High-efficiency purification and self-cleaning civil air defense building ventilation opening protective door equipment

Abstract

The present application relates to the technical field of air defense building ventilation equipment, and particularly relates to a high-efficiency purification and self-cleaning air defense building ventilation port protective door equipment, which comprises a door frame, a door body, a driving unit, a sensing system, a purification device, a self-cleaning execution unit and a control unit. The sensing system comprehensively collects environment and equipment data, and the control unit calculates a comprehensive pollution index and determines a pollution level by using a weighted fusion algorithm. Based on fluid simulation, the protective and ventilation efficiency coefficients under different door body opening angles are calculated. The optimal opening angle of the door body and the optimal operating parameters of the purification device are dynamically solved by using a multi-objective optimization algorithm. The self-cleaning effect is intelligently triggered and verified according to the filter screen state and the pollution level. The present application realizes adaptive intelligent regulation and control of the protective door in a complex pollution environment, effectively balances safety protection and ventilation efficiency, and improves purification capacity and automatic maintenance level.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of civil air defense engineering and air purification technology, and particularly relates to a high-efficiency purification and self-cleaning civil air defense building ventilation port protective door equipment. BACKGROUND

[0002] The civil air defense building ventilation port protective door equipment is a comprehensive protection device for adjusting the opening angle of the door body, purifying air and realizing self-cleaning function, mainly composed of a door frame, a door body, a driving unit, a sensing system, a purification device and a self-cleaning execution unit, and each component cooperates to realize air purification, pollution protection and equipment maintenance and other functions.

[0003] The utility model with the publication number CN220955362U discloses a rail transit clean type ventilation protective sealed door, including the door frame, the civil air defense door body is placed in the door frame, the ventilation port is opened in the civil air defense door body, the installation cavity is communicated with the ventilation port and is arranged, the installation cavity top is equipped with the air duct that is communicated with the outside and is arranged, the air duct inside is symmetrically installed with multiple air exchangers, the civil air defense door body is connected with the ventilation component that controls the ventilation port and opens and closes state, the air exchanger works, and the outside air is transported to the ventilation port through the air duct, and the internal air is output to the air duct outside through the air exchanger in reverse, and the space is ventilated and aerated, simultaneously, rotating the rotating wheel, the rotating wheel drives the linkage gear set that is composed of the connecting gear and the toothed plate to act, the toothed plate follows the displacement of the connecting gear rotation, and then drives the sealing plate to translate left and right, controls the open and close state of the ventilation port position, and the toothed plate is slidably connected in the installation cavity through the guide seat and the sliding groove, and the smoothness in the movement process of the toothed plate is increased.

[0004] The utility model with the publication number CN219119101U discloses a clean type ventilation protective civil air defense sealed door, including door frame and sealed door body, the outside of sealed door body is equipped with heat dissipation mechanism;The sealed door body is composed of fireproof plate, heat insulation layer, sound insulation layer and insulating layer, the number of fireproof plate is two, two fireproof plate is located heat insulation layer and insulating layer is apart from one side respectively;The heat dissipation mechanism includes the installation box that is fixedly installed in the outside of sealed door body, the inside fixed mounting of installation box has the mounting bracket, the outside fixed mounting of mounting bracket has the cooling fan.

[0005] The current device for protecting the ventilation opening is usually equipped with a basic filtering device to realize the air purification function. However, the environmental data acquisition dimension is single, and cannot be deeply coupled with the control algorithm, so that the dynamic adjustment capability of the purification device operation parameter is limited, and the purification efficiency under different pollution levels has certain limitations. In addition, the cleaning of the filter screen in the existing device depends on manual operation or a simple timing cleaning mechanism, the cleaning trigger logic cannot introduce external environmental pollution variables, and lacks quantifiable verification and closed-loop adjustment of the cleaning effect, so the cleaning effect is often not ideal. In terms of door opening angle adjustment, there is a lack of quantitative evaluation means based on real-time flow field simulation, and the safety protection level cannot be embedded into the optimization decision process as a rigid constraint, so that the adaptability of the device in complex environment is limited.

[0006] In view of the above problems, the present application provides a high-efficiency purification and self-cleaning civil air defense building ventilation opening protection door device to solve the above problems. SUMMARY

[0007] The present application aims to provide a high-efficiency purification and self-cleaning civil air defense building ventilation opening protection door device to solve the above problems.

[0008] To solve the above technical problems, the technical solution adopted by the present application is:

[0009] A high-efficiency purification and self-cleaning civil air defense building ventilation opening protection door device, comprising a door frame, a door body embedded in the door frame, and a driving unit in transmission connection with the door body;

[0010] Further comprising:

[0011] A sensing system for collecting environmental data and device state data; the environmental data includes the concentration of toxic gases, the concentration of particulate matter, the temperature and humidity, and the ventilation flow rate inside the ventilation opening; the device state data includes the opening angle of the door body, the working current of the driving unit, the pressure difference on both sides of the filter screen of the purification device, the cumulative running time of the purification device, and the remaining amount of the self-cleaning medium;

[0012] A purification device arranged on the ventilation path for filtering and purifying air;

[0013] A self-cleaning execution unit for performing cleaning action on the purification device;

[0014] A control unit electrically connected with the sensing system, the driving unit, the purification device and the self-cleaning execution unit respectively;

[0015] The control unit is configured to:

[0016] Step A: based on the environmental data, calculate the comprehensive pollution index by weighted fusion algorithm, and determine the pollution level, purification priority and protection level accordingly;

[0017] Step B: Based on the pollution level, the ventilation flow rate, and the door structure parameters, calculate the protection effect coefficient and the ventilation efficiency coefficient under different door opening angles through fluid simulation simulation;

[0018] Step C: Based on the protection effect coefficient, the ventilation efficiency coefficient, the protection level, and the driving unit operating current, calculate the optimal opening angle of the door, and control the driving unit to drive the door to the optimal opening angle;

[0019] Step D: Based on the purification priority, the pollutant concentration inside and outside the ventilation port, calculate the optimal operating parameters of the purification device through an optimization algorithm, and control the purification device to work according to the optimal operating parameters;

[0020] Step E: Based on the pressure difference across the filter screen, the cumulative operating time, the purification efficiency, the pollution level, and the amount of self-cleaning medium, determine the self-cleaning requirement, and control the self-cleaning execution unit to perform the corresponding cleaning action.

[0021] Further, the weighting fusion algorithm in step A includes: calculating the gas pollution sub-index, the particulate matter pollution sub-index, the temperature and humidity deviation index, and the flow rate deviation index respectively; using a preset weight to fuse each sub-index to obtain the comprehensive pollution index; the preset weight is determined by training a plurality of sets of historical environmental data.

[0022] Further, the fluid simulation simulation process in step B includes: establishing a three-dimensional model of the door and the door frame; using the ventilation flow rate and the pollutant concentration corresponding to the pollution level as boundary conditions; by solving the fluid dynamics equation, the flow field and the pollutant concentration distribution under different door opening angles are obtained, and the protection effect coefficient and the ventilation efficiency coefficient are calculated accordingly.

[0023] Further, the control unit is further configured to periodically execute steps A and B, dynamically adjust the boundary conditions according to the updated pollution level, and recalculate the protection effect coefficient and the ventilation efficiency coefficient to achieve adaptive adjustment of the door opening angle.

[0024] Further, the process of calculating the optimal opening angle in step C includes:

[0025] Construct a multi-objective optimization function with the protection effect coefficient, the ventilation efficiency coefficient, and an energy consumption coefficient calculated based on the driving current as the target; find the angle that maximizes the value of the optimization function by traversing the door opening angle as the preliminary optimal angle; then modify the preliminary optimal angle according to the protection level to obtain the final optimal opening angle.

[0026] Further, the optimization algorithm in step D is a particle swarm optimization algorithm, and the control unit is configured to dynamically adjust an inertia weight of the particle swarm optimization algorithm according to the level of the purification priority, wherein the higher the purification priority, the smaller the inertia weight, so as to accelerate the convergence speed.

[0027] Further, the process of judging the self-cleaning demand in step E includes:

[0028] determining a cleaning demand correction coefficient according to the pollution level; calculating a filter screen pollution index based on the pressure difference between the two sides of the filter screen, the cumulative running time and the purification efficiency; multiplying the filter screen pollution index by the cleaning demand correction coefficient to obtain a self-cleaning demand degree; and when the self-cleaning demand degree exceeds a threshold value, selecting a self-cleaning mode according to the remaining amount of the self-cleaning medium.

[0029] Further, the control unit is further configured to form a self-cleaning closed-loop control: after the self-cleaning execution unit completes the cleaning action, verifying the cleaning effect; if the decrease of the pressure difference between the two sides of the filter screen after cleaning does not reach a first preset proportion, or the recovery of the purification efficiency does not reach a second preset proportion, then controlling the self-cleaning execution unit to upgrade the cleaning mode or prolong the cleaning time before performing the cleaning action again.

[0030] Further, the control unit is configured to form a door body adjustment closed-loop control: after controlling the driving unit to act, receiving the real-time opening and closing angle of the door body and the working current of the driving unit fed back by the sensing system; if the deviation of the real-time opening and closing angle of the door body from the target angle exceeds an angle tolerance, then adjusting the output of the driving unit to correct the deviation; if the working current of the driving unit exceeds a safe current threshold value, then immediately stopping driving and triggering an alarm signal.

[0031] Further, the fluid simulation model in step B is calibrated by experimental data, and the calibration process includes: comparing the simulation data and the measured data under different door body opening and closing angles and ventilation flow rates, and adjusting the fluid physical property parameters in the simulation model until the error between the simulation data and the measured data is less than a preset error threshold.

[0032] Compared with the prior art, the present application has the following beneficial effects:

[0033] The present application solves the problem of limited environmental data collection range of traditional equipment by comprehensively collecting environmental data through a sensing system and calculating a comprehensive pollution index in combination with a weighted fusion algorithm. The protective effect coefficient and ventilation efficiency coefficient under different door opening angles are calculated through fluid simulation, and the comprehensive optimization of the door opening angle is realized. At the same time, a self-cleaning closed-loop control mechanism is introduced, which determines whether to upgrade the cleaning method or extend the cleaning time after the self-cleaning execution unit completes the cleaning action according to the cleaning effect, solving the problem of unsatisfactory cleaning effect of traditional equipment. The operating parameters of the purification device are dynamically adjusted through the particle swarm optimization algorithm, improving the response speed and processing capacity of the equipment under the condition of sudden high concentration pollution. The door adjustment closed-loop control mechanism of the present application can monitor the door opening angle and driving unit working current in real time, ensure that the door is accurately adjusted to the target angle, and avoid safety hazards caused by overload. The purification device of the present application adopts a multi-layer filter screen structure, which significantly improves the air purification efficiency, and through the buckle structure, the filter screen can be conveniently disassembled and replaced, reducing the maintenance cost. BRIEF DESCRIPTION OF DRAWINGS

[0034] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can also be obtained without creative labor.

[0035] Figure 1 The present application is a system architecture diagram.

[0036] Figure 2 The present application is a control unit logic flow chart.

[0037] Reference signs:

[0038] 101 door frame, 102 door body, 103 driving unit, 104 control unit, 105 self-cleaning execution unit, 106 sensing system, 107 purification device. DETAILED DESCRIPTION

[0039] In the following, only some exemplary embodiments are simply described. As those skilled in the art can recognize, the described embodiments can be modified in various different ways without departing from the spirit or scope of the embodiments of the present application. Therefore, the drawings and the description are considered to be exemplary in nature rather than limiting. The embodiments of the present application are described in detail below with reference to the drawings.

[0040] Example 1:

[0041] Reference Figure 1 and Figure 2The utility model provides a high -efficient purifying and self -cleaning civil air defense building ventilation opening protective door equipment, including door frame 101, the door body 102 of embedding in door frame 101 and with door body 102 transmission connection drive unit 103,

[0042] Further comprising:

[0043] Sensing system 106 for collecting environmental data and equipment state data, the environmental data includes the concentration of toxic gases, particulate matter concentration, temperature and humidity and ventilation flow rate inside the ventilation opening, the equipment state data includes the opening angle of the door body 102, the working current of the drive unit 103, the pressure difference on both sides of the filter screen of the purification device, the cumulative running time of the purification device and the remaining amount of self-cleaning medium;

[0044] Purification device arranged on the ventilation path for filtering and purifying air;

[0045] Self-cleaning execution unit 105 for performing cleaning action on the purification device;

[0046] Control unit 104 is electrically connected with the sensing system 106, the drive unit 103, the purification device and the self-cleaning execution unit 105 respectively;

[0047] The control unit 104 is configured to:

[0048] Step A: based on the environmental data, the comprehensive pollution index is calculated by weighted fusion algorithm, and the pollution grade, purification priority and protection level are determined accordingly;

[0049] Step B: based on the pollution grade, the ventilation flow rate and the door body 102 structure parameter, the protection effect coefficient and the ventilation efficiency coefficient under different door body 102 opening angles are calculated by fluid simulation simulation;

[0050] Step C: based on the protection effect coefficient, the ventilation efficiency coefficient, the protection level and the working current of the drive unit 103, the optimal opening angle of the door body 102 is calculated, and the drive unit 103 is controlled to drive the door body 102 to the optimal opening angle;

[0051] Step D: based on the purification priority, the concentration of pollutants inside and outside the ventilation opening, the optimal operating parameters of the purification device are calculated by optimization algorithm, and the purification device is controlled to work according to the optimal operating parameters;

[0052] Step E: based on the pressure difference on both sides of the filter screen, the cumulative running time, the purification efficiency, the pollution grade and the remaining amount of self-cleaning medium, the self-cleaning demand is judged, and the self-cleaning execution unit 105 is controlled to perform the corresponding cleaning action.

[0053] Further, the weighting fusion algorithm in step A comprises: calculating a gas pollution sub-index, a particulate matter pollution sub-index, a temperature and humidity deviation index and a flow rate deviation index respectively; and fusing each sub-index using a preset weight to obtain the comprehensive pollution index; the preset weight is determined by training a plurality of sets of historical environmental data.

[0054] Further, the fluid simulation process in step B comprises: establishing a three-dimensional model of the door body 102 and the door frame 101; using the ventilation flow rate and the pollutant concentration corresponding to the pollution level as boundary conditions; and solving a fluid dynamics equation to obtain a flow field and a pollutant concentration distribution under different door body 102 opening angles, and calculating the protection effect coefficient and the ventilation efficiency coefficient based on the flow field and the pollutant concentration distribution.

[0055] Further, the control unit 104 is further configured to periodically perform steps A and B, dynamically adjust the boundary conditions according to the updated pollution level, and recalculate the protection effect coefficient and the ventilation efficiency coefficient to achieve adaptive adjustment of the door body 102 opening angle.

[0056] Further, the process of calculating the optimal opening angle in step C comprises:

[0057] a multi-objective optimization function is constructed with the protection effect coefficient, the ventilation efficiency coefficient and an energy consumption coefficient calculated based on the driving current as targets; a preliminary optimal angle is found by traversing the door body 102 opening angle, which is the angle that maximizes the value of the optimization function; and the preliminary optimal angle is corrected according to the protection level to obtain the final optimal opening angle.

[0058] Further, the optimization algorithm in step D is a particle swarm optimization algorithm, and the control unit 104 is configured to dynamically adjust the inertia weight of the particle swarm optimization algorithm according to the purification priority, wherein the higher the purification priority, the smaller the inertia weight, so as to speed up the convergence speed.

[0059] Further, the process of determining the self-cleaning demand in step E comprises:

[0060] a cleaning demand correction coefficient is determined according to the pollution level; a filter screen pollution index is calculated based on the pressure difference between the two sides of the filter screen, the cumulative running time and the purification efficiency; the self-cleaning demand degree is obtained by multiplying the filter screen pollution index and the cleaning demand correction coefficient; and when the self-cleaning demand degree exceeds a threshold value, a self-cleaning mode is selected according to the amount of self-cleaning medium.

[0061] Further, the control unit 104 is further configured to form a self-cleaning closed-loop control: after the self-cleaning execution unit 105 completes the cleaning action, the cleaning effect is verified; if the drop of the pressure difference on both sides of the filter screen after cleaning does not reach the first preset proportion, or the recovery of the purification efficiency does not reach the second preset proportion, the self-cleaning execution unit 105 is controlled to upgrade the cleaning mode or prolong the cleaning time before performing the cleaning action again.

[0062] Further, the control unit 104 is configured to form a door body 102 adjustment closed-loop control: after controlling the driving unit 103 to act, the real-time opening and closing angle of the door body 102 and the working current of the driving unit 103 fed back by the sensing system 106 are received; if the deviation of the real-time opening and closing angle of the door body 102 from the target angle exceeds the angle tolerance, the output of the driving unit 103 is adjusted to correct the deviation; if the working current of the driving unit 103 exceeds the safe current threshold, the driving is immediately stopped and an alarm signal is triggered.

[0063] Further, the fluid simulation model in step B is calibrated by experimental data, and the calibration process includes: comparing the simulation data and the measured data under different opening and closing angles of the door body 102 and ventilation flow rates, and adjusting the fluid physical property parameters in the simulation model until the error between the simulation data and the measured data is less than a preset error threshold.

[0064] In step A, in the weighted fusion algorithm, the training method of the preset weight is multivariate linear regression or neural network algorithm, which is obtained based on supervised learning of historical environmental data and expert-labeled pollution level labels.

[0065] In step B, the fluid simulation is simulated by using CFD software (such as ANSYS Fluent or OpenFOAM), and the mapping relationship between the pollutant concentration and the pollution level in the boundary condition is determined by the table lookup method, for example:

[0066] Pollution level PM2.5 concentration (pg / m3) CO concentration (ppm) 1 ≤35 ≤10 2 35~75 10~20 3 75~150 20~50 4 >150 >50

[0067] In order to better enable the relevant personnel in the technical field to fully understand and implement the present application, the specific implementation principles of the present application are further supplemented by combining with a specific application scenario.

[0068] The embodiment discloses a high-efficiency purification and self-cleaning civil air defense building ventilation opening protective door equipment, which comprises a door frame 101, a door body 102, a purification device 107, a self-cleaning execution unit 105, a sensing system 106 and a driving unit 103. The door frame 101 is a basic frame of an integral structure, the door body 102 is installed at the upper and lower ends of the inner side of the door frame 101 through a rotating shaft, the rotating shaft is connected with the driving unit 103 through a transmission mechanism, the transmission mechanism is composed of a worm and a worm wheel, wherein the worm is fixedly connected with the output shaft of a speed reducer in a coaxial mode, and the worm wheel is fixedly connected with the rotating shaft of the door body 102. The driving unit 103 comprises a motor and a speed reducer, the motor is connected with the input shaft of the speed reducer through a shaft coupling, and the output shaft of the speed reducer is connected with the transmission mechanism through a gear pair, so that the opening and closing action of the door body 102 is realized.

[0069] The purification device 107 is arranged on the ventilation path and located in the ventilation channel between the door frame 101 and the door body 102, close to the inner side of the ventilation opening. The purification device 107 adopts a multi-layer filter screen structure and comprises a primary filter screen, a high-efficiency filter screen and an activated carbon filter screen, and each layer of filter screen is fixed in the frame of the purification device 107 through a buckle structure. The primary filter screen is used for intercepting large particles, the high-efficiency filter screen is used for filtering fine particles, and the activated carbon filter screen is used for adsorbing toxic gases. The design of the buckle structure makes the filter screen convenient to disassemble and replace, thereby reducing the maintenance cost. Differential pressure sensors are arranged on the two sides of the purification device 107 respectively, for detecting the differential pressure change on the two sides of the filter screen.

[0070] The self-cleaning execution unit 105 comprises a spraying assembly and a recovery assembly, the spraying assembly is connected with a liquid storage tank through a flexible pipeline, and a one-way valve is arranged in the flexible pipeline to prevent the backflow of the cleaning medium. The spraying assembly is installed on one side of the purification device 107 and is used for spraying the cleaning medium to the surface of the filter screen, and the cleaning medium can be water or special cleaning liquid. The recovery assembly is located below the purification device 107 and is used for collecting the waste generated in the cleaning process, and the waste is discharged to an external collecting device through a pipeline.

[0071] The sensing system 106 comprises a plurality of sensor modules, and each sensor module is connected with a control unit 104 through a wireless communication protocol. The shell of the sensor module is made of shielding material to reduce the influence of electromagnetic interference on signal transmission. The sensing system 106 is used for collecting environmental data and equipment state data, wherein the environmental data comprises the concentration of toxic gases, the concentration of particles, the temperature and humidity and the ventilation flow rate on the inner side of the ventilation opening, and the equipment state data comprises the opening angle of the door body 102, the working current of the driving unit 103, the differential pressure on the two sides of the filter screen of the purification device 107, the cumulative running time of the purification device 107 and the remaining amount of the self-cleaning medium. The sensor modules are distributed at key positions of the equipment, for example, the gas sensor and the particle sensor are installed on the inner side of the ventilation opening close to the purification device 107, the temperature and humidity sensor is installed on the outer side of the ventilation opening, and the differential pressure sensors are installed on the two sides of the purification device 107.

[0072] The control unit 104 is configured as a core processing module, and is electrically connected with the sensing system 106, the driving unit 103, the purification device 107 and the self-cleaning execution unit 105 respectively. The control unit 104 performs the following steps based on the collected data:

[0073] Firstly, based on the environmental data collected by the sensing system 106, a comprehensive pollution index is calculated by a weighted fusion algorithm, and a pollution level, a purification priority and a protection level are determined according to the index. The weighted fusion algorithm includes calculating a gas pollution sub-index, a particulate matter pollution sub-index, a temperature and humidity deviation index and a flow rate deviation index respectively, fusing the sub-indices by using a preset weight to obtain the comprehensive pollution index, and determining the preset weight by training a plurality of sets of historical environmental data.

[0074] Secondly, based on the pollution level, the ventilation flow rate and the structural parameters of the door body 102, the protection effect coefficient and the ventilation efficiency coefficient under different opening angles of the door body 102 are calculated by fluid simulation. The fluid simulation model is calibrated by experimental data, and the calibration process includes comparing the simulation data and the measured data under different opening angles of the door body 102 and ventilation flow rates, and adjusting the fluid physical property parameters in the simulation model until the error between the simulation data and the measured data is less than a preset error threshold.

[0075] Thirdly, based on the protection effect coefficient, the ventilation efficiency coefficient, the protection level and the working current of the driving unit 103, the optimal opening angle of the door body 102 is calculated, and the door body 102 is adjusted to the angle by the driving unit 103. A multi-objective optimization function is constructed with the protection effect coefficient, the ventilation efficiency coefficient and an energy consumption coefficient calculated based on the driving current as the target, and the angle that makes the optimization function value maximum is found by traversing the opening angle of the door body 102 as the preliminary optimal angle. The preliminary optimal angle is corrected according to the protection level to obtain the final optimal opening angle.

[0076] The control unit 104 also calculates the optimal operating parameters of the purification device 107 by an optimization algorithm based on the purification priority and the pollutant concentrations on the inside and outside of the ventilation port, and controls the purification device 107 to operate according to the parameters. The optimization algorithm is a particle swarm optimization algorithm, and the control unit 104 dynamically adjusts the inertia weight of the particle swarm optimization algorithm according to the level of the purification priority, wherein the higher the purification priority, the smaller the inertia weight, so as to accelerate the convergence speed.

[0077] In addition, the control unit 104 determines the self-cleaning demand based on the pressure difference across the filter screen, the cumulative running time, the purification efficiency, the pollution level, and the remaining amount of self-cleaning medium, and controls the self-cleaning execution unit 105 to perform the corresponding cleaning action. The cleaning demand correction coefficient is determined according to the pollution level, the filter screen pollution index is calculated based on the pressure difference across the filter screen, the cumulative running time, and the purification efficiency, the self-cleaning demand degree is obtained by multiplying the filter screen pollution index by the cleaning demand correction coefficient, and when the self-cleaning demand degree exceeds the threshold value, the self-cleaning mode is selected according to the remaining amount of self-cleaning medium.

[0078] The control unit 104 forms a self-cleaning closed-loop control, and verifies the cleaning effect after the self-cleaning execution unit 105 completes the cleaning action. If the decrease in the pressure difference across the filter screen after cleaning does not reach the first preset proportion, or the recovery of the purification efficiency does not reach the second preset proportion, the self-cleaning execution unit 105 is controlled to upgrade the cleaning mode or prolong the cleaning time before performing the cleaning action again. The control unit 104 also forms a door body 102 adjustment closed-loop control, and receives the real-time opening and closing angle of the door body 102 and the working current of the driving unit 103 fed back by the sensing system 106 after the driving unit 103 is actuated. If the deviation of the real-time opening and closing angle of the door body 102 from the target angle exceeds the angle tolerance, the output of the driving unit 103 is adjusted to correct the deviation; if the working current of the driving unit 103 exceeds the safe current threshold, the driving is immediately stopped and an alarm signal is triggered.

[0079] A sealing strip is arranged between the door frame 101 and the door body 102, and is made of multiple layers of composite materials. The outer layer is corrosion-resistant rubber, and the inner layer is elastic foam material, so as to improve the sealing performance and reduce vibration noise. The sealing strip is installed on the inner side edge of the door frame 101 and tightly adheres to the outer surface of the door body 102. The motor of the driving unit 103 is installed on the top of the door frame 101, the reducer is connected with the motor through a shaft coupling, the output shaft of the reducer is engaged with the transmission mechanism through a gear pair, and the worm and the worm wheel of the transmission mechanism cooperate to achieve the smooth opening and closing of the door body 102. The sensor modules of the sensing system 106 are distributed at key positions of the equipment, such as the gas sensor and the particulate matter sensor which are installed inside the air vent near the purification device 107, the temperature and humidity sensor which is installed outside the air vent, and the pressure difference sensor which is installed on both sides of the purification device 107.

[0080] The process of the control unit 104 collecting data through the sensing system 106 and calculating the optimal opening and closing angle and the purification parameters. The control unit 104 periodically performs the weighted fusion algorithm and the fluid simulation simulation, dynamically adjusts the boundary conditions of the fluid simulation simulation according to the updated pollution level, and recalculates the protection effect coefficient and the ventilation efficiency coefficient, so as to realize the adaptive adjustment of the opening and closing angle of the door body 102.

[0081] The spraying assembly and the recovery assembly of the self-cleaning execution unit 105 work cooperatively, the spraying assembly is connected with the liquid storage tank through a flexible pipeline, and a one-way valve in the flexible pipeline ensures one-way flow of the cleaning medium and avoids backflow. The recovery assembly discharges the waste generated in the cleaning process to an external collection device through a pipeline, ensuring environmental protection and high efficiency of the cleaning process.

[0082] The sealing strip design between the door frame 101 and the door body 102 improves the overall sealing performance of the equipment, reduces the infiltration of external pollutants, and reduces the vibration noise during equipment operation. The multi-layer filter screen structure of the purification device 107 significantly improves the air purification efficiency, and each layer of filter screen is fixed in the frame of the purification device 107 through a buckle structure, facilitating disassembly and replacement, and reducing maintenance costs. The wireless communication protocol design of the sensing system 106 reduces the wiring complexity and improves the installation flexibility and reliability of the equipment. The closed-loop control mechanism of the control unit 104 ensures the accuracy and safety of the equipment during operation, solving the problem of insufficient response speed and processing capacity of traditional equipment under sudden high-concentration pollution conditions.

[0083] Firstly, when the equipment starts, multiple sensor modules in the sensing system 106 begin to collect environmental data and equipment state data. The gas sensor and the particulate matter sensor are installed inside the air vent near the purification device 107, used to monitor the concentration of toxic gases and particulate matter; the temperature and humidity sensor is installed outside the air vent, used to detect the temperature and humidity changes of the external environment; the differential pressure sensor is distributed on both sides of the purification device 107, measuring the pressure difference on both sides of the filter screen in real time. These data are transmitted to the control unit 104 through a wireless communication protocol, ensuring the stability of signal transmission while reducing wiring complexity. The control unit 104 performs a weighted fusion algorithm based on the collected data, calculates the gas pollution sub-index, the particulate matter pollution sub-index, the temperature and humidity deviation index, and the flow rate deviation index, respectively, and fuses each sub-index through a pre-set weight to obtain a comprehensive pollution index. The comprehensive pollution index is used to determine the current pollution level, purification priority, and protection level, thereby providing a basis for subsequent equipment operation.

[0084] Secondly, the control unit 104 calls a fluid simulation model for simulation calculation according to the pollution level, the ventilation flow rate, and the structural parameters of the door body 102. The fluid simulation model takes the ventilation flow rate and the pollutant concentration as the boundary conditions, solves the fluid dynamics equation, and obtains the flow field distribution and the pollutant concentration variation under different opening angles of the door body 102.

[0085] On this basis, the control unit 104 calculates the protection effect coefficient and the ventilation efficiency coefficient corresponding to each opening angle.

[0086] To ensure the accuracy of the simulation results, the fluid simulation model is calibrated with experimental data. The calibration process includes comparing the simulation data with the measured data under different door body 102 opening angles and ventilation flow rates, and adjusting the fluid physical property parameters in the simulation model until the error is less than the preset threshold.

[0087] Subsequently, the control unit 104 constructs a multi-objective optimization function targeting the protection effect coefficient, the ventilation efficiency coefficient and the energy consumption coefficient, finds the angle that maximizes the optimization function value by traversing the door body 102 opening angle as the preliminary optimal angle, and modifies the angle in combination with the protection level to finally determine the optimal opening angle of the door body 102. The drive unit 103 adjusts the door body 102 to the target angle through the reducer and transmission mechanism according to the instructions of the control unit 104, realizing the comprehensive optimization of protection effect and ventilation efficiency.

[0088] Thirdly, the control unit 104 calculates the optimal operating parameters of the purification device 107 based on the purification priority and the pollutant concentration on the inside and outside of the ventilation port using the particle swarm optimization algorithm.

[0089] Under high pollution level conditions, the control unit 104 dynamically reduces the inertia weight of the particle swarm optimization algorithm to speed up the convergence speed and quickly adjust the operating mode of the purification device 107. The multi-layer filter screen structure of the purification device 107 includes a primary filter screen, a high-efficiency filter screen and an activated carbon filter screen, which are fixed in the frame through a buckle structure for easy disassembly and replacement.

[0090] The primary filter screen intercepts large particles, the high-efficiency filter screen filters fine particles, and the activated carbon filter screen adsorbs toxic gases, significantly improving the air purification efficiency. The control unit 104 monitors the pressure difference change on both sides of the filter screen through the differential pressure sensor, and judges the pollution degree of the filter screen in combination with the cumulative running time and the purification efficiency.

[0091] When the self-cleaning demand degree obtained by multiplying the filter screen pollution index and the cleaning demand correction coefficient exceeds the preset threshold, the control unit 104 starts the self-cleaning execution unit 105. The injection assembly extracts cleaning medium from the liquid storage tank through a flexible pipeline and sprays cleaning liquid onto the surface of the filter screen. The one-way valve in the flexible pipeline ensures one-way flow of the cleaning medium, avoiding backflow phenomenon. The recovery assembly is located below the purification device 107 and is used to collect waste generated during the cleaning process and discharge it to the external collection device through the pipeline, ensuring the environmental friendliness and efficiency of the cleaning process. After self-cleaning is completed, the control unit 104 verifies the cleaning effect. If the pressure difference on both sides of the filter screen decreases by less than the first preset proportion or the purification efficiency recovers by less than the second preset proportion, the control unit 104 upgrades the cleaning method or prolongs the cleaning time before executing the cleaning action again, forming a closed-loop control.

[0092] In addition, the control unit 104 also forms a closed-loop control mechanism for the door body 102 adjustment. After the driving unit 103 is in action, the control unit 104 receives the real-time opening and closing angle of the door body 102 and the working current of the driving unit 103 fed back by the sensing system 106. If the deviation of the real-time opening and closing angle of the door body 102 from the target angle exceeds the angle tolerance, the control unit 104 adjusts the output of the driving unit 103 to correct the deviation; if the working current of the driving unit 103 exceeds the safe current threshold, the driving is immediately stopped and an alarm signal is triggered to ensure the safety of the equipment operation.

[0093] The seal strip design between the door frame 101 and the door body 102 further improves the overall sealing performance of the equipment. The seal strip is made of multiple layers of composite materials, with the outer layer being corrosion-resistant rubber and the inner layer being elastic foam material, which not only reduces the penetration of external pollutants, but also reduces the vibration noise during equipment operation. The motor of the driving unit 103 is connected with the reducer through a shaft coupling, the output shaft of the reducer is engaged with the transmission mechanism through a gear pair, and the worm of the transmission mechanism cooperates with the worm gear to realize the smooth opening and closing of the door body 102, ensuring the reliability of the equipment operation.

[0094] The present application realizes the efficient purification and self-cleaning function of the air defense building ventilation port protective door equipment through comprehensive data collection of the sensing system 106, accurate calculation of fluid simulation, dynamic adjustment of particle swarm optimization algorithm and effective verification of self-cleaning closed-loop control. The coordinated work of various components solves the technical problems of limited environmental data collection range, inflexible filter cleaning mechanism, lack of comprehensive optimization of door body 102 opening and closing angle adjustment and insufficient response ability to sudden high concentration pollution in the prior art, and significantly improves the adaptability and protection effect of the equipment.

[0095] The present application constructs an integrated intelligent regulation and control system of full-dimensional data collection, intelligent algorithm optimization, function closed-loop control and structure cooperative adaptation, and forms a multi-dimensional breakthrough for the problems of one-sided environmental data collection, difficulty in balancing protection and ventilation efficiency, rigid purification parameter regulation, no guarantee for self-cleaning effect, high maintenance cost and insufficient safety of traditional air defense building ventilation port protective door equipment (door frame 101, door body 102). Break through the limitation of traditional single index monitoring, realize the full coverage of environmental and equipment data through the sensing system 106, the environmental data includes the concentration of toxic gas, the concentration of particulate matter, the temperature and humidity and the ventilation flow rate inside the ventilation port, the equipment state data includes the opening and closing angle of the door body 102, the working current of the driving unit 103, the pressure difference between the two sides of the filter screen of the purification device 107, the cumulative running time and the self-cleaning medium remaining amount of the self-cleaning execution unit 105, and then combined with the weighted fusion algorithm trained by multiple groups of historical environmental data, the comprehensive pollution index is accurately calculated, and the pollution grade, purification priority and protection grade are scientifically divided according to the accurate data support for subsequent regulation and control.

[0096] The application adopts an experimentally calibrated fluid simulation model, adjusts fluid physical property parameters to an error less than a preset threshold by comparing simulation and actual measurement data under different door body 102 opening angles and ventilation flow rates, calculates protection effect coefficients and ventilation efficiency coefficients corresponding to different door body 102 opening angles, simultaneously constructs a multi-objective optimization function fusing the protection effect coefficients, the ventilation efficiency coefficients and the energy consumption coefficients based on the current of the driving unit 103, first traverses the angles to determine a preliminary optimal angle, and then corrects the final optimal opening angle according to the protection level, and periodically performs data acquisition and simulation calculation of the sensing system 106, dynamically adjusts the boundary conditions to realize adaptive optimization of the door body 102 angle, and effectively balances safety protection and ventilation efficiency.

[0097] The application adopts a particle swarm optimization algorithm to dynamically adjust the inertia weight according to the purification priority, the inertia weight is smaller as the priority is higher, the convergence speed is accelerated, the optimal operation parameters of the purification device 107 are quickly solved in combination with the pollutant concentrations inside and outside the ventilation opening, and the response and processing capacity in a sudden high-concentration pollution scene are improved.

[0098] The self-cleaning execution unit 105 of the application determines the self-cleaning demand and the closed-loop control mechanism, determines the cleaning demand correction coefficient based on the pollution level, calculates the filter screen pollution index in combination with the pressure difference of the filter screen of the purification device 107, the cumulative running time and the purification efficiency, multiplies the two to obtain the self-cleaning demand degree, selects the cleaning method according to the self-cleaning medium reserve of the self-cleaning execution unit 105 when the threshold is exceeded, and verifies the pressure difference drop ratio and the purification efficiency recovery ratio of the filter screen of the purification device 107 after cleaning, and upgrades the cleaning method or prolongs the time when the preset standard is not reached, solving the poor cleaning effect of the traditional fixed time / single trigger.

[0099] The application constructs the closed-loop control of the door body 102, compares the actual opening angle of the door body 102 with the target angle in real time through the control unit 104, adjusts the output correction of the driving unit 103 when the deviation exceeds the tolerance, simultaneously monitors the current of the driving unit 103 through the sensing system 106, and immediately stops the driving of the driving unit 103 and alarms when the safety threshold is exceeded, and considers the regulation and control accuracy and equipment safety.

[0100] Embodiment 2:

[0101] The embodiment is basically the same as embodiment 1, and the difference is that in the embodiment, the control unit is configured to:

[0102] Step A: based on the environmental data, calculating a comprehensive pollution index by a weighted fusion algorithm, and determining a pollution level, a purification priority and a protection level according to the comprehensive pollution index;

[0103] Step B: driving a fluid simulation model calibrated by experimental data with the pollution concentration corresponding to the pollution level and the ventilation flow rate as dynamic boundary conditions to calculate the protection effect coefficient and ventilation efficiency coefficient under different door opening angles;

[0104] Step C: constructing a multi-objective optimization function with the protection effect coefficient, ventilation efficiency coefficient and energy consumption coefficient as targets to obtain a preliminary optimal opening angle; then, according to the protection level, the preliminary result is forcibly corrected to obtain the final optimal opening angle of the door, and the driving unit is controlled to drive the door to the optimal opening angle;

[0105] The multi-objective optimization function is as follows:

[0106] ;

[0107] wherein, represents the comprehensive performance evaluation value when the door opening angle is , is the protection effect coefficient, is the ventilation efficiency coefficient, is the energy consumption coefficient, , , is a weight coefficient, the value range is [0.1], and is determined by the analytic hierarchy process (AHP) combined with expert scoring.

[0108] Step D: based on the purification priority, the pollutant concentrations inside and outside the ventilation port, the optimal operating parameters of the purification device are calculated by a particle swarm optimization algorithm with a dynamically adjusted inertia weight, and the purification device is controlled to work according to the optimal operating parameters; wherein the higher the purification priority, the smaller the inertia weight value, and the faster the algorithm converges;

[0109] Step E: determining a cleaning demand correction coefficient according to the pollution level; calculating a filter screen pollution index based on the pressure difference between the two sides of the filter screen, the cumulative running time and the purification efficiency; multiplying the two to obtain the self-cleaning demand degree; when the self-cleaning demand degree exceeds the threshold value, the self-cleaning mode is selected according to the self-cleaning medium remaining amount.

[0110] The threshold value is a dynamic threshold value, which is jointly calibrated according to historical self-cleaning effect data and pollution levels, as follows: when the pollution level is 1, 2 or 3, the self-cleaning demand degree threshold value is set to 80, 70 or 60.

[0111] Further, the control unit is further configured to form a self-cleaning closed-loop control: after the self-cleaning execution unit completes the cleaning action, the cleaning effect is verified; the verification index includes whether the pressure difference on both sides of the filter screen after cleaning decreases by a first preset proportion and whether the purification efficiency recovers by a second preset proportion; if the standard is not met, the self-cleaning execution unit is controlled to upgrade the cleaning mode or prolong the cleaning time before performing the cleaning action again until the verification index meets the standard.

[0112] Further, the control unit is configured to form a door body adjustment closed-loop control: the control includes a double-loop structure: a precision control loop for adjusting the output of the driving unit to correct the deviation according to the deviation between the real-time opening angle and the target angle of the door body; a safety monitoring loop for stopping driving and triggering an alarm signal when the working current of the driving unit exceeds the safety current threshold.

[0113] In specific implementation:

[0114] The control unit 104 performs the following steps based on the collected data:

[0115] Firstly, based on the environmental data collected by the sensing system 106, the comprehensive pollution index is calculated by a weighted fusion algorithm, and the pollution level, purification priority and protection level are determined according to the index. The weighted fusion algorithm includes calculating the gas pollution sub-index, the particulate matter pollution sub-index, the temperature and humidity deviation index and the flow rate deviation index respectively, using the preset weight to fuse each sub-index to obtain the comprehensive pollution index, and the preset weight is determined by training a plurality of sets of historical environmental data.

[0116] Secondly, taking the real-time collected ventilation flow rate and the pollutant concentration corresponding to the pollution level as the dynamically changing boundary conditions, the fluid simulation model pre-stored in the control unit and calibrated by experimental data is driven to calculate the protection effect coefficient and the ventilation efficiency coefficient under different opening angles of the door body 102. During calibration, the simulation data and the measured data under different door body opening angles and ventilation flow rates are compared, and the fluid physical property parameters in the simulation model are adjusted until the error is less than a preset threshold.

[0117] Thirdly, a multi-objective optimization function with the protection effect coefficient, the ventilation efficiency coefficient and an energy consumption coefficient calculated based on the driving current as the target is constructed. The function is solved by traversing the opening angle of the door body to obtain a preliminary optimal angle that maximizes the function value. Thereafter, the independently determined protection level is introduced as a rigid constraint condition to forcibly correct the preliminary optimal angle to obtain a final optimal opening and closing angle that is safe and efficient, and the door body 102 is adjusted to the angle by the driving unit 103.

[0118] The control unit 104 also calculates the optimal operating parameters of the purification device 107 based on the purification priority, the pollutant concentration on the inside and outside of the air vent, and a particle swarm optimization (PSO) algorithm. The innovation lies in that the business logic index of the purification priority is dynamically mapped to the inertia weight parameter of the PSO algorithm: the higher the purification priority, the smaller the inertia weight value, so as to forcibly accelerate the convergence speed of the algorithm, thereby quickly responding to high-risk pollution conditions and controlling the purification device 107 to operate according to the optimal parameters.

[0119] In addition, the control unit 104 innovatively couples the external environment and the internal state to determine the self-cleaning demand: a cleaning demand correction coefficient is determined according to the pollution level; a filter screen pollution index is calculated based on the pressure difference between the two sides of the filter screen, the cumulative operating time, and the purification efficiency; and the self-cleaning demand degree is obtained by multiplying the two. When the self-cleaning demand degree exceeds the threshold, the self-cleaning mode is selected according to the amount of self-cleaning medium.

[0120] The control unit 104 further constitutes a self-cleaning closed-loop control with verifiable effect and upgradable strategy: after the self-cleaning execution unit 105 completes the cleaning action, the system does not assume that the cleaning is effective by default, but verifies two quantifiable performance indicators: whether the pressure difference between the two sides of the filter screen decreases by a first preset proportion, and whether the recovery of the purification efficiency reaches a second preset proportion. If either indicator fails to pass the verification, the self-cleaning execution unit 105 is controlled to upgrade the cleaning method (such as increasing the injection pressure) or extend the cleaning time before performing the cleaning action again, and the verification is performed again until the effect meets the standard.

[0121] The control unit 104 also constitutes a double-loop door body control architecture that integrates precision and safety monitoring: after the driving unit 103 operates, the precision control loop continuously receives the real-time opening angle of the door body 102 fed back by the sensing system 106, and compares it with the target angle. If the deviation exceeds the angle tolerance, the output of the driving unit 103 is adjusted to correct the deviation. The safety monitoring loop continuously monitors the working current of the driving unit 103, and if the current exceeds the safety current threshold, the driving is immediately stopped and an alarm signal is triggered. The double loops run in parallel to ensure that the door body adjustment process is both accurate and safe.

[0122] The present application solves the problem of limited environmental data collection range of traditional equipment by comprehensively collecting environmental data through the sensing system 106 and calculating a comprehensive pollution index by combining a weighted fusion algorithm. By introducing an experimentally calibrated fluid simulation model and driving the calculation of the protection effect coefficient and the ventilation efficiency coefficient at different door body opening angles with real-time data, the scientific, quantitative and dynamic optimization of the door body opening angle is realized.

[0123] Meanwhile, a self-cleaning demand degree model based on pollution level correction and a closed-loop control mechanism for cleaning effect verification and upgrade execution are introduced, solving the problem of rigid cleaning trigger logic and no guarantee of cleaning effect of traditional equipment. By dynamically mapping the purification priority to the optimization algorithm parameters, the response speed and processing capacity of the equipment under the condition of sudden high concentration pollution are improved. The door body adjustment of the application adopts a double-loop closed-loop control mechanism of precision and safety, which can monitor the door body opening angle and driving unit working current in real time, ensure the door body to be adjusted to the target angle accurately, and avoid safety hazards caused by overload.

[0124] Embodiment 3:

[0125] This embodiment is further optimized on the basis of embodiment 1 or embodiment 2. In this embodiment, the control unit accesses a digital twin cloud platform;

[0126] The digital twin cloud platform is constructed with an ultra-high precision virtual model of the protective door equipment, which is continuously trained and calibrated by real-time and historical data uploaded by the sensing system;

[0127] The control unit is further configured to:

[0128] Step F: synchronizing the real-time data collected by the sensing system to the digital twin cloud platform;

[0129] Step G: receiving the instructions issued by the digital twin cloud platform, including the Remaining Useful Life (RUL) of the filter screen calculated based on the virtual model;

[0130] Based on historical data and real-time flow field simulation, the boundary conditions and physical parameters of the optimized fluid simulation model are optimized;

[0131] Based on multi-scenario pre-rehearsal, a device maintenance strategy library is generated.

[0132] Among them, the device maintenance strategy library in step G includes the optimal start-stop timing of the cleaning device for different pollutants, the drive unit torque compensation parameters for different degrees of wear, and the optimal trigger timing of the self-cleaning execution unit based on the predictive RUL.

[0133] In this embodiment, the control unit 104 establishes a low-latency and high-bandwidth connection with the digital twin cloud platform through a 5G module.

[0134] The digital twin cloud platform uses ANSYS Twin Builder or equivalent tools to build a multi-physical field ultra-high precision virtual model including door body dynamics, fluid dynamics, and filter screen pollutant adsorption dynamics. The initial parameters of the virtual model come from the equipment design drawings, and are continuously calibrated by receiving the full amount of data uploaded by the sensing system 106 (1 time per second) during operation, ensuring that the synchronization error rate with the physical entity is less than 3%.

[0135] In specific implementation, in addition to performing original steps A-E, the control unit 104 also performs:

[0136] Step F: After packaging and encrypting the real-time collected environmental and equipment state data, it is synchronized to the digital twin cloud platform.

[0137] Step G: Receive and execute the optimization instructions issued by the cloud platform.

[0138] For example: Based on the filter screen pressure difference growth rate, pollutant adsorption model, and historical cleaning effect data, the cloud platform predicts that the current filter screen RUL is only 48 hours. The control unit 104 accordingly schedules the self-cleaning execution unit 105 in advance, and sends a filter screen replacement warning to the maintenance personnel 12 hours before the RUL is exhausted, avoiding sudden failure.

[0139] The cloud platform uses its powerful computing power to mine massive historical data and finds that when the particulate matter concentration suddenly rises, starting the efficient filter screen to maximum power for 10 seconds first, and then starting the activated carbon filter screen, can reduce energy consumption by 15% compared to simultaneous starting. The optimized start-stop sequence is issued to the control unit 104 and updates the execution logic of step D.

[0140] The cloud platform simulates and finds that the worm gear mechanism of the driving unit 103 will cause a 5% transmission efficiency drop after 100,000 runs due to wear and tear. Therefore, it issues a set of torque compensation parameters, and the control unit 104 automatically increases the driving current upper limit by 5% when it detects that the driving frequency is close to the threshold, thereby compensating for the torque loss caused by wear and tear, ensuring that the door body angle control accuracy is always consistent.

[0141] After introducing the digital twin, the system changes from post-response to pre-prediction. Laboratory comparison data shows that the filter screen replacement warning accuracy rate has increased to 95%, avoiding purification failure accidents caused by filter screen breakdown. Through continuous cloud optimization of the operation strategy, the overall equipment energy consumption is reduced by 10-15%. Preventive maintenance of key mechanical components is achieved, and the average time between failures is expected to increase by 20%.

[0142] Further, in some preferred embodiments, the sensing system 106 further comprises a MEMS ultrasonic array sensor, the transmitting end and the receiving end of which are arranged non-contactly on both sides of the filter screen of the purification device 107.

[0143] The control unit (104) is further configured to:

[0144] Step H: control the MEMS ultrasonic array sensor to transmit ultrasonic waves of a specific frequency to the filter screen and receive the penetrating signals;

[0145] Step I: analyze the sound velocity attenuation, frequency spectrum change and phase shift of the penetrating ultrasonic waves, and input them into a trained deep learning model to directly output the pollutant load on the filter screen and the pollutant component identification result, such as oily particulate matter, aqueous particulate matter, fibers, etc.

[0146] In the step E of judging the self-cleaning demand, the calculation of the filter screen pollution index will be based on the pollutant load and the pollutant component identification result. The deep learning model in step I is a convolutional neural network (CNN), and the training data of the convolutional neural network comes from the corresponding relationship data set between the ultrasonic penetration signals under different pollution levels and different pollutant components and the true values obtained by standard weighing method and chemical analysis method.

[0147] In actual use, a MEMS ultrasonic array sensor is added near the primary filter screen and the high-efficiency filter screen of the purification device 107, and the model can be selected as CH101 of TDK.

[0148] In specific implementation, the control unit 104 periodically (e.g., every 30 minutes) performs steps H and I:

[0149] Ultrasonic wave pulses with a frequency of 1 MHz are transmitted through the filter screen.

[0150] The signal obtained by the receiving end is compared with the signal of the transmitting end, for example:

[0151] The sound velocity attenuation is calculated to be 15%, and the center frequency shift is 5 kHz. These characteristic values are input into a trained CNN model, and the model file is stored in the Flash of the control unit 104. The model quickly outputs that the pollutant load on the current filter screen is 250 g / m², and the proportion of oily particulate matter is more than 70%.

[0152] Based on this component identification result, the control unit 104 makes an intelligent decision in step E: since the pollutants are mainly oily, if only the conventional water cleaning method is used, the effect will be greatly reduced. Therefore, it controls the self-cleaning execution unit 105:

[0153] First, spray a special emulsified cleaning agent and react with the oil stain for 60 seconds.

[0154] Then, the high-pressure water mist is used for flushing.

[0155] After cleaning, the ultrasonic sensor is used again to verify that the sound velocity attenuation rate has returned to within ±2% of the clean state.

[0156] Compared with the traditional differential pressure sensor, the measurement accuracy is higher, the qualitative identification of the pollutant composition is realized, the scientific basis for the selection of the self-cleaning mode is provided, and the waste or incomplete cleaning caused by the misuse of the cleaning medium is avoided. At the same time, the non-contact measurement completely solves the industry pain point that the sensor itself is polluted and fails.

[0157] Although the preferred embodiments of the present application have been described, those skilled in the art who, once aware of the basic inventive concept, can make further changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0158] The above is only a preferred embodiment of the present application, and is not intended to limit the present application. It should be noted that any modifications, equivalent replacements and improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A high-efficiency purification and self-cleaning civil air defense building ventilation port protective door device, comprising a purification device, a self-cleaning execution unit, a door frame, a door body embedded in the door frame, and a driving unit in transmission connection with the door body, the purification device being arranged on a ventilation path for filtering and purifying air; the self-cleaning execution unit is used for executing cleaning action on the purification device; characterized in that It also includes a control unit and a sensing system, the control unit is electrically connected with the sensing system, the driving unit, the purification device and the self-cleaning execution unit respectively; The sensing system is used for collecting environmental data and equipment state data; the control unit is configured to: Step A: based on the environmental data, the comprehensive pollution index is calculated by a weighted fusion algorithm, and the pollution level, the purification priority and the protection level are determined accordingly; Step B: based on the pollution level, the ventilation flow rate and the door body structure parameters, the protection effect coefficient and the ventilation efficiency coefficient under different door body opening angles are calculated by fluid simulation simulation; Step C: based on the protection effect coefficient, the ventilation efficiency coefficient, the protection level and the driving unit working current, the optimal opening angle of the door body is calculated, and the driving unit is controlled to drive the door body to the optimal opening angle; Step D: based on the purification priority, the pollutant concentration inside and outside the ventilation port, the optimal operating parameters of the purification device are calculated by optimization algorithm, and the purification device is controlled to work according to the optimal operating parameters; Step E: based on the differential pressure of the filter screen on both sides, the cumulative running time, the purification efficiency, the pollution level and the self-cleaning medium reserve, the self-cleaning demand is judged, and the self-cleaning execution unit is controlled to execute the corresponding cleaning action.

2. The high-efficiency particulate and self-cleaning air defense construction portal door apparatus of claim 1, wherein, The weighted fusion algorithm in step A includes: Respectively calculate the gas pollution sub-index, the particulate matter pollution sub-index, the temperature and humidity deviation index and the flow rate deviation index; the preset weight is used to fuse each sub-index to obtain the comprehensive pollution index; the preset weight is determined by training a plurality of groups of historical environmental data.

3. The high efficiency particulate and self-cleaning air defense construction portal door apparatus of claim 1, wherein, The fluid simulation simulation process in step B includes: Establish a three-dimensional model of the door body and the door frame; the pollutant concentration corresponding to the ventilation flow rate and the pollution level is used as the boundary condition; by solving the fluid dynamics equation, the flow field and the pollutant concentration distribution under different door body opening angles are obtained, and the protection effect coefficient and the ventilation efficiency coefficient are calculated accordingly.

4. The high efficiency particulate and self-cleaning air defense construction portal door apparatus of claim 3, wherein, The control unit is further configured to: Periodically execute step A and step B, dynamically adjust the boundary conditions according to the updated pollution level, and recalculate the protection effect coefficient and the ventilation efficiency coefficient to realize the self-adaptive adjustment of the door body opening angle.

5. The high efficiency particulate and self-cleaning air defense construction portal door apparatus of claim 1, wherein, The process of calculating the optimal opening angle in step C includes: Construct a multi-objective optimization function with the protection effect coefficient, the ventilation efficiency coefficient and an energy consumption coefficient calculated based on the driving current as the target; find the angle that makes the optimization function value maximum as the preliminary optimal angle by traversing the door body opening angle; then correct the preliminary optimal angle according to the protection level to obtain the final optimal opening angle.

6. The high efficiency particulate and self-cleaning air defense construction portal door apparatus of claim 1, wherein, The optimization algorithm in step D is a particle swarm optimization algorithm, and the control unit is configured to: dynamically adjust the inertia weight of the particle swarm optimization algorithm according to the level of the purification priority, wherein the higher the purification priority, the smaller the inertia weight, so as to speed up the convergence speed.

7. The high efficiency particulate and self-cleaning air defense construction portal door apparatus of claim 1, wherein, The process of judging the self-cleaning demand in step E includes: A cleaning demand correction coefficient is determined according to the pollution level; a filter screen pollution index is calculated based on the pressure difference between the two sides of the filter screen, the cumulative running time and the purification efficiency; the self-cleaning demand degree is obtained by multiplying the filter screen pollution index and the cleaning demand correction coefficient; when the self-cleaning demand degree exceeds the threshold value, the self-cleaning mode is selected according to the remaining amount of the self-cleaning medium.

8. A high efficiency particulate and self-cleaning air defense construction portal door apparatus according to any one of claims 1-7, wherein, The control unit is further configured to form a self-cleaning closed-loop control: after the self-cleaning execution unit completes the cleaning action, the cleaning effect is verified; if the decrease of the pressure difference between the two sides of the filter screen after cleaning does not reach the first preset proportion, or the recovery of the purification efficiency does not reach the second preset proportion, the self-cleaning execution unit is controlled to upgrade the cleaning mode or prolong the cleaning time and then execute the cleaning action again.

9. The high efficiency particulate and self-cleaning air defense construction portal door apparatus of claim 1, wherein, The control unit is configured to form a door body adjustment closed-loop control: after the driving unit is controlled to act, the real-time opening and closing angle of the door body and the working current of the driving unit fed back by the sensing system are received; if the deviation of the real-time opening and closing angle of the door body from the target angle exceeds the angle tolerance, the output of the driving unit is adjusted to correct the deviation; if the working current of the driving unit exceeds the safe current threshold value, the driving is immediately stopped and an alarm signal is triggered.

10. The high efficiency particulate and self-cleaning air defense construction portal door apparatus of claim 1, wherein, The fluid simulation model in step B is calibrated by experimental data, and the calibration process includes: comparing the simulation data and the measured data under different door body opening and closing angles and ventilation flow rates, and adjusting the fluid physical property parameters in the simulation model until the error between the simulation data and the measured data is less than the preset error threshold.

Images