Exhaust fan dynamic control method and system based on ventilation and exhaust adjustment

Abstract

The invention discloses an exhaust fan dynamic control method and system based on ventilation and exhaust adjustment, and relates to the technical field of data processing.The method comprises the steps that exhaust fan nodes are obtained, and a main trigger area and an auxiliary trigger area of the ith exhaust fan node are obtained; acquiring a preset time period, acquiring a processing window, acquiring a specified concentration data sequence of the ith exhaust fan node, and acquiring current specified concentration data of the ith exhaust fan node; acquiring an incremental trend value, an auxiliary demand value and a main demand value; if the incremental trend value exceeds a first preset threshold value, obtaining a first control strategy of the ith exhaust fan node according to a main demand value of the ith exhaust fan node; and if the progressive increase trend value does not exceed the first preset threshold value and the correction value exceeds a second preset threshold value, obtaining a second control strategy of the ith exhaust fan node according to the auxiliary demand value of the ith exhaust fan node. The method has the advantages of progressive pre-control, cooperative dynamic control and energy consumption reduction.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a dynamic control method and system for an exhaust fan based on ventilation and exhaust adjustment. Background Art

[0002] In the ventilation and exhaust duct network system, when the specified gas concentration (such as CO2, VOCs, etc.) in the main trigger area directly controlled by a certain exhaust fan node has not yet reached the preset startup threshold, the existing technology lacks an effective dynamic prediction and coordination mechanism, resulting in multiple defects in the system.

[0003] First, the existing method only monitors the instantaneous concentration in the main trigger area and cannot identify the potential risk of a specified gas concentration that continues to rise even though it has not exceeded the standard (such as a gradual increase in CO2 caused by too many people). If the fan is started after the concentration exceeds the standard, the specified gas concentration cannot be quickly reduced. Not only will the sudden high-intensity ventilation bring about an energy consumption peak, but the specified gas may have already spread to adjacent areas.

[0004] Secondly, the areas controlled by each exhaust fan node in the exhaust branch are interrelated (for example, multiple sub-workshops share air ducts), but the existing technology regards each node as an independent unit. When a certain area does not exceed the standard but the adjacent secondary trigger area (such as a sub-workshop or warehouse in the same branch) suddenly experiences pollution, the exhaust fan node in the area remains closed, and the spread of pollution cannot be curbed through coordinated ventilation, causing local environmental deterioration.

[0005] Finally, when the standard is not exceeded, the exhaust fan node is completely inactive. It is unable to use progressive ventilation to suppress the pollution trend, nor can it respond to the hidden risks of the branch as a whole (such as multiple secondary trigger areas approaching the threshold at the same time), which essentially wastes the adjustment capacity of the ventilation resources. Summary of the Invention

[0006] In response to the technical problem that passively waiting for the specified gas to accumulate to the critical point within the safety range where the concentration is lower than the starting threshold cannot prevent sudden pollution incidents, and the low-energy intervention window is missed, resulting in low ventilation efficiency, energy waste and the risk of local environmental loss of control, the present invention provides a dynamic control method and system for exhaust fans based on ventilation and exhaust adjustment.

[0007] A dynamic control method for exhaust fans based on ventilation and exhaust air regulation includes: obtaining an ventilation and exhaust duct network and multiple exhaust fan nodes arranged on the ventilation and exhaust duct network, and taking the control area directly connected to the i-th exhaust fan node as the main trigger area of ​​the i-th exhaust fan node, and taking the control areas directly connected to multiple exhaust fan nodes in the exhaust branch where the i-th exhaust fan node is located as multiple secondary trigger areas of the i-th exhaust fan node; obtaining a preset time period, and obtaining a preset time period before the current moment of the i-th exhaust fan node as a processing window, and obtaining a specified concentration data sequence of the main trigger area of ​​the i-th exhaust fan node within the processing window, and obtaining the concentration data sequence of each secondary trigger area of ​​the i-th exhaust fan node in the processing window. The current specified concentration data at the current moment; obtaining an increasing trend value according to the specified concentration data sequence of the main trigger area of ​​the i-th exhaust fan node, and obtaining a secondary demand value according to the current specified concentration data of each secondary trigger area of ​​the i-th exhaust fan node, and obtaining the main demand value of the i-th exhaust fan node according to the increasing trend value and the secondary demand value of the i-th exhaust fan node; if the increasing trend value exceeds a first preset threshold, obtaining a first control strategy for the i-th exhaust fan node according to the main demand value of the i-th exhaust fan node; if the increasing trend value does not exceed the first preset threshold and the correction value exceeds the second preset threshold, obtaining a second control strategy for the i-th exhaust fan node according to the secondary demand value of the i-th exhaust fan node.

[0008] Optionally, obtaining an increasing trend value based on the specified concentration data sequence of the main trigger area of ​​the i-th exhaust fan node includes: dividing the specified concentration data sequence of the main trigger area of ​​the i-th exhaust fan node into multiple continuous sub-processing segments in chronological order; obtaining the average specified concentration data of each sub-processing segment, and obtaining an increasing mark based on the positive or negative difference between the average specified concentration data of adjacent sub-processing segments; obtaining the increasing proportion based on the number of increasing marks and the number of sub-processing segments and using it as the increasing trend value of the i-th exhaust fan node.

[0009] Optionally, obtaining the secondary demand value based on the current specified concentration data of each secondary trigger area of ​​the i-th exhaust fan node includes: obtaining the specified concentration threshold of each secondary trigger area of ​​the i-th exhaust fan node, and obtaining the excess ratio based on the current specified concentration data and the specified concentration threshold of each secondary trigger area of ​​the i-th exhaust fan node; accumulating the excess ratios of all secondary trigger areas of the i-th exhaust fan node and obtaining the secondary demand value.

[0010] Optionally, obtaining the main demand value of the i-th exhaust fan node according to the increasing trend value and the secondary demand value of the i-th exhaust fan node includes: obtaining a correction ratio according to the increasing trend value; multiplying the correction ratio by the secondary demand value to obtain the main demand value.

[0011] Optionally, obtaining the first control strategy of the i-th exhaust fan node based on the main demand value of the i-th exhaust fan node includes: comparing the main demand value of the i-th exhaust fan node with multiple preset first numerical ranges, and determining the target first numerical range in which the main demand value of the i-th exhaust fan node is located; according to the mapping relationship between the preset first numerical range and the control instruction, obtaining the control instruction corresponding to the target first numerical range and using it as the first control strategy.

[0012] Optionally, obtaining the second control strategy of the i-th exhaust fan node based on the secondary demand value of the i-th exhaust fan node includes: comparing the secondary demand value of the i-th exhaust fan node with multiple preset second numerical ranges, and determining the target second numerical range in which the secondary demand value of the i-th exhaust fan node is located; according to the mapping relationship between the preset second numerical range and the control instruction, obtaining the control instruction corresponding to the target second numerical range and using it as the second control strategy.

[0013] A dynamic control system for exhaust fans based on ventilation and exhaust air regulation is also provided, and the system includes: a data association module for acquiring the ventilation and exhaust duct network and multiple exhaust fan nodes arranged on the ventilation and exhaust duct network, and taking the control area directly connected to the i-th exhaust fan node as the main trigger area of ​​the i-th exhaust fan node, and taking the control areas directly connected to multiple exhaust fan nodes in the exhaust branch where the i-th exhaust fan node is located as multiple sub-trigger areas of the i-th exhaust fan node; a data acquisition module for acquiring a preset time period, and acquiring a preset time period before the current moment of the i-th exhaust fan node as a processing window, and acquiring a specified concentration data sequence of the main trigger area of ​​the i-th exhaust fan node within the processing window, and acquiring the concentration data of each sub-trigger area of ​​the i-th exhaust fan node at the current moment the current specified concentration data at the moment; a data processing module, used to obtain an increasing trend value according to the specified concentration data sequence of the main trigger area of ​​the i-th exhaust fan node, and obtain a secondary demand value according to the current specified concentration data of each secondary trigger area of ​​the i-th exhaust fan node, and obtain the main demand value of the i-th exhaust fan node according to the increasing trend value and the secondary demand value of the i-th exhaust fan node; a first control and adjustment module, used to obtain a first control strategy for the i-th exhaust fan node according to the main demand value of the i-th exhaust fan node if the increasing trend value exceeds a first preset threshold; a second control and adjustment module, used to obtain a second control strategy for the i-th exhaust fan node according to the secondary demand value of the i-th exhaust fan node if the increasing trend value does not exceed the first preset threshold and the correction value exceeds the second preset threshold.

[0014] Optionally, the data processing module is also used to: divide the specified concentration data sequence of the main trigger area of ​​the i-th exhaust fan node into multiple continuous sub-processing segments in chronological order; obtain the average specified concentration data of each sub-processing segment, and obtain an incremental mark based on the positive or negative difference between the average specified concentration data of adjacent sub-processing segments; obtain the incremental proportion based on the number of incremental marks and the number of sub-processing segments and use it as the incremental trend value of the i-th exhaust fan node.

[0015] Optionally, the data processing module is also used to: obtain the specified concentration threshold of each sub-trigger area of ​​the i-th exhaust fan node, and obtain the excess ratio based on the current specified concentration data and the specified concentration threshold of each sub-trigger area of ​​the i-th exhaust fan node; accumulate the excess ratios of all sub-trigger areas of the i-th exhaust fan node and obtain the sub-demand value.

[0016] Optionally, the data processing module is further configured to: obtain a correction ratio according to the increasing trend value; and multiply the correction ratio by the secondary demand value to obtain the main demand value.

[0017] The beneficial effects of the present invention are embodied in: The dynamic control method for exhaust fans based on ventilation and exhaust adjustment first identifies the risk of slow deformation at the initial stage of accumulation of a specified gas by quantifying the concentration increase trend in the primary trigger area in real time. This allows for the initiation of progressive ventilation (e.g., continuous low-volume operation) even before the concentration reaches a critical point. This effectively suppresses the potential deterioration path of the specified gas's continued rise, avoiding the energy consumption spike caused by existing technologies that passively wait for concentrations to exceed the standard and then suddenly initiate full-power exhaust. Furthermore, through early intervention, the diffusion window of the specified gas is compressed, reducing the probability of its spread to adjacent areas. Secondly, a coordinated response mechanism for secondary trigger areas based on pipe network connectivity is constructed. When the primary area is stable but a secondary area sharing a shared air duct experiences a sudden contamination (e.g., a chemical warehouse leak), the exhaust fan nodes are no longer treated as independent units, but are activated at low speed to create a negative pressure barrier within the duct. Simultaneously, joint defense commands are sent to associated nodes on the same branch. By synchronously increasing air volume at multiple nodes, a coordinated interception network is formed. This not only blocks the path for the specified gas to backflow or spread through the duct, but also significantly reduces the energy consumption for cross-regional pollution removal through a distributed low-speed operation mode (rather than a single node operating at full power). Finally, the adjustment potential of the exhaust fan in the non-exceeding standard range is fully utilized. Through the dynamic demand of the main / secondary area risk coupling, it can respond to the progressive ventilation demand of the main area and quickly capture the sudden pollution signal of the secondary area. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly describes the drawings required for the specific embodiments or the description of the prior art. Similar elements or parts are generally identified by similar reference numerals throughout the drawings. Elements or parts in the drawings are not necessarily drawn to scale.

[0019] Figure 1 This is a partial flow chart of a method for dynamically controlling an exhaust fan based on ventilation and exhaust air regulation according to the present invention; Figure 2 This is another partial flow chart of the method for dynamically controlling an exhaust fan based on ventilation and exhaust air regulation according to the present invention; Figure 3 Schematic diagram of the steps of a dynamic control method for an exhaust fan based on ventilation and exhaust adjustment according to an embodiment of the present invention; Figure 4 Schematic diagram of a portion of steps S3 in the dynamic control method of the exhaust fan based on ventilation and exhaust adjustment of the present invention; Figure 5 Schematic diagram of another part of the steps of S3 in the dynamic control method of the exhaust fan based on ventilation and exhaust adjustment of the present invention; Figure 6 Schematic diagram of another part of the steps of S3 in the dynamic control method of the exhaust fan based on ventilation and exhaust adjustment of the present invention; Figure 7 Schematic diagram of a portion of step S4 in the dynamic control method of the exhaust fan based on ventilation and exhaust adjustment of the present invention; Figure 8 This is a schematic diagram of part of the steps of S5 in the dynamic control method of the exhaust fan based on ventilation and exhaust adjustment of the present invention. DETAILED DESCRIPTION

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0021] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention as claimed, but rather merely represents selected embodiments of the present invention. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort are intended to fall within the scope of protection of the present invention.

[0022] It should be noted that similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings. In addition, the terms "first," "second," etc. are used only to distinguish the descriptions and are not to be understood as indicating or implying relative importance.

[0023] like Figure 1 、 Figure 2 and Figure 3 As shown, a method for dynamic control of an exhaust fan based on ventilation and exhaust air regulation is provided. In one embodiment, the method includes: S1. Obtain a ventilation and exhaust duct network and multiple exhaust fan nodes arranged on the ventilation and exhaust duct network, and use the control area directly connected to the i-th exhaust fan node as the main triggering area of ​​the i-th exhaust fan node, and use the control areas directly connected to multiple exhaust fan nodes along the exhaust branch where the i-th exhaust fan node is located as multiple secondary triggering areas of the i-th exhaust fan node; S2. Obtain a preset time period, and obtain the preset time period before the current moment of the i-th exhaust fan node as a processing window, and obtain the specified concentration data sequence of the main trigger area of ​​the i-th exhaust fan node within the processing window, and obtain the current specified concentration data of each secondary trigger area of ​​the i-th exhaust fan node at the current moment; S3. Obtain an increasing trend value according to a specified concentration data sequence of a primary triggering area of ​​the i-th exhaust fan node, obtain secondary demand values ​​according to current specified concentration data of each secondary triggering area of ​​the i-th exhaust fan node, and obtain a primary demand value of the i-th exhaust fan node according to the increasing trend value and secondary demand values ​​of the i-th exhaust fan node; S4. If the increasing trend value exceeds a first preset threshold, obtaining a first control strategy for the i-th exhaust fan node according to the main demand value of the i-th exhaust fan node; S5. If the increasing trend value does not exceed the first preset threshold and the correction value exceeds the second preset threshold, obtain a second control strategy for the i-th exhaust fan node according to the secondary demand value of the i-th exhaust fan node.

[0024] In this embodiment, it should be noted that in S1, the relationship between each exhaust fan node and its physical space control range is clearly defined, and special emphasis is placed on the mutual influence between areas caused by the connectivity of the pipe network. It is specifically divided into two key definitions: First, it is clear that the i-th exhaust fan node (such as the exhaust fan numbered i) is directly connected to a specific physical space in the pipe network and is responsible for forcibly exhausting air. This space is defined as the "primary trigger area" of this node. For example, in a large open office design scenario, fan A (node ​​i) is installed at a specific position on the ceiling. The workstation area covered below it and the surrounding area of ​​several meters directly affected by its suction are the primary trigger area of ​​this fan A - here it mainly monitors the concentration of specified gases and is its main area of ​​responsibility.

[0025] Furthermore, S1 identifies other areas aerodynamically linked to the node's primary triggering area due to shared exhaust branches. These areas are defined as the "secondary triggering areas" of the i-th exhaust fan node. This is based on the fact that exhaust duct networks are not completely independent branches; the exhaust outlets of multiple exhaust fans often converge on the same branch duct. Therefore, for fan A (node ​​i), the primary triggering areas (such as adjacent conference rooms, rest areas, or data storage rooms) managed by other exhaust fans (such as fans B and C) connected to the same physical branch duct as its exhaust outlet automatically become fan A's secondary triggering areas. Although these secondary triggering areas are not directly controlled by fan A, the air they exhaust (possibly carrying specific gases) can interact within the duct and even cause backflow or diffusion within the branches. In essence, by defining primary and secondary triggering areas, S1 constructs a control domain for each exhaust fan node. This domain encompasses not only the primary triggering area directly under its jurisdiction, but also secondary triggering areas with "joint responsibility" due to shared connections on the duct network branches. This establishes the physical foundation of regional connectivity for subsequent coordinated early warning and control.

[0026] In S2, critical, time-sensitive environmental data input is provided for each exhaust fan node (taking the i-th node as an example). This step first obtains a preset time period, and then obtains a processing window based on the preset time period, with the end point being the current moment and the starting point being the moment from the current moment forward of the length of the preset time period. This processing window (such as the past 30 minutes) focuses on analyzing the historical change trajectory of the specified gas concentration in the main trigger area that the i-th exhaust fan node is directly responsible for. For this main trigger area, S2 extracts a set of specified gas concentration measurement values ​​arranged in chronological order within the entire processing window to form a complete time series data, which contains detailed information on how the concentration evolves over time and is the basic data source for subsequent analysis of its changing trends. Specifically, the preset time period (i.e., the length of the processing window) can be obtained by pre-setting a fixed value by technical personnel in this field based on the business scenario; specifically, it depends on the diffusion characteristics of the specified gas. For example, the concentration of CO2 rises slowly in crowded spaces, and the processing window needs to cover 30 to 60 minutes to capture trends, while VOCs may soar when chemicals leak, and the window needs to be shortened to 5 to 10 minutes to achieve rapid response; it also depends on the scale of the physical space. Large factories need to extend the window (such as 45 minutes) due to low air mobility and slow mixing of specified gases, while small compartments can be shortened to 15 minutes due to rapid changes.

[0027] Furthermore, in addition to the historical trend analysis of the main trigger area, S2 also focuses on the current instantaneous status of the secondary trigger areas that are associated due to the sharing of the pipe network. Unlike the main trigger area, which obtains the change sequence within the time period, for each secondary trigger area of ​​the i-th exhaust fan node (such as the adjacent workshop, warehouse or functional area that shares the same ventilation branch with it), S2 only obtains the real-time measurement value of the specified gas concentration at the current specific moment (that is, the moment when the processing window ends). This is to avoid the impact of the instantaneous high concentration in the secondary trigger area on the main trigger area. In essence, through the data collection strategy, S2 provides the main trigger area with dynamic change clues in the time dimension (the sequence within the processing window) and provides the secondary trigger area with instantaneous risk snapshots in the spatial dimension (the concentration of each point at the current moment), which together constitute a complete decision data set for the i-th node that includes environmental evolution and neighboring dynamics. For example, in a factory workshop, in addition to analyzing whether VOCs in the core processing area (primary trigger area) have been quietly increasing over the past period of time, it is also necessary to know whether there is a risk of a surge in the concentration of a specified gas in the spray room upstream (secondary trigger area) or the material storage room downstream (another secondary trigger area) of the same ventilation duct.

[0028] In S3, a dynamic demand assessment is constructed to quantify two dimensions of environmental risk (the potential deterioration tendency of the primary trigger area and the immediate threat level of the secondary trigger area), providing a decision-making basis for proactive intervention of exhaust fans when the primary trigger area does not exceed the standard. Specifically, the potential risk of the primary trigger area is quantified (increasing trend value). For the primary trigger area of ​​the i-th exhaust fan node, the concentration change pattern of the specified gas within the processing window is analyzed. First, the time concentration series of the primary trigger area is divided into multiple equal-length time periods (such as each 5-minute period), and the average concentration value is calculated within each time period. Then, the average concentration values ​​of adjacent time periods are compared in chronological order. If the average value of the latter time period is higher than that of the previous time period, an "increasing mark" is recorded (indicating an upward trend within that time period). Furthermore, the proportion of increasing marks in all adjacent time periods is calculated (for example, 9 groups of comparisons are formed for 10 time periods. If 7 groups show an increase, the trend value is 7 / 9≈0.78). The closer this value is to 1, the higher the certainty that the specified gas in the primary trigger area will continue to rise.

[0029] Furthermore, the current specified gas conditions of the secondary triggering areas that share the air duct with the i-th node are evaluated. First, for each secondary triggering area, the proportion of its current concentration that exceeds its own safety threshold is calculated (if it does not exceed the standard, it is 0). Secondly, the exceeding proportions of all secondary triggering areas are added together (for example, if secondary triggering area 1 exceeds the standard by 20%, and secondary triggering area 2 exceeds the standard by 50%, then the secondary demand value = 0.7). The larger the value, the more urgent the overall pollution pressure of the secondary triggering area group. For example, the secondary triggering areas of a certain exhaust fan node in a factory include the spray room (current VOCs exceed the standard by 30%) and the raw material warehouse (dust exceeds the standard by 15%); the secondary demand value = 0.45, reflecting that there is a significant risk of pollution spread in the adjacent areas.

[0030] Furthermore, the potential risk in the primary trigger area is coupled with the urgency level of the secondary trigger area. First, the secondary demand value is weighted and amplified using the trend value of the primary trigger area. If the primary trigger area's own trend is strong (trend value → 1), even if the secondary demand value is low (e.g., 0.3), the integrated primary demand value will still be significantly increased (e.g., 0.3 × (1 + 0.9) = 0.57). Conversely, if the primary trigger area is stable (trend value → 0), the primary demand value approaches the secondary demand value. Through a three-order assessment mechanism, within a safe range where the specified gas concentration is below the existing trigger threshold, the system proactively captures slowly increasing concentration threats in the primary trigger area. It also simultaneously detects sudden pulses of pollution in the secondary trigger area, preventing pollution backflow through shared air ducts. Ultimately, progressive ventilation is initiated during low-energy consumption windows, avoiding energy consumption spikes and the risk of uncontrolled diffusion caused by sudden high-intensity exhaust.

[0031] In S4, this step begins when the concentration of the designated gas in the primary triggering area of ​​the i-th exhaust fan node shows a significant upward trend (i.e., the increasing trend value exceeds the first preset threshold). This first preset threshold is determined by the cumulative dynamics of the designated gas within the safety interval, which is obtained through a finite number of experiments. Specifically, a concentration-time second-order derivative curve is fitted with a large amount of data, and the increasing trend value corresponding to the inflection point of the curve is taken as the first preset threshold. The core of this strategy is to use the primary demand value (integrating the potential deterioration risk of the primary area and the urgency of the secondary area) to dynamically generate a graded first control strategy, achieving progressive intervention when the risk is not exceeded but is exposed. Specifically, the demand value intervals are matched first, and several non-overlapping numerical intervals are preset (such as low / medium / high intervals). Each interval corresponds to a different pollution threat level. The calculated main demand value (reflecting the comprehensive risk level) is matched with these intervals to determine the threat level to which it belongs; secondly, differentiated control instructions corresponding to each numerical interval are used. These instructions include the speed gear of the exhaust fan (such as low gear corresponds to continuous ventilation with a light breeze, and medium gear is increased to 50% of the standard air volume). At the same time, additional instructions can be added to control the opening of related air valves or activate sensors in adjacent areas to strengthen monitoring.

[0032] In S5, this step begins when the designated gas in the primary triggering area of ​​the i-th exhaust fan node does not show a significant upward trend (i.e., the increasing trend value does not exceed the first preset threshold), but the sudden pollution pressure in the secondary triggering area reaches an emergency level (the secondary demand value exceeds the second preset threshold). The second preset threshold is determined based on the detection of sudden changes in the diffusion of the designated gas in the pipeline network, that is, obtained through a limited number of experiments. Specifically, the secondary demand values ​​at the time of a large number of historical designated gas diffusion events are averaged, and 90% of the average is taken as the first preset threshold. The core of this process is to dynamically generate a cross-region coordinated defense strategy based on the secondary demand values, achieving pollution interception and strengthening exhaust intensity when the primary area is safe but the secondary areas are in crisis. Specifically, the demand value interval is matched. Several numerical intervals corresponding to the secondary demand values ​​are preset (such as warning / emergency / high-risk intervals). The real-time calculated secondary demand value (reflecting the cumulative degree of pollution exceeding the standard in the secondary area group) is matched with these intervals to determine the interval to which it belongs. Next, based on the cross-node coordinated control instructions corresponding to each numerical interval, the control instructions corresponding to the interval are found and the second control strategy is formed.

[0033] In summary, the dynamic control method for exhaust fans based on ventilation and exhaust adjustment, firstly, by quantifying the concentration increase trend in the primary triggering area in real time, can identify the risk of slow deformation at the early stages of accumulation of a specified gas. Gradual ventilation (e.g., continuous low air volume operation) is initiated when the concentration is far from reaching the critical point. This effectively suppresses the potential deterioration path of the specified gas's continued rise, avoiding the energy consumption spike caused by the existing technology of passively waiting until the concentration exceeds the standard and then suddenly exhausting at full power. Furthermore, through early intervention, the diffusion window of the specified gas is compressed, reducing the probability of its spread to adjacent areas. Secondly, a coordinated response mechanism for secondary triggering areas based on pipe network connectivity is constructed. When the primary area is stable but a secondary area sharing the air duct experiences sudden pollution (e.g., a chemical warehouse leak), the exhaust fan nodes are no longer treated as independent units, but are activated to operate at low speed to establish a negative pressure barrier within the duct. Simultaneously, joint defense commands are sent to associated nodes on the same branch. By synchronously increasing air volume at multiple nodes, a coordinated interception network is formed. This not only blocks the path for the specified gas to flow back through the duct or diffuse, but also significantly reduces the energy consumption of cross-region pollution removal through a distributed low-speed operation mode (rather than a single node operating at full power). Finally, the exhaust fan's adjustment potential in the non-exceeding-standard range is fully utilized. Through the dynamic demand of risk coupling of the main / secondary areas, it can respond to the progressive ventilation needs of the main area and quickly capture the sudden pollution signals of the secondary area, transforming ventilation resources into a gradient-schedulable environmental adjustment method, significantly reducing overall energy consumption while ensuring the stability of the local environment.

[0034] like Figure 1 and Figure 4 As shown, in one embodiment, obtaining the increasing trend value according to the specified concentration data sequence of the main triggering area of ​​the i-th exhaust fan node in S3 includes: S31, dividing the specified concentration data sequence of the main triggering area of ​​the i-th exhaust fan node into multiple continuous sub-processing segments in chronological order; S32, obtaining the average specified concentration data of each sub-processing segment, and obtaining an increment mark according to the positive or negative difference between the average specified concentration data of adjacent sub-processing segments; S33. Obtain an increasing proportion according to the number of increasing marks and the number of sub-processing segments and use it as the increasing trend value of the i-th exhaust fan node.

[0035] In this embodiment, it should be noted that in S31, the designated concentration history sequence of the primary trigger area is divided into multiple continuous time periods of equal length along the time axis. The length of each time period is determined by the total processing window duration and the preset granularity. For example, a 30-minute processing window is divided into six segments at a 5-minute granularity, each containing a number of concentration sampling points. This discretizes the continuous time series, providing a structured data foundation for trend analysis.

[0036] Example: In the main area of ​​the data center computer room, the C The concentration sequence is divided into 6 segments with 5 minutes as the unit, and each segment contains 12 sampling points (assuming 1 sampling per minute).

[0037] In S32, the concentration average of all sampling points within each time period is calculated, and the averages of adjacent cells are compared sequentially, following the time period. If the mean of the subsequent time period is strictly greater than that of the previous time period (i.e., the difference is positive), a binary increment flag (marked as 1) is generated; otherwise, it is marked as 0. This design uses the mean to filter out transient fluctuations and only captures continuously rising signals.

[0038] Example: The average CO2 value sequence for the six time periods in the computer room is [420ppm, 428ppm, 425ppm, 432ppm, 440ppm, 445ppm]. The label sequence [1, 0, 1, 1, 1] is obtained through adjacent comparison (because 428>420→1, 425<428→0, 432>425→1...).

[0039] In S33 , the ratio of the number of times the increment mark is 1 in all adjacent time period comparisons is calculated (i.e., the number of increment marks / total number of comparisons). This ratio is defined as an increment trend value, which has a range of [0, 1]. A larger value indicates that the concentration of the specified gas is showing a more monotonically increasing trend.

[0040] Example: The above equipment room mark sequence has four increases (marker 1) and one decrease (marker 0). The increasing trend value = 4 / 5 = 0.8, reflecting that the risk of continued CO2 increase is extremely high.

[0041] It should also be noted that the increasing trend value obtained in S3 according to the specified concentration data sequence of the main trigger area of ​​the i-th exhaust fan node is expressed as:

[0042] ;in, is the increasing trend value of the i-th exhaust fan node, is the number of sub-processing segments in the specified concentration data sequence of the main trigger area of ​​the i-th exhaust fan node, is the average specified concentration data of the j+1th sub-processing segment in the specified concentration data sequence of the main trigger area of ​​the i-th exhaust fan node, It is the average specified concentration data of the jth sub-processing segment in the specified concentration data sequence of the main trigger area of ​​the i-th exhaust fan node.

[0043] It should also be noted that in the entire expression, a three-level quantification mechanism is used to solve the existing problem of being unable to identify slowly changing risks. Specifically, The continuous concentration sequence in the main area processing window is divided into m equal-length sub-processing segments to calculate the mean value of the discretized time period. ;at the same time, Is a sign function, representing the quantitative trend direction, the mean difference between adjacent periods Perform symbolic function operations when hour, , indicating that the concentration increases; when hour, , indicating that the concentration is stable or decreasing. This treatment effectively distinguishes between stable fluctuations and continuous deterioration.

[0044] Further, Represents non-negative truncated quantization, directly eliminating negative disturbances and forcing The result is reset to zero, only the strictly rising signal is retained, and the interference signals during the falling / stable period are ignored. This avoids the existing slope calculation method (such as linear regression) from counting short-term declines as negative contributions, weakening the weight of the real upward trend, and leading to misjudgment.

[0045] Further, For accumulation and normalization, it represents the quantification of trend persistence. The binary results of all adjacent time periods are summed and then divided by the total number of comparisons (m-1) to get the proportion of rising periods. . Solve the problem of “misjudging occasional rises as persistent risks”: , 30% of the time period increases (occasional risk, requiring light intervention); when , 90% of the time periods increase (continuous deterioration, requiring enhanced response). For example, a fault causes the concentration of a specified gas to increase 9 times in 10 time periods within 30 minutes ( ), triggering ventilation and cooling in advance to prevent the server from overheating.

[0046] like Figure 1 and Figure 5 As shown, in one embodiment, obtaining the secondary demand value according to the current specified concentration data of each secondary triggering area of ​​the i-th exhaust fan node in S3 includes: S34, obtaining a designated concentration threshold value of each secondary triggering area of ​​the i-th exhaust fan node, and obtaining an exceeding standard ratio based on the current designated concentration data of each secondary triggering area of ​​the i-th exhaust fan node and the designated concentration threshold value; S35 , accumulating the excess ratios of all secondary triggering areas of the i-th exhaust fan node and obtaining a secondary demand value.

[0047] In this embodiment, it should be noted that in S34, for each secondary triggering zone, the preset safety threshold for the designated gas is obtained. The absolute difference between the current real-time concentration value in that zone and the safety threshold is calculated, and this difference is divided by the safety threshold to obtain the excess ratio. If the current concentration does not exceed the standard, the ratio is recorded as 0. This design quantifies the instantaneous pollution pressure of a single secondary zone.

[0048] Example: A factory's exhaust fan subzones include a hazardous chemical storage (threshold 100 ppm) and a raw material pretreatment room (threshold 80 ppm). The measured concentrations are 112 ppm and 75 ppm, respectively. The percentage exceeding the standard is (112 - 100) / 100 = 0.12, and (75 - 80) / 80 = 0 (0 if the standard is not exceeded).

[0049] In S35, the non-negative percentages of excess pollution in all secondary triggering areas are accumulated, and the resulting sum is used as the secondary demand value. This value reflects the overall pollution diffusion pressure of the secondary area group associated with the shared air duct and is the core basis for the coordinated response of the pipe network.

[0050] Example: In the example above, the cumulative excess ratio of the two sub-areas is 0.12 + 0 = 0.12. If the excess ratio of the third sub-area (packaging room) is 0.2, the total sub-demand value is 0.32.

[0051] It should also be noted that in S3, the secondary demand value is obtained according to the current specified concentration data of each secondary triggering area of ​​the i-th exhaust fan node as follows: ;in, is the secondary demand value of the i-th exhaust fan node, is the number of secondary triggering areas of the i-th exhaust fan node, is the excess ratio of the kth secondary triggering area of ​​the i-th exhaust fan node, Specifies the concentration threshold for the kth secondary triggering area of ​​the i-th exhaust fan node.

[0052] It should also be noted that the entire expression implements network-level risk aggregation. Specifically, To quantify relative excess, unify the risk scale of multiple specified gases. For the kth secondary trigger area, calculate its current concentration Exceeding safety threshold The relative proportions (rather than absolute differences) of the thresholds for different gases (e.g., CO2 / VOCs) or areas (warehouse / workshop) vary significantly. Using only absolute differences (e.g., a 100ppm CO2 excess vs. a 5ppm VOCs excess) prevents direct comparison of risk levels. Relative proportions eliminate dimensional differences: 200ppm CO2 (threshold 1000ppm) → 0.2% excess; 15ppm VOCs (threshold 10ppm) → 0.5% excess; VOC pollution is more pressing.

[0053] Furthermore, Non-negative truncation is achieved to eliminate interference from the safe area.

[0054] when When the value is not exceeded, the output is forced to be 0. This solves the problem of existing technologies misjudging the overall safety of branches by ignoring uncontaminated sub-areas in shared air ducts due to ignoring the areas that do not exceed the standard. The entire expression ensures that only the threat value of the areas that actually exceed the standard is accumulated, preventing the safe areas from diluting the overall risk value (for example, if two of three sub-areas do not exceed the standard, the accumulated value still reflects the actual risk).

[0055] Further, This system dynamically senses network-level pollution pressure by accumulating pollution levels across regions. The percentage of excess pollution levels in all P secondary triggering regions is summed. When multiple regions simultaneously approach or exceed thresholds, a single regional excess may be overlooked (e.g., a VOCs excess of 0.1 in a workshop). This cumulative effect amplifies hidden risks (e.g., if three regions each exceed the threshold by 0.1, the secondary demand value will be 0.3), addressing the vulnerability of unresponsiveness to critical pollution in multiple regions.

[0056] like Figure 1 and Figure 6 As shown, in one embodiment, obtaining the main demand value of the i-th exhaust fan node according to the increasing trend value and the secondary demand value of the i-th exhaust fan node in S3 includes: S36, obtaining a correction ratio according to the increasing trend value; S37. Multiply the correction ratio by the secondary demand value to obtain the main demand value.

[0057] In this embodiment, it should be noted that in S36, the increasing trend value of the primary region is directly used as a correction factor. This factor represents the potential risk intensity of the primary region itself: when the trend value is 0 (no increase), the factor is ineffective; when the trend value is close to 1, the factor has a strong correction effect on the secondary demand.

[0058] In S37 (Demand Fusion), the primary demand value is obtained by multiplying the secondary demand value by (1 + correction factor). When the primary region's trend is strong (factor → 1), the primary demand value ≈ 2 × the secondary demand value. Even if the secondary region is slightly polluted, the response is still high-risk. When the primary region's trend is stable (factor → 0), the primary demand value ≈ the secondary demand value. The response is entirely based on the pressure in the secondary region.

[0059] For example, in a laboratory, the trend value of the main area is 0.9 (strong rise) and the secondary demand value is 0.2 (low pressure). The main demand value is (1+0.9)×0.2=0.38, which triggers a moderate response. If the trend value is only 0.1, the main demand value is 1.1×0.2=0.22, which triggers a low-level response.

[0060] It should also be noted that in S3, the main demand value of the i-th exhaust fan node is obtained according to the increasing trend value and the secondary demand value of the i-th exhaust fan node as follows: ;in, is the secondary demand value of the i-th exhaust fan node, is the increasing trend value of the i-th exhaust fan node, is the main demand value of the i-th exhaust fan node.

[0061] It should also be noted that in the entire expression, As the correction ratio, the base coefficient 1 guarantees the secondary demand value The original risk is not diluted, the trend amplifier Incremental trend value based on main area When the designated gas in the main area continues to rise but does not exceed the standard (such as CO2 rising at 0.5ppm / minute), the existing technology makes independent judgments on the main and secondary areas. If the secondary area does not exceed the standard, there is no response at all, but through (1+ ) structure is modified, even if Safety, main requirement value Control limits may also be reached. The larger the value, the higher the response intensity, which converts the progressive ventilation demand of the main area into an effective control instruction. is strictly constrained to [0, 1], so that , to avoid distortion of control instructions caused by risk value of a single area.

[0062] like Figure 2 and Figure 7 As shown, in one embodiment, obtaining the first control strategy of the i-th exhaust fan node according to the main demand value of the i-th exhaust fan node in S4 includes: S41, comparing the main demand value of the i-th exhaust fan node with a plurality of preset first value ranges, and determining a target first value range in which the main demand value of the i-th exhaust fan node falls; S42. According to a preset mapping relationship between the first numerical range and the control instruction, obtain the control instruction corresponding to the target first numerical range and use it as the first control strategy.

[0063] In this implementation, it's important to note that the master demand value is precisely located using preset, non-overlapping, continuous intervals (e.g., low risk [0, 0.3], medium risk [0.3, 0.6], and high risk [0.6, 1.0]). Each interval corresponds to a critical turning point in the diffusion of a specific gas. Based on fluid dynamics simulation and historical accident data analysis, for example, in an air duct, when the master demand value is ≥ 0.3, the probability of the specified gas diffusing to adjacent areas exceeds 40%. When the master demand value is ≥ 0.6, the risk of branch pressure imbalance increases dramatically.

[0064] In S42, a step-by-step response strategy is used to bind control instructions. The low-risk interval represents the instruction for the fan to operate at a low speed (such as 30% air volume) and only maintain the basic negative pressure; the medium-risk interval represents the instruction for the medium air volume (60%) plus the associated air valve to suppress diffusion; the high-risk interval represents the instruction for the full-load air volume (100%), closing the air supply valve in the high-risk area and starting the joint defense of adjacent nodes.

[0065] It should also be noted that multiple first-level value ranges can be obtained through a limited number of experiments and gas diffusion coefficients (e.g., 0.16 cm² / s for CO2 and 0.08 cm² / s for VOCs). The success rate of ventilation interventions can also be tracked in real time (number of successful pollution suppressions divided by total number of triggers). When the success rate of a certain interval falls below 85%, the interval is automatically contracted by 0.05 and moved to the next higher-level interval. For example, the initial high-risk range [0.6, 1.0] had a success rate of only 80%, but adjusting it to [0.65, 1.0] increased the success rate to 89%.

[0066] like Figure 2 and Figure 8 As shown, in one embodiment, obtaining the second control strategy of the i-th exhaust fan node according to the secondary demand value of the i-th exhaust fan node in S5 includes: S51, comparing the secondary demand value of the i-th exhaust fan node with a plurality of preset second value ranges, and determining a target second value range in which the secondary demand value of the i-th exhaust fan node is located; S52: According to the preset mapping relationship between the second numerical range and the control instruction, obtain the control instruction corresponding to the target second numerical range and use it as the second control strategy.

[0067] In this embodiment, it should be noted that in S51, the preset coordinated response intervals (such as the warning interval [0.1, 0.4], the emergency interval [0.4, 0.7], and the high-risk interval (above 0.7)) are matched based on the secondary demand value (reflecting the instantaneous pollution superposition pressure of multiple secondary triggering areas in the shared air duct). The interval boundaries are set based on the specified gas diffusion velocity threshold within the air duct, which can also be obtained through a limited number of experiments and the gas diffusion coefficient; the warning interval specifies the time window in which the specified gas may enter the adjacent air duct (such as 5 minutes for CO2 and 90 seconds for VOCs); the high-risk interval indicates that the specified gas has diffused to the critical point of the main air duct (requiring immediate physical blockage).

[0068] Example: When the secondary demand value reaches the emergency range, it indicates that at least two secondary areas (such as the hazardous chemicals warehouse and the spray room) exceed the standard at the same time, and cross-node exhaust linkage needs to be activated.

[0069] In S52, a network-level collaborative strategy is used to bind commands. During the alert period, the exhaust fan at this node is turned on at its lowest setting (20% air volume) and a warning signal is sent to nodes on the same branch. During the emergency period, the air volume at this node is increased to a medium setting (50%), the air volume at adjacent nodes is increased by 30%, and the branch air valve opening is adjusted. During the high-risk period, the air volume at this node is increased to its full setting (100%), the valves in the pollution source area are forcibly closed, and the emergency exhaust protocol for all branches is activated.

[0070] A dynamic control system for exhaust fans based on ventilation and exhaust air regulation is also provided, the system comprising: a data association module for acquiring a ventilation and exhaust duct network and a plurality of exhaust fan nodes disposed on the ventilation and exhaust duct network, and determining a control area directly connected to the i-th exhaust fan node as a primary triggering area of ​​the i-th exhaust fan node, and determining control areas directly connected to a plurality of exhaust fan nodes along an exhaust branch where the i-th exhaust fan node is located as a plurality of secondary triggering areas of the i-th exhaust fan node; A data acquisition module is used to obtain a preset time period, and obtain the preset time period before the current moment of the i-th exhaust fan node as a processing window, and obtain the specified concentration data sequence of the main trigger area of ​​the i-th exhaust fan node within the processing window, and obtain the current specified concentration data of each secondary trigger area of ​​the i-th exhaust fan node at the current moment; a data processing module, configured to obtain an increasing trend value based on a specified concentration data sequence of a primary triggering area of ​​the i-th exhaust fan node, obtain secondary demand values ​​based on current specified concentration data of each secondary triggering area of ​​the i-th exhaust fan node, and obtain a primary demand value of the i-th exhaust fan node based on the increasing trend value and secondary demand value of the i-th exhaust fan node; a first control and adjustment module, configured to obtain a first control strategy for the i-th exhaust fan node according to the main demand value of the i-th exhaust fan node if the increasing trend value exceeds a first preset threshold; The second control and adjustment module is used to obtain the second control strategy of the i-th exhaust fan node according to the secondary demand value of the i-th exhaust fan node if the increasing trend value does not exceed the first preset threshold and the correction value exceeds the second preset threshold.

[0071] In one embodiment, the data processing module is also used to: divide the specified concentration data sequence of the main trigger area of ​​the i-th exhaust fan node into multiple continuous sub-processing segments in chronological order; obtain the average specified concentration data of each sub-processing segment, and obtain an incremental mark based on the positive or negative difference between the average specified concentration data of adjacent sub-processing segments; obtain the incremental proportion based on the number of incremental marks and the number of sub-processing segments and use it as the incremental trend value of the i-th exhaust fan node.

[0072] In one embodiment, the data processing module is also used to: obtain the specified concentration threshold of each sub-trigger area of ​​the i-th exhaust fan node, and obtain the excess ratio based on the current specified concentration data and the specified concentration threshold of each sub-trigger area of ​​the i-th exhaust fan node; accumulate the excess ratios of all sub-trigger areas of the i-th exhaust fan node and obtain the sub-demand value.

[0073] In one embodiment, the data processing module is further configured to: obtain a correction ratio according to the increasing trend value; and multiply the correction ratio by the secondary demand value to obtain the main demand value.

[0074] In this embodiment, it should be noted that, regarding the above-mentioned exhaust fan dynamic control system based on ventilation and exhaust air regulation, the specific method of performing the operation has been described in detail in the implementation method of the exhaust fan dynamic control method based on ventilation and exhaust air regulation, and will not be elaborated here.

[0075] The preferred embodiments of the present disclosure are described in detail above in conjunction with the accompanying drawings. However, the present disclosure is not limited to the specific details of the above embodiments. Within the technical concept of the present disclosure, various simple modifications can be made to the technical solutions of the present disclosure, and these simple modifications all fall within the scope of protection of the present disclosure.

[0076] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, the present disclosure will not further describe various possible combinations.

[0077] In addition, the various embodiments of the present disclosure may be arbitrarily combined, and as long as they do not violate the concept of the present disclosure, they should also be regarded as the contents disclosed by the present disclosure.

[0078] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some or all of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and description of the present invention.

Claims

1. A dynamic control method for an exhaust fan based on ventilation and exhaust adjustment, characterized in that: include: Obtain a ventilation and exhaust duct network and multiple exhaust fan nodes arranged on the ventilation and exhaust duct network, and use the control area directly connected to the i-th exhaust fan node as the main trigger area of ​​the i-th exhaust fan node, and use the control areas directly connected to multiple exhaust fan nodes along the exhaust branch where the i-th exhaust fan node is located as multiple secondary trigger areas of the i-th exhaust fan node; Obtain a preset time period, and obtain the preset time period before the current moment of the i-th exhaust fan node as a processing window, and obtain the specified concentration data sequence of the main trigger area of ​​the i-th exhaust fan node within the processing window, and obtain the current specified concentration data of each secondary trigger area of ​​the i-th exhaust fan node at the current moment; Obtain an increasing trend value according to the specified concentration data sequence of the main trigger area of ​​the i-th exhaust fan node, obtain a secondary demand value according to the current specified concentration data of each secondary trigger area of ​​the i-th exhaust fan node, and obtain a main demand value of the i-th exhaust fan node according to the increasing trend value and secondary demand value of the i-th exhaust fan node; If the increasing trend value exceeds a first preset threshold, obtaining a first control strategy for the i-th exhaust fan node according to the main demand value of the i-th exhaust fan node; If the increasing trend value does not exceed the first preset threshold and the correction value exceeds the second preset threshold, the second control strategy of the i-th exhaust fan node is obtained according to the secondary demand value of the i-th exhaust fan node.

2. The dynamic control method for exhaust fans based on ventilation and exhaust adjustment according to claim 1, characterized in that: The step of obtaining the increasing trend value according to the specified concentration data sequence of the main triggering area of ​​the i-th exhaust fan node includes: Divide the specified concentration data sequence of the main trigger area of ​​the i-th exhaust fan node into multiple continuous sub-processing segments in chronological order; Obtaining average specified concentration data of each sub-processing segment, and obtaining an increment mark according to the positive or negative difference between the average specified concentration data of adjacent sub-processing segments; The increasing proportion is obtained according to the number of increasing marks and the number of sub-processing segments and is used as the increasing trend value of the i-th exhaust fan node.

3. The dynamic control method of the exhaust fan based on ventilation and exhaust adjustment according to claim 1 is characterized in that: The obtaining of the secondary demand value according to the current designated concentration data of each secondary triggering area of ​​the i-th exhaust fan node includes: Obtain the specified concentration threshold of each secondary triggering area of ​​the i-th exhaust fan node, and obtain the exceeding standard ratio based on the current specified concentration data of each secondary triggering area of ​​the i-th exhaust fan node and the specified concentration threshold; The excess ratios of all secondary triggering areas of the i-th exhaust fan node are accumulated to obtain the secondary demand value.

4. The method for dynamic control of exhaust fans based on ventilation and exhaust adjustment according to claim 1, characterized in that: The step of obtaining the main demand value of the i-th exhaust fan node according to the increasing trend value and the secondary demand value of the i-th exhaust fan node includes: Get the correction ratio based on the increasing trend value; Multiply the correction ratio by the secondary demand value and get the primary demand value.

5. The method for dynamic control of exhaust fans based on ventilation and exhaust adjustment according to claim 1, characterized in that: The step of obtaining a first control strategy for the i-th exhaust fan node according to the main demand value of the i-th exhaust fan node includes: Compare the main demand value of the i-th exhaust fan node with a plurality of preset first value ranges, and determine a target first value range in which the main demand value of the i-th exhaust fan node is located; According to the mapping relationship between the preset first numerical range and the control instruction, the control instruction corresponding to the target first numerical range is obtained and used as the first control strategy.

6. The method for dynamic control of exhaust fans based on ventilation and exhaust adjustment according to claim 1, characterized in that: The method of obtaining the second control strategy of the i-th exhaust fan node according to the secondary demand value of the i-th exhaust fan node includes: Comparing the secondary demand value of the i-th exhaust fan node with a plurality of preset second value ranges, and determining a target second value range in which the secondary demand value of the i-th exhaust fan node is located; According to the mapping relationship between the preset second numerical range and the control instruction, the control instruction corresponding to the target second numerical range is obtained and used as the second control strategy.

7. A dynamic control system for exhaust fans based on ventilation and exhaust adjustment, characterized in that: The system comprises: a data association module for acquiring a ventilation and exhaust duct network and a plurality of exhaust fan nodes disposed on the ventilation and exhaust duct network, and determining a control area directly connected to the i-th exhaust fan node as a primary triggering area of ​​the i-th exhaust fan node, and determining control areas directly connected to a plurality of exhaust fan nodes along an exhaust branch where the i-th exhaust fan node is located as a plurality of secondary triggering areas of the i-th exhaust fan node; A data acquisition module is used to obtain a preset time period, and obtain the preset time period before the current moment of the i-th exhaust fan node as a processing window, and obtain the specified concentration data sequence of the main trigger area of ​​the i-th exhaust fan node within the processing window, and obtain the current specified concentration data of each secondary trigger area of ​​the i-th exhaust fan node at the current moment; a data processing module, configured to obtain an increasing trend value based on a specified concentration data sequence of a primary triggering area of ​​the i-th exhaust fan node, obtain secondary demand values ​​based on current specified concentration data of each secondary triggering area of ​​the i-th exhaust fan node, and obtain a primary demand value of the i-th exhaust fan node based on the increasing trend value and secondary demand value of the i-th exhaust fan node; a first control and adjustment module, configured to obtain a first control strategy for the i-th exhaust fan node according to the main demand value of the i-th exhaust fan node if the increasing trend value exceeds a first preset threshold; The second control and adjustment module is used to obtain the second control strategy of the i-th exhaust fan node according to the secondary demand value of the i-th exhaust fan node if the increasing trend value does not exceed the first preset threshold and the correction value exceeds the second preset threshold.

8. The dynamic control system for exhaust fans based on ventilation and exhaust adjustment according to claim 7, characterized in that: The data processing module is further configured to: Divide the specified concentration data sequence of the main trigger area of ​​the i-th exhaust fan node into multiple continuous sub-processing segments in chronological order; Obtaining average specified concentration data of each sub-processing segment, and obtaining an increment mark according to the positive or negative difference between the average specified concentration data of adjacent sub-processing segments; The increasing proportion is obtained according to the number of increasing marks and the number of sub-processing segments and is used as the increasing trend value of the i-th exhaust fan node.

9. The dynamic control system for exhaust fans based on ventilation and exhaust adjustment according to claim 7, characterized in that: The data processing module is further configured to: Obtain the specified concentration threshold of each secondary triggering area of ​​the i-th exhaust fan node, and obtain the exceeding standard ratio based on the current specified concentration data of each secondary triggering area of ​​the i-th exhaust fan node and the specified concentration threshold; The excess ratios of all secondary triggering areas of the i-th exhaust fan node are accumulated to obtain the secondary demand value.

10. The dynamic control system for exhaust fans based on ventilation and exhaust adjustment according to claim 7, characterized in that: The data processing module is further configured to: Get the correction ratio based on the increasing trend value; Multiply the correction ratio by the secondary demand value and get the primary demand value.

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