A roof ventilation and smoke exhaust system with intelligent linkage control and adaptive adjustment function

Abstract

This invention relates to a roof ventilation and smoke extraction system with intelligent linkage control and adaptive adjustment functions, belonging to the field of building ventilation and smoke extraction technology. The system includes a roof skylight array, smoke extraction fan units, a multi-source sensor network, and an edge computing controller. The edge computing controller incorporates a pattern recognition module, a linkage control module, an adaptive adjustment module, and a zone scheduling module. In fire-fighting smoke extraction mode, the linkage control module dynamically calculates the optimal opening sequence of each smoke extraction skylight and the optimal speed sequence of each smoke extraction fan based on the spatial distribution of smoke concentration and temperature, ensuring coordinated matching between skylight opening and fan speed. In daily ventilation mode, the adaptive adjustment module uses a predictive control algorithm to dynamically adjust the equipment's operating status. This invention achieves integrated intelligent management of daily ventilation and fire-fighting smoke extraction through deep linkage control, intelligent pattern recognition, and zone adaptive scheduling, improving smoke extraction efficiency by more than 30% and significantly reducing energy consumption.

Description

Technical Field

[0001] This invention relates to the field of building ventilation and smoke extraction technology, specifically to a roof ventilation and smoke extraction system and control method with intelligent linkage control and adaptive adjustment functions. Background Technology

[0002] Roof ventilation and smoke extraction systems are critical infrastructure in industrial plants, commercial complexes, and public buildings, serving the dual functions of daily ventilation and emergency smoke extraction. With the increasing scale and complexity of building functions, higher demands are being placed on the intelligence and adaptability of roof ventilation and smoke extraction systems.

[0003] In related technologies, the control of smoke exhaust skylights and smoke exhaust fans are often executed by independent control loops or independent controllers. For example, an intelligent smoke exhaust skylight system based on smoke concentration-assisted smoke exhaust adjusts the smoke exhaust speed by rotating the window, but does not coordinate the change in the opening of the smoke exhaust window with the speed of the smoke exhaust fan, resulting in energy loss between the smoke flow path and the fan suction force.

[0004] In its smoke extraction skylight system, the central processor receives signals from smoke sensors and controls an electric telescopic rod to open the skylight, simultaneously activating the smoke extraction fan. However, there is a lack of a dynamic matching mechanism between the skylight opening and the fan speed based on smoke concentration. This functional disconnect results in low smoke extraction efficiency, failing to achieve optimal smoke extraction during the precious smoke extraction window in the early stages of a fire. Summary of the Invention

[0005] To address the aforementioned issues, this invention provides a roof ventilation and smoke extraction system and control method with intelligent linkage control and adaptive adjustment functions.

[0006] The roof ventilation and smoke extraction system with intelligent linkage control and adaptive adjustment functions provided by this invention adopts the following technical solution: A roof ventilation and smoke exhaust system with intelligent linkage control and adaptive adjustment functions includes a roof skylight array, a smoke exhaust fan unit, a multi-source sensor network, and an edge computing controller. The roof skylight array is installed on the building roof and includes multiple smoke exhaust skylights with independently controllable opening. The smoke exhaust fan unit is installed on the roof or in a smoke exhaust fan room and connected to the smoke exhaust duct to provide negative pressure smoke exhaust power. The multi-source sensor network includes smoke concentration sensors, temperature sensors, and carbon monoxide sensors installed in each smoke control zone, as well as wind speed sensors, rain and snow sensors, and outdoor temperature sensors installed on the roof. The edge computing controller is connected to the roof skylight array, the smoke exhaust fan unit, and the multi-source sensor network to perform intelligent linkage control and adaptive adjustment. The edge computing controller has a built-in pattern recognition module, linkage control module, adaptive adjustment module, and zone adjustment module. The system comprises several modules: a degree module; a pattern recognition module for automatically identifying the current operating mode based on data collected by a multi-source sensor network, including daily ventilation mode, fire smoke exhaust mode, and fault self-check mode; a linkage control module for dynamically calculating the optimal opening sequence of each smoke exhaust skylight and the optimal speed sequence of each smoke exhaust fan in fire smoke exhaust mode, based on the spatial distribution of smoke concentration and temperature in each smoke control zone, to ensure coordinated matching between skylight opening and fan speed; an adaptive adjustment module for dynamically adjusting the opening of smoke exhaust skylights and the speed of smoke exhaust fans using predictive control algorithms in daily ventilation mode, based on real-time changes in indoor and outdoor environmental parameters; and a zone scheduling module for dynamically allocating smoke exhaust resources according to the smoke development trend of each zone when the building is divided into multiple smoke control zones, and automatically scheduling smoke exhaust equipment from adjacent zones to provide support when the smoke exhaust capacity of a certain zone is insufficient.

[0007] By adopting the above technical solutions, the edge computing controller integrates smoke exhaust skylights and smoke exhaust fans into a unified intelligent control architecture. The pattern recognition module automatically distinguishes between three operating modes: daily ventilation, fire smoke exhaust, and fault self-diagnosis. In fire smoke exhaust mode, the linkage control module dynamically calculates the optimal opening sequence and speed sequence based on the spatial distribution of smoke concentration and temperature, ensuring coordinated matching between skylight opening and fan speed, thus avoiding wasted or insufficient smoke exhaust capacity caused by excessively large or small skylight openings. The zone scheduling module enables dynamic allocation of smoke exhaust resources among multiple smoke control zones, effectively addressing fire spread and smoke diffusion.

[0008] Furthermore, the linkage control module calculates the optimal opening sequence of each smoke exhaust skylight according to the following formula: θ_i(t)=f(ρ_i(t),T_i(t))·K_spatial(i,ρ_distribution)·K_temporal(t), where θ_i(t) is the target opening of the i-th smoke exhaust skylight at time t, ρ_i(t) is the smoke concentration in the smoke control zone below the i-th skylight, T_i(t) is the temperature of the zone, f is a function of smoke concentration and temperature, K_spatial is the spatial correction coefficient based on the spatial distribution of smoke, and K_temporal is the temporal correction coefficient based on the fire development trend.

[0009] By adopting the above technical solution, smoke concentration and temperature are used as the basic control variables, and spatial and temporal correction coefficients are introduced to enable the skylight opening to adaptively adjust to the uneven distribution of smoke and the temporal dynamics of fire development. The spatial correction coefficient prioritizes the opening of skylights in areas with large smoke concentration gradients, while the temporal correction coefficient accelerates the opening response when the fire spreads rapidly, thus achieving precise dynamic adjustment of the skylight opening.

[0010] Furthermore, the linkage control module also calculates the optimal speed sequence of each smoke exhaust fan according to the following formula: ω_j(t)=g(Σρ_i(t),ΣQ_i(t))·η(ω_j(t-Δt)), where ω_j(t) is the target speed of the j-th smoke exhaust fan at time t, Σρ_i(t) is the total smoke concentration of all smoke control zones corresponding to the open smoke exhaust skylights, ΣQ_i(t) is the total heat release rate, g is a function of concentration and heat release rate, and η is a speed smoothing function based on the historical operating data of the fans.

[0011] By adopting the above technical solution, the rotational speed of the smoke exhaust fan is no longer independent of the skylight opening, but is calculated comprehensively based on the total smoke concentration and total heat release rate corresponding to all open skylights. The speed smoothing function avoids sudden changes in fan speed, prevents impact on the fan's mechanical structure, and extends equipment life.

[0012] Furthermore, the linkage control module is also used to: when the spatial distribution of smoke concentration and temperature meets the preset non-uniformity conditions, control the skylights near the high concentration area to open to a larger degree, and the skylights far away from the high concentration area to open to a smaller degree or remain closed, forming a differentiated smoke exhaust layout.

[0013] By adopting the above technical solutions, the differentiated smoke extraction layout concentrates limited smoke extraction capacity in the area with the highest smoke concentration, while avoiding excessive smoke extraction in low-concentration areas that would lead to energy waste. This non-uniform opening strategy is more effective at suppressing smoke diffusion than the traditional uniform opening strategy, and the smoke extraction efficiency can be improved by more than 30%.

[0014] Furthermore, the adaptive adjustment module has a built-in indoor air quality prediction model. The prediction model predicts the trend of indoor environmental parameter changes within a preset time window based on historical environmental data and equipment operating status, and adjusts the opening of the smoke exhaust skylight and the speed of the smoke exhaust fan in advance based on the prediction results.

[0015] By adopting the above technical solution, the predictive control algorithm overcomes the lag of traditional feedback control. When it is predicted that the indoor pollutant concentration is about to exceed the standard, the system opens the skylight or increases the fan speed in advance, so that the indoor air quality is always maintained within the set range, while avoiding frequent start-ups and shutdowns of the equipment.

[0016] Furthermore, it also includes an energy efficiency optimization module, which is connected to the adaptive adjustment module. This module is used to dynamically allocate the load rate of each smoke exhaust fan based on the real-time operating efficiency curve of the smoke exhaust fan unit, so that the smoke exhaust fan unit can operate in the optimal range of comprehensive energy efficiency while meeting the smoke exhaust requirements.

[0017] By adopting the above technical solution, the energy efficiency optimization module solves the problem of energy waste caused by "over-powered engines." When multiple fans are running in parallel, the system rationally distributes the total exhaust load to each fan based on the real-time efficiency curve of each fan, so that the overall operating efficiency of the unit reaches the optimal level, which meets the requirements of the new national standard for the energy efficiency level of exhaust fans.

[0018] Furthermore, it also includes a fault self-diagnosis module, which is connected to a multi-source sensor network and an edge computing controller to monitor the bearing temperature and vibration parameters of the drive motor and exhaust fan of the smoke exhaust skylight in real time, and to establish a fault prediction model based on historical data. When the predicted parameters exceed the preset threshold, a maintenance warning is issued in advance.

[0019] By adopting the above technical solution, the fault self-diagnosis module realizes the transformation from passive maintenance to proactive early warning. By analyzing the changing trends of characteristic parameters such as drive motor current, bearing temperature, and vibration spectrum, the system can identify anomalies and issue maintenance warnings before a fault occurs, avoiding the risk of equipment failure during fire emergencies.

[0020] Furthermore, the zone scheduling module is also used to: when the smoke concentration growth rate in a certain smoke control zone exceeds a preset threshold, the zone scheduling module automatically marks the zone as a high-priority area and increases the allocation weight of the smoke exhaust skylight opening and the smoke exhaust fan speed corresponding to the zone.

[0021] By adopting the above technical solution, the zoned dispatch module introduces the smoke concentration growth rate as a dynamic priority indicator. Areas with rapid smoke concentration growth indicate rapid fire development and require priority smoke extraction. This mechanism enables smoke extraction resources to be dynamically focused on the most dangerous areas, improving the effectiveness of emergency response.

[0022] Furthermore, the edge computing controller is also equipped with an interface for communicating with the city's fire protection IoT platform, which is used to upload system operating status parameters in real time and receive remote control commands issued by the fire protection IoT platform.

[0023] By adopting the above technical solution, the system connects with the city's fire protection IoT platform, enabling full lifecycle management and remote collaborative control of equipment. The fire command center can view real-time information such as smoke concentration, temperature, and equipment operating status in each smoke control zone, and remotely force the activation of the smoke extraction system in emergencies, meeting the development requirements of smart fire protection.

[0024] This invention also provides a roof ventilation and smoke exhaust intelligent linkage control method based on the above system, including the following steps: Step S1: Real-time collection of smoke concentration, temperature, carbon monoxide concentration, and roof wind speed and rain / snow conditions in each smoke control zone through a multi-source sensor network; Step S2: The edge computing controller determines the current working mode based on the collected data through a pattern recognition module—if the smoke concentration and temperature are both below the first threshold, it is determined to be the daily ventilation mode; if the smoke concentration exceeds the second threshold or the temperature exceeds the third threshold, it is determined to be the fire smoke exhaust mode; if an abnormal sensor signal or actuator feedback is detected, it is determined to be the fault self-check mode; Step S3: In the fire smoke exhaust mode, the linkage control module determines the spatial distribution of smoke concentration and temperature in each smoke control zone. Step S4: The zone scheduling module dynamically allocates smoke exhaust resources based on the smoke development trend of each smoke control zone. When the smoke exhaust capacity of a certain zone is insufficient, it automatically schedules the smoke exhaust equipment of adjacent zones for support. Step S5: The linkage control module outputs control commands to the roof skylight array and the smoke exhaust fan unit respectively according to the calculated optimal opening sequence and optimal speed sequence, so that the opening of the smoke exhaust skylight and the speed of the smoke exhaust fan are matched in coordination. Step S6: During the smoke exhaust process, the linkage control module monitors the smoke concentration and temperature changes in each smoke control zone in real time. When the smoke concentration drops below the safety threshold, it gradually reduces the opening of the smoke exhaust skylight and the speed of the smoke exhaust fan until the system returns to standby state.

[0025] By adopting the above technical solution, this control method organically integrates pattern recognition, linkage control, zone scheduling, and gradual recovery, forming a complete intelligent linkage control closed loop. From daily monitoring to fire response and post-disaster recovery, the entire process requires no manual intervention, with fast response speed and high smoke extraction efficiency.

[0026] In summary, the present invention has at least one of the following beneficial effects: 1. The linkage control module built into the edge computing controller is used to coordinate and match the opening degree of the smoke exhaust skylight with the speed of the smoke exhaust fan. The optimal opening degree sequence and speed sequence are dynamically calculated based on the spatial distribution of smoke concentration and temperature, which improves the smoke exhaust efficiency by more than 30% compared with the existing independent control system. 2. The pattern recognition module automatically distinguishes between three modes: daily ventilation, fire smoke exhaust, and fault self-check, achieving smooth transition and automatic switching. Daily ventilation uses predictive control algorithm for energy-saving operation, and fire smoke exhaust automatically switches to maximum smoke exhaust capacity, with response time shortened to the second level. 3. The zoning scheduling module enables dynamic allocation and intelligent scheduling of smoke exhaust resources among multiple smoke control zones. When a fire occurs in a zone, the smoke exhaust equipment in adjacent zones can be automatically scheduled to coordinate smoke exhaust, effectively preventing the spread of fire. 4. The energy efficiency optimization module dynamically allocates the load rate based on the real-time operating efficiency curve of the exhaust fan, achieving optimal overall energy efficiency in daily operation and meeting the new national energy efficiency requirements; the fault self-diagnosis module enables real-time monitoring of equipment status and predictive maintenance, reducing operation and maintenance costs. 5. Through the communication interface between the edge computing controller and the urban fire protection IoT platform, the system operation status can be uploaded in real time and remote collaborative control can be achieved, meeting the requirements of smart fire protection development. Attached Figure Description

[0027] Figure 1 This is a block diagram of the overall structure of the system of the present invention; Figure 2 This is a schematic diagram of the computational logic of the linkage control module of the present invention; Figure 3 This is a schematic diagram of resource scheduling for the partition scheduling module of the present invention; Figure 4 This is a flowchart of the control method of the present invention.

[0028] In the diagram: 1. Roof skylight array; 11. Smoke exhaust skylight; 2. Smoke exhaust fan unit; 21. Smoke exhaust fan; 3. Multi-source sensor network; 31. Smoke concentration sensor; 32. Temperature sensor; 33. Carbon monoxide sensor; 34. Wind speed sensor; 35. Rain and snow sensor; 36. Outdoor temperature sensor; 4. Edge computing controller; 41. Pattern recognition module; 42. Linkage control module; 43. Adaptive adjustment module; 44. Zone scheduling module; 45. Energy efficiency optimization module; 46. Fault self-diagnosis module; 47. Communication interface. Detailed Implementation

[0029] The following is in conjunction with the appendix Figure 1-4 The present invention will be described in further detail below.

[0030] This invention discloses a roof ventilation and smoke extraction system and control method with intelligent linkage control and adaptive adjustment functions. (Refer to...) Figure 1 The system includes a roof skylight array 1, a smoke exhaust fan unit 2, a multi-source sensor network 3, and an edge computing controller 4.

[0031] A rooftop skylight array 1 is installed on the building roof and includes multiple smoke exhaust skylights 11 with independently controllable opening. Each smoke exhaust skylight 11 is equipped with an independent electric actuator or rotary motor, capable of continuously adjusting the opening within a range of 0-100%. Smoke exhaust fan units 2 are installed on the roof or in a dedicated smoke exhaust fan room, including at least one smoke exhaust fan 21, with multiple fans capable of parallel operation. The smoke exhaust fan 21 is connected to the smoke exhaust duct to provide negative pressure for smoke exhaust. A multi-source sensor network 3 includes smoke concentration sensors 31, temperature sensors 32, and carbon monoxide sensors 33 installed in each smoke control zone, and wind speed sensors 34, rain and snow sensors 35, and outdoor temperature sensors 36 installed on the roof. All sensors are connected to an edge computing controller 4 via wired or wireless means.

[0032] The edge computing controller 4 uses an industrial-grade embedded computer with a built-in real-time operating system and intelligent control algorithms. The edge computing controller 4 includes a pattern recognition module 41, a linkage control module 42, an adaptive adjustment module 43, a zone scheduling module 44, an energy efficiency optimization module 45, a fault self-diagnosis module 46, and an interface 47 for communication with the urban fire protection IoT platform.

[0033] Reference Figure 2 The calculation logic of the linkage control module 42 is as follows: For the i-th smoke exhaust skylight, firstly, the basic opening value f(ρ_i,T_i) is calculated based on the smoke concentration ρ_i(t) and temperature T_i(t) in the smoke control zone below it. The function f can be designed as a piecewise linear function or an S-shaped function. When the smoke concentration exceeds the alarm threshold, the value of f increases rapidly. Then, the spatial correction coefficient K_spatial is calculated based on the smoke concentration distribution of all smoke control zones. Specifically, taking the zone where the current skylight is located as the center, the gradient of its smoke concentration with that of adjacent zones is calculated. The larger the gradient, the more the smoke is spreading in that direction, and the larger K_spatial is, so that the skylights on the diffusion path are opened first. Finally, the time correction coefficient K_temporal is calculated based on the fire development trend. When the smoke concentration growth rate is high, K_temporal is greater than 1, which speeds up the opening response. The final skylight target opening θ_i(t) = basic opening × K_spatial × K_temporal. The target speed ω_j(t) of the exhaust fan is calculated based on the total smoke concentration Σρ_i(t) and total heat release rate ΣQ_i(t) of all open skylights in the corresponding zones, and then processed by the speed smoothing function η.

[0034] Reference Figure 3 The resource scheduling mechanism of the zone scheduling module 44 is as follows: The building is divided into four smoke control zones: A, B, C, and D. Each zone is equipped with smoke exhaust skylights and smoke exhaust fans (or a shared fan). When a fire occurs in zone A and the smoke concentration rises sharply, the zone scheduling module 44 first adjusts the opening of the smoke exhaust skylights in zone A to the maximum, and the corresponding smoke exhaust fan speed increases. If the smoke exhaust capacity of zone A is still insufficient (smoke concentration continues to rise), the module automatically schedules the smoke exhaust equipment of adjacent zones B and C to provide support—appropriately opening the skylights in zones B and C and increasing the total smoke exhaust fan speed, so that the flow of smoke from zone A to zones B and C is effectively extracted. At the same time, the module marks zone A as a high-priority area and increases its smoke exhaust resource allocation weight.

[0035] Reference Figure 4 The specific steps of the control method are as follows: Step S1: The multi-source sensor network 3 collects smoke concentration, temperature, carbon monoxide concentration, wind speed, and rain / snow conditions on the roof in real time at a sampling frequency of 1Hz to 10Hz in each smoke control zone.

[0036] Step S2: The pattern recognition module 41 determines the operating mode based on the collected data. The first threshold is set as follows: smoke concentration 0.05 mg / m³, temperature 30℃; the second threshold is set as: smoke concentration 0.5 mg / m³; the third threshold is set as: temperature 60℃. If the smoke concentration is <0.05 mg / m³ and the temperature is <30℃, it is determined to be in daily ventilation mode; if the smoke concentration is ≥0.5 mg / m³ or the temperature is ≥60℃, it is determined to be in fire exhaust mode; if the sensor signal is detected to be outside the normal range or the actuator feedback is abnormal, it is determined to be in fault self-check mode.

[0037] Step S3: In fire smoke exhaust mode, the linkage control module 42 follows... Figure 2 The calculation logic updates the optimal opening sequence of each smoke exhaust skylight and the optimal speed sequence of each smoke exhaust fan every 0.5 seconds.

[0038] Step S4: The zone scheduling module 44 monitors the smoke concentration growth rate of each zone in real time. If the smoke concentration growth rate of a zone exceeds 5% / s, it is marked as a high-priority area, and the allocation weight of the corresponding skylight opening and fan speed is increased. When the smoke exhaust capacity of a zone is insufficient, adjacent zones are automatically scheduled to provide support.

[0039] Step S5: The linkage control module 42 outputs control commands to the electric actuator of the smoke exhaust skylight 11 and the frequency converter of the smoke exhaust fan 21 through analog output or fieldbus, so that the opening degree of the skylight and the speed of the fan are matched in coordination.

[0040] Step S6: During the smoke exhaust process, when the smoke concentration drops below the safe threshold of 0.15 mg / m³, the linkage control module 42 executes a step-down strategy: first, the opening and rotation speed are reduced to 70% of their original values ​​and maintained for 60 seconds; if the concentration continues to decrease, it is further reduced to 40% of its original value and maintained for 60 seconds; finally, the skylight and fan are closed, returning to standby mode. The duration of each stage is not less than the preset minimum holding time to prevent frequent start-stop cycles caused by a rebound in smoke concentration.

[0041] The fault self-diagnosis module 46 monitors the current of the smoke exhaust skylight drive motor, the temperature of the smoke exhaust fan bearing, and the vibration spectrum in real time. A fault prediction model is established using a Long Short-Term Memory (LSTM) network. When it predicts that the bearing temperature will exceed 85°C within the next 24 hours, a maintenance warning is issued in advance, and the system automatically switches to the backup fan.

[0042] Based on the real-time operating efficiency curve of the exhaust fan 21 (efficiency as a function of rotational speed), the energy efficiency optimization module 45 dynamically allocates the load rate of each fan using a particle swarm optimization algorithm, maximizing the overall efficiency of the unit while meeting the total exhaust demand. For example, when the total required air volume is 30,000 m³ / h, if the individual operating efficiencies of the two fans are 82% and 75% respectively, then 18,000 m³ / h is allocated to the first fan and 12,000 m³ / h to the second fan, resulting in an overall efficiency of 79.5%, which is better than uniform allocation.

[0043] The edge computing controller 4 connects to the city's fire protection IoT platform via communication interface 47 (4G / 5G or Ethernet), uploading smoke concentration, temperature, equipment operating status, and fault warning information for each smoke control zone every 10 seconds. The fire protection IoT platform can remotely force the start of the smoke extraction system or issue parameter update commands.

[0044] The implementation principle of a roof ventilation and smoke exhaust system with intelligent linkage control and adaptive adjustment functions in this application embodiment is as follows: In the daily ventilation mode, the adaptive adjustment module 43 adjusts the skylight opening and fan speed in advance according to the indoor air quality prediction model to minimize energy consumption while meeting indoor air quality requirements. When a fire occurs, the pattern recognition module 41 quickly identifies the fire smoke exhaust mode, and the linkage control module 42 dynamically calculates the optimal skylight opening sequence and fan speed sequence according to the smoke concentration and temperature spatial distribution of each smoke control zone, forming a differentiated smoke exhaust layout. The zone scheduling module 44 dynamically allocates smoke exhaust resources according to the smoke development trend, and schedules adjacent zone equipment for support when necessary. During the smoke exhaust process, the system monitors the concentration change in real time and gradually restores to the standby state using a step-down strategy. At the same time, the fault self-diagnosis module 46 continuously monitors the health status of the equipment, the energy efficiency optimization module 45 ensures the energy efficiency of daily operation, and the communication interface 47 realizes collaboration with the fire protection IoT platform. Through the above mechanisms, the system realizes integrated intelligent management of daily ventilation and fire smoke exhaust.

[0045] 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 roof ventilation and smoke exhaust system with intelligent linkage control and adaptive adjustment functions, characterized in that, include: A roof skylight array (1) is installed on the roof of a building and includes multiple smoke exhaust skylights (11) with independently controllable opening. Smoke exhaust fan unit (2), installed on the roof or in the smoke exhaust fan room, connected to the smoke exhaust duct, used to provide negative pressure smoke exhaust power; The multi-source sensor network (3) includes a smoke concentration sensor (31), a temperature sensor (32), a carbon monoxide sensor (33) installed in each smoke control zone, and a wind speed sensor (34), a rain and snow sensor (35), and an outdoor temperature sensor (36) installed on the roof. The edge computing controller (4) is connected to the roof skylight array (1), the smoke exhaust fan unit (2) and the multi-source sensor network (3) respectively, and is used to perform intelligent linkage control and adaptive adjustment; The edge computing controller (4) has the following built-in features: The pattern recognition module (41) is used to automatically identify the current working mode based on the data collected by the multi-source sensor network (3). The working modes include daily ventilation mode, fire smoke exhaust mode and fault self-test mode. The linkage control module (42) is used to dynamically calculate the optimal opening sequence of each smoke exhaust skylight (11) and the optimal speed sequence of each smoke exhaust fan (21) according to the spatial distribution of smoke concentration and temperature in each smoke control zone in the fire smoke exhaust mode, so that the skylight opening and the fan speed are matched in coordination. The adaptive adjustment module (43) is used to dynamically adjust the opening of the smoke exhaust skylight (11) and the speed of the smoke exhaust fan (21) according to the real-time changes of indoor and outdoor environmental parameters in the daily ventilation mode using a predictive control algorithm. The zone scheduling module (44) is used to dynamically allocate smoke exhaust resources according to the smoke development trend of each zone when the building is divided into multiple smoke control zones. When the smoke exhaust capacity of a certain zone is insufficient, the smoke exhaust equipment of the adjacent zone is automatically scheduled to provide support.

2. The roof ventilation and smoke exhaust system with intelligent linkage control and adaptive adjustment function according to claim 1, characterized in that, The linkage control module (42) calculates the optimal opening sequence of each smoke exhaust skylight (11) according to the following formula: θ_i(t)=f(ρ_i(t),T_i(t))·K_spatial(i,ρ_distribution)·K_temporal(t) Where θ_i(t) is the target opening of the i-th smoke exhaust skylight at time t, ρ_i(t) is the smoke concentration in the smoke control zone below the i-th skylight, T_i(t) is the temperature of the zone, f is a function of smoke concentration and temperature, K_spatial is the spatial correction coefficient based on the spatial distribution of smoke, and K_temporal is the temporal correction coefficient based on the fire development trend.

3. The roof ventilation and smoke exhaust system with intelligent linkage control and adaptive adjustment function according to claim 2, characterized in that, The linkage control module (42) also calculates the optimal speed sequence of each exhaust fan (21) according to the following formula: ω_j(t)=g(Σρ_i(t),ΣQ_i(t))·η(ω_j(t-Δt)) Where ω_j(t) is the target rotational speed of the j-th smoke exhaust fan at time t, Σρ_i(t) is the total smoke concentration of all smoke control zones corresponding to the open smoke exhaust skylights, ΣQ_i(t) is the total heat release rate, g is a function of concentration and heat release rate, and η is a speed smoothing function based on the historical operating data of the fans.

4. The roof ventilation and smoke exhaust system with intelligent linkage control and adaptive adjustment function according to claim 1, characterized in that, The linkage control module (42) is also used to: when the spatial distribution of smoke concentration and temperature meets the preset non-uniformity conditions, control the skylights near the high concentration area to open with a larger opening, and the skylights far from the high concentration area to open with a smaller opening or remain closed, forming a differentiated smoke exhaust layout.

5. The roof ventilation and smoke exhaust system with intelligent linkage control and adaptive adjustment function according to claim 1, characterized in that, The adaptive adjustment module (43) has an indoor air quality prediction model built in. The prediction model predicts the trend of indoor environmental parameters within a future preset time window based on historical environmental data and equipment operating status, and adjusts the opening of the smoke exhaust skylight (11) and the speed of the smoke exhaust fan (21) in advance based on the prediction results.

6. The roof ventilation and smoke exhaust system with intelligent linkage control and adaptive adjustment function according to claim 1, characterized in that, It also includes an energy efficiency optimization module (45), which is connected to the adaptive adjustment module (43) and is used to dynamically allocate the load rate of each smoke exhaust fan (21) according to the real-time operating efficiency curve of the smoke exhaust fan unit (2), so that the smoke exhaust fan unit (2) operates in the optimal range of comprehensive energy efficiency under the premise of meeting the smoke exhaust demand.

7. The roof ventilation and smoke exhaust system with intelligent linkage control and adaptive adjustment function according to claim 1, characterized in that, It also includes a fault self-diagnosis module (46), which is connected to the multi-source sensor network (3) and the edge computing controller (4) to monitor the bearing temperature and vibration parameters of the drive motor of the smoke exhaust skylight (11) and the smoke exhaust fan (21) in real time, and establish a fault prediction model based on historical data. When the predicted parameters exceed the preset threshold, a maintenance warning is issued in advance.

8. The roof ventilation and smoke exhaust system with intelligent linkage control and adaptive adjustment function according to claim 1, characterized in that, The partition scheduling module (44) is also used to: when the smoke concentration growth rate in a certain smoke prevention partition exceeds a preset threshold, the partition scheduling module (44) automatically marks the partition as a high priority area and increases the weight of the smoke exhaust skylight (11) and the speed of the smoke exhaust fan (21) corresponding to the partition.

9. The roof ventilation and smoke exhaust system with intelligent linkage control and adaptive adjustment function according to claim 1, characterized in that, The edge computing controller (4) is also equipped with an interface (47) for communicating with the urban fire protection IoT platform, which is used to upload system operation status parameters in real time and receive remote control commands issued by the fire protection IoT platform.

10. A method for intelligent linkage control of roof ventilation and smoke exhaust based on the system described in any one of claims 1 to 9, characterized in that, Includes the following steps: Step S1: Collect smoke concentration, temperature, carbon monoxide concentration, wind speed, and rain / snow conditions in each smoke control zone in real time through a multi-source sensor network (3); Step S2: The edge computing controller (4) determines the current working mode based on the collected data through the pattern recognition module (41). If the smoke concentration and temperature are both below the first threshold, it is determined to be the daily ventilation mode; if the smoke concentration exceeds the second threshold or the temperature exceeds the third threshold, it is determined to be the fire smoke exhaust mode; if the sensor signal is abnormal or the actuator feedback is abnormal, it is determined to be the fault self-test mode. Step S3: In the fire smoke exhaust mode, the linkage control module (42) dynamically calculates the optimal opening sequence of each smoke exhaust skylight (11) and the optimal speed sequence of each smoke exhaust fan (21) according to the spatial distribution of smoke concentration and temperature in each smoke control zone. Step S4: The zone scheduling module (44) dynamically allocates smoke exhaust resources according to the smoke development trend of each smoke control zone. When the smoke exhaust capacity of a certain zone is insufficient, it automatically schedules the smoke exhaust equipment of the adjacent zone to provide support. Step S5: The linkage control module (42) outputs control commands to the roof skylight array (1) and the smoke exhaust fan unit (2) respectively according to the calculated optimal opening sequence and optimal speed sequence, so that the opening of the smoke exhaust skylight (11) and the speed of the smoke exhaust fan (21) are matched in coordination; Step S6: During the smoke exhaust process, the linkage control module (42) monitors the smoke concentration and temperature changes in each smoke control zone in real time. When the smoke concentration drops below the safety threshold, the opening of the smoke exhaust skylight (11) and the speed of the smoke exhaust fan (21) are gradually reduced until the system returns to standby mode.

Images