-off timeliness by determining whether the valve can be shut off in parallel. Then, it generates shut-off start-up delay parameters for each valve based on the cycle order and the full-stroke shut-off time.

[0072] During the shutdown process, each local controller compares the measured differential pressure value with the estimated differential pressure value. If the deviation exceeds the tolerance, an alarm is triggered, and the remote management platform dynamically adjusts the scheduling scheme for subsequent cycles accordingly. If the remote management platform fails to respond in a timely manner, the local controller autonomously delays the shutdown and waits for the airflow conditions to improve. The entire solution, without adding additional sensors or changing the existing valve hardware structure, avoids the stalling of individual valves due to airflow redistribution effects in multi-valve linkage shutdown scenarios by scheduling the shutdown sequence and dynamically adjusting the operation period, while keeping the overall shutdown completion time within the fire safety timeliness requirements.

[0073] Please see Figure 4 , Figure 4 This is a schematic diagram of a remote intelligent control system for a smoke exhaust fire damper based on the Internet of Things, provided in an embodiment of this application. For example... Figure 4 As shown, the system includes: The remote management platform, the local controllers for multiple smoke exhaust fire dampers, and the communication links connected to the remote management platform and each of the local controllers, wherein: The remote management platform is used to determine the set of valves to be closed when it receives multiple valve closure requests in the same duct section, and to obtain the duct pressure difference measurement value at the current location of each valve in the set, the rated output torque of the electric actuator of each valve, and the current operating status of the smoke exhaust fan. The remote management platform is also used to calculate the aerodynamic load borne by each valve plate based on the pre-stored duct system network model, combined with the duct differential pressure measurement value, the current opening status of each valve and the operating status of the smoke exhaust fan, through steady-state air volume balance calculation of the network, and to calculate the load ratio of each valve based on the aerodynamic load. The remote management platform is also used to determine the closing round of each valve in descending order of the load ratio using an iterative method. In each round, the valve with the largest load ratio among the remaining valves is selected as the closing target for that round. After setting the closing target for that round to the closed state in the pipeline model, the pipeline steady-state air volume balance calculation is re-executed to update the load ratio of the remaining valves and proceed to the next round of selection until all valves are assigned to the corresponding round. The remote management platform is also used to generate a shutdown start delay parameter for each valve based on the order of each round and the full stroke closing time of each valve electric actuator, and to send the shutdown start delay parameter to the local controller of each valve along with the shutdown command via the communication link; Each of the local controllers is used to sequentially start the corresponding electric actuator to perform the shutdown action according to the shutdown start delay parameters received by each controller.

[0074] Each processing unit and / or module in the embodiments of this application can be implemented by an analog circuit that implements the functions described in the embodiments of this application, or by software that executes the functions described in the embodiments of this application.

[0075] Based on the same inventive concept, this application also provides an electronic device, the method corresponding to which can be the method in the foregoing embodiments, and its problem-solving principle is similar to that method. For example... Figure 5 As shown, Figure 5 This is a schematic diagram of an electronic device structure provided in an embodiment of the present disclosure. The device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the methods and / or technical solutions of the foregoing embodiments of the present application.

[0076] In particular, the methods and / or embodiments in this application can be implemented as computer software programs. For example, the embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowchart. When the computer program is executed by a processor, it performs the functions defined in the methods of this application.

[0077] Another embodiment of this application provides a storage medium storing computer program instructions thereon, which can be executed by a processor to implement the methods and / or technical solutions of any one or more embodiments of this application.

[0078] In the above embodiments, the descriptions of each embodiment have different focuses. Parts not described in detail in a certain embodiment can be referred to in the relevant descriptions of other embodiments. The above descriptions are merely preferred embodiments of this application and explanations of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to the technical solutions formed by specific combinations of the above technical features, but should also cover other technical solutions formed by arbitrary combinations of the above technical features or their equivalent features without departing from the inventive concept.

Claims

1. A remote intelligent control method for smoke exhaust fire dampers based on the Internet of Things, characterized in that, include: When the remote management platform receives multiple valve closure requests in the same duct section, it determines the set of valves to be closed and obtains the duct pressure difference measurement value at the current location of each valve in the set, the rated output torque of the electric actuator of each valve, and the current operating status of the smoke exhaust fan. The remote management platform is based on a pre-stored duct system network model. It combines the duct differential pressure measurement value, the current opening status of each valve and the operating status of the smoke exhaust fan. Through steady-state air volume balance calculation of the network, it obtains the aerodynamic load borne by each valve plate and calculates the load ratio of each valve based on the aerodynamic load. The remote management platform determines the closing round of each valve in descending order of load ratio using an iterative method. In each round, the valve with the largest load ratio among the remaining valves is selected as the closing target for that round. After setting the closing target for that round to the closed state in the pipeline model, the pipeline steady-state air volume balance calculation is re-executed to update the load ratio of the remaining valves, and the next round of selection is entered until all valves are assigned to the corresponding round. The remote management platform generates a shutdown start delay parameter for each valve based on the order of each cycle and the full stroke closing time of each valve's electric actuator. The shutdown start delay parameter is then sent to the local controller of each valve via the communication link along with the shutdown command. Each local controller starts the electric actuator sequentially to perform the shutdown action according to the shutdown start delay parameter it receives.

2. The method according to claim 1, characterized in that, The load ratio is calculated as follows: multiply the pneumatic load of each valve by the lever arm length between the valve plate rotation center and the equivalent point of action of the pneumatic load to obtain the pneumatic resistance torque, and divide the pneumatic resistance torque by the rated output torque of the electric actuator of the valve to obtain the load ratio of the valve.

3. The method according to claim 1, characterized in that, In the iterative process described above, after selecting the valve with the largest load ratio as the shut-off target for each round, the process further includes determining whether the remaining valves can be shut off in parallel: valves with load ratios lower than a preset torque margin coefficient among the remaining valves are included in the shut-off targets for that round and shut off simultaneously with the valve with the largest load ratio in that round; after setting all shut-off targets in the pipeline model to the closed state, the pipeline steady-state airflow balance calculation is re-executed to update the load ratios of the remaining valves, wherein the torque margin coefficient is a positive number between 0 and 1.

4. The method according to claim 1, characterized in that, The shutdown start delay parameter is generated as follows: the shutdown start delay parameter of the first round of shutdown objects is zero; from the second round onwards, the shutdown start delay parameter of each round of shutdown objects is equal to the cumulative value of the total shutdown time of the shutdown objects in the previous rounds.

5. The method according to claim 4, characterized in that, An additional stabilization waiting time is added between the shutdown start delay parameters of two adjacent shutdown objects. The stabilization waiting time is determined based on the time required for the airflow in the pipe to transition from transient to steady state after the previous shutdown object is shut down.

6. The method according to claim 1, characterized in that, When the remote management platform issues a shutdown command, it sends the estimated differential pressure value for each valve corresponding to the cycle obtained from the steady-state airflow balance calculation of the pipeline network to the local controller of each valve along with the shutdown command. After each local controller initiates the shutdown action, it continuously collects the measured differential pressure value on both sides of the valve plate and compares the measured differential pressure value with the estimated differential pressure value. When the deviation of the measured differential pressure value from the estimated differential pressure value exceeds the preset deviation tolerance, it sends a differential pressure deviation alarm to the remote management platform.

7. The method according to claim 6, characterized in that, After receiving the differential pressure deviation alarm, the remote management platform uses the measured differential pressure value carried in the alarm as input to re-execute the steady-state air volume balance calculation of the pipeline network and update the load ratio of each valve in the subsequent rounds that have not yet been started or shut down; If the updated load ratio exceeds the preset torque margin coefficient, the remote management platform will re-execute the shutdown cycle arrangement for the subsequent cycles and send the updated shutdown start delay parameters to the local controller of the corresponding valve.

8. The method according to claim 6, characterized in that, When the measured differential pressure value of the local controller continuously exceeds the deviation tolerance and no updated shutdown / start delay parameters are received from the remote management platform within the preset safety waiting period, the local controller delays the shutdown action. After the safety waiting period ends, the local controller re-collects the measured differential pressure value. If the measured differential pressure value falls back to the deviation tolerance range, the shutdown action is initiated. If it still exceeds the deviation tolerance, the delay continues and a differential pressure deviation alarm is sent to the remote management platform again.

9. The method according to claim 1, characterized in that, The duct system network model includes the length, cross-sectional area, friction resistance characteristics, and local resistance characteristics of each pipe segment, the position coordinates of each smoke exhaust fire damper in the pipeline, and the connection relationship between each pipe segment; the steady-state airflow balance calculation of the network is based on the friction resistance and local resistance characteristics of each pipe segment, and the pressure distribution of each node is solved according to the pressure balance relationship of each node and the flow conservation relationship of each branch. The pressure difference value on both sides of the valve plate at each valve position is extracted from the pressure distribution, and the aerodynamic load of the valve is determined by combining the structural parameters of the corresponding valve.

10. A remote intelligent control system for smoke exhaust fire dampers based on the Internet of Things, characterized in that, include: The remote management platform, the local controllers for multiple smoke exhaust fire dampers, and the communication links connected to the remote management platform and each of the local controllers, wherein: The remote management platform is used to determine the set of valves to be closed when it receives multiple valve closure requests in the same duct section, and to obtain the duct pressure difference measurement value at the current location of each valve in the set, the rated output torque of the electric actuator of each valve, and the current operating status of the smoke exhaust fan. The remote management platform is also used to calculate the aerodynamic load borne by each valve plate based on the pre-stored duct system network model, combined with the duct differential pressure measurement value, the current opening status of each valve and the operating status of the smoke exhaust fan, through steady-state air volume balance calculation of the network, and to calculate the load ratio of each valve based on the aerodynamic load. The remote management platform is also used to determine the closing round of each valve in descending order of the load ratio using an iterative method. In each round, the valve with the largest load ratio among the remaining valves is selected as the closing target for that round. After setting the closing target for that round to the closed state in the pipeline model, the pipeline steady-state air volume balance calculation is re-executed to update the load ratio of the remaining valves and proceed to the next round of selection until all valves are assigned to the corresponding round. The remote management platform is also used to generate a shutdown start delay parameter for each valve based on the order of each round and the full stroke closing time of each valve electric actuator, and to send the shutdown start delay parameter to the local controller of each valve along with the shutdown command via the communication link; Each of the local controllers is used to sequentially start the corresponding electric actuator to perform the shutdown action according to the shutdown start delay parameters received by each controller.

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