Total heat exchange fresh air constant-temperature debugging air system

Abstract

The invention relates to the technical field of fresh air systems, and discloses a total heat exchange fresh air constant-temperature debugging air system. Comprising a composite heat exchange module, a multi-mode sensing network, a fuzzy neural network controller, a variable cross-section air duct system, an intelligent filter screen management system, an integrated pressure difference sensing-machine vision detection device and an energy collaborative optimization module, wherein the energy collaborative optimization module is connected with a photovoltaic-heat pump composite energy supply system. According to the total heat exchange fresh air constant-temperature debugging air system, the heat exchange efficiency is remarkably improved by adopting the composite heat exchange module with the gradient pore ceramic matrix and the nano-silver-TiO2 coating, and the gradient pore structure can better adapt to air flowing at different flow speeds and temperatures; and the nano silver-TiO2 coating has excellent photocatalyst degradation performance and is beneficial to air purification, and due to the design, the heat exchange efficiency is improved, the air purification capacity is enhanced, and a healthier and more comfortable indoor environment is provided for users.

Description

Technical Field

[0001] The invention relates to the technical field of fresh air systems, and in particular to a full heat exchange fresh air constant temperature debugging air system. Background Art

[0002] The fresh air system is a device used for indoor air purification and ventilation. It can send fresh outdoor air into the room after filtering, and at the same time discharge the indoor polluted air to the outside, thereby replacing the indoor air and achieving scientific air convection in the enclosed space.

[0003] In modern building environments, the performance of air systems is directly related to indoor air quality, energy consumption and user comfort. Traditional air systems usually have the following problems: traditional heat exchange modules usually use materials with fixed porosity, which are difficult to efficiently adapt to air flows with different flow rates and temperatures, resulting in limited heat exchange efficiency; lack of a comprehensive and accurate sensor network, making it difficult to monitor key parameters such as air temperature, humidity, PM2.5 and CO2 concentration in real time, making it impossible to achieve accurate indoor environmental control. Therefore, a full heat exchange fresh air constant temperature debugging air system is proposed to solve the above problems. Summary of the invention

[0004] The purpose of the present invention is to provide a full heat exchange fresh air constant temperature adjustment air system to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a full heat exchange fresh air constant temperature debugging air system, comprising:

[0006] Composite heat exchange module: This module is composed of a gradient porosity ceramic matrix coated with a nano-silver-TiO2 coating. The ceramic matrix adopts a 3D printed gradient structure, and the porosity is exponentially distributed along the airflow direction;

[0007] Multimodal sensing network: including distributed fiber optic temperature measurement units, laser scattering PM2.5 sensors and CO2 concentration arrays;

[0008] Fuzzy neural network controller: It has an input layer for receiving real-time data of temperature, humidity, PM2.5, and CO2 concentration, a hidden layer, and an output layer for outputting PID parameter setting values ​​and air valve opening instructions, a three-layer nonlinear structure, and a dynamic weight adjustment mechanism;

[0009] Variable cross-section air duct system: equipped with axial guide vanes with an angle adjustment range of 0°-35° and a step accuracy of 0.1°, and equipped with a pressure differential feedback actuator, specifically a pressure differential sensor with a range of 0-500Pa for real-time feedback adjustment;

[0010] Intelligent filter management system: integrated pressure difference sensor-machine vision detection device;

[0011] Energy collaborative optimization module: connects to the photovoltaic-heat pump composite energy supply system.

[0012] Preferably, the gradient porous ceramic matrix of the composite heat exchange module is prepared by a CO2 gas-assisted deposition process, the pore formation rate is controlled at 0.1 μm / min, and the gradient distribution satisfies an exponential function relationship: ρ(x)=ρ0×e^(kx), where ρ0=0.3 mm, k=0.05 mm / m, and x is the airflow direction coordinate.

[0013] Preferably, the thickness of the nano silver-TiO2 coating is 50-100 nm, wherein the particle size of the silver nanoparticles is 20-50 nm, the TiO2 has an anatase structure as the main phase, and the photocatalyst degradation efficiency is ≥90%.

[0014] Preferably, the multimodal sensing network comprises at least 3 groups of distributed optical fiber temperature measurement units, which are arranged at the air outlet, return air outlet and the middle of the heat exchange module of the fresh air system, with a temperature sampling frequency of 1 Hz and a measurement accuracy of ±0.1°C, and integrates a laser scattering PM2.5 sensor and a CO2 concentration array. The detection limit of the laser scattering PM2.5 sensor is 3 μg / m 3 , range 0-500μg / m 3 The range of the CO2 concentration array is 0-5000ppm, with a resolution of ±1ppm.

[0015] Preferably, the hidden layer in the fuzzy neural network controller has two layers, wherein the first hidden layer adopts the LeakyReLU activation function (α=0.01), the second hidden layer adopts the ReLU function, the output layer integrates the PID parameter tuning algorithm, the dynamic weight adjustment factor α(t)=0.6sin(ωt)+0.4(ω=0.05rad / s), and the network training adopts an adaptive learning rate scheduling strategy with an initial value of 0.01 and a decay rate of 0.95 / epoch.

[0016] Preferably, the pressure difference feedback actuator of the variable cross-section air duct system includes a voice coil motor with a thrust of 50N and a ball screw transmission assembly with a lead of 10mm, with a positioning accuracy of ±0.02mm, and the pressure difference sensor is a high-precision silicon piezoresistive sensor with a temperature compensation accuracy of ±0.05Pa / ℃.

[0017] Preferably, the intelligent filter management system integrates a pressure difference sensor-machine vision composite detection device, wherein the pressure difference sensor threshold is 50Pa±5%, and when the cumulative pressure difference exceeds 120% of the design value, the machine vision detection module is triggered. The module uses a linear array CCD camera with a resolution of 2592×1944 to capture the filter image, and predicts the remaining service life through the LSTM network, with an error rate of ≤8%.

[0018] Preferably, the photovoltaic-heat pump composite energy supply subsystem of the energy collaborative optimization module includes: photovoltaic panels using double-sided monocrystalline silicon components, wherein the conversion efficiency is ≥24%, the heat pump circulating working fluid is R410A / R32 mixed refrigerant, COP ≥3.8 under design conditions, the system integrates a peak load shaving algorithm, and predicts the load change trend in the next 30 minutes through discrete Fourier transform, and the peak shaving efficiency is ≥25%.

[0019] Preferably, the system executes the following energy-saving mode when it is running: when it is detected that the indoor PM2.5 concentration is greater than 50 μg / m 3 When the temperature is high, it will automatically switch to enhanced purification mode. At this time, the heat recovery efficiency is allowed to drop to 78%, the fresh air volume is maintained at 80% of the baseline value, and the UVC wavelength is 275nm, and the negative ion concentration is ≥5×10 6 / cm 3 Ultraviolet-negative ion combined disinfection module.

[0020] Compared with the prior art, the beneficial effects achieved by the present invention are:

[0021] First, the full heat exchange fresh air constant temperature adjustment air system of the present invention significantly improves the heat exchange efficiency by adopting a composite heat exchange module with a gradient pore ceramic matrix and a nano silver-TiO2 coating. The gradient pore structure can better adapt to the air flow of different flow rates and temperatures, and the nano silver-TiO2 coating has excellent photocatalyst degradation performance, which helps to purify the air. This design not only improves the heat exchange efficiency, but also enhances the air purification ability, providing users with a healthier and more comfortable indoor environment.

[0022] Second, the present invention realizes comprehensive and accurate monitoring and intelligent control of the indoor environment by integrating a multimodal sensor network, a fuzzy neural network controller, a variable-section air duct system, an intelligent filter management system and an energy collaborative optimization module. The integration of these technologies not only improves the automation level of the system, but also enables the system to automatically adjust parameters such as air volume and temperature according to real-time monitoring data to achieve the best environmental control effect. At the same time, the application of the intelligent filter management system and the energy collaborative optimization module further improves the energy efficiency and sustainability of the system, providing users with a more energy-saving and environmentally friendly user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 This is a flow chart of the composite heat exchange module of the present invention;

[0024] Figure 2 It is a flow chart of the multimodal sensor network of the present invention;

[0025] Figure 3 This is a flow chart of the fuzzy neural network controller of the present invention;

[0026] Figure 4 This is a flow chart of the variable cross-section air duct system of the present invention;

[0027] Figure 5 This is a flow chart of the intelligent filter management system of the present invention;

[0028] Figure 6 This is a flow chart of the energy collaborative optimization module of the present invention. DETAILED DESCRIPTION

[0029] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in 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. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0030] The present invention provides the following technical solutions:

[0031] Example

[0032] See also Figure 1 , Figure 2 , Figure 3 , Figure 4 , Figure 5 and Figure 6 , a full heat exchange fresh air constant temperature debugging air system, comprising:

[0033] Composite heat exchange module: This module is composed of a gradient porosity ceramic matrix coated with a nano-silver-TiO2 coating. The ceramic matrix adopts a 3D printed gradient structure, and the porosity is exponentially distributed along the airflow direction;

[0034] Multimodal sensing network: including distributed fiber optic temperature measurement units, laser scattering PM2.5 sensors and CO2 concentration arrays;

[0035] Fuzzy neural network controller: It has an input layer for receiving real-time data of temperature, humidity, PM2.5, and CO2 concentration, a hidden layer, and an output layer for outputting PID parameter setting values ​​and air valve opening instructions, a three-layer nonlinear structure, and a dynamic weight adjustment mechanism;

[0036] Variable cross-section air duct system: equipped with axial guide vanes with an angle adjustment range of 0°-35° and a step accuracy of 0.1°, and equipped with a pressure differential feedback actuator, specifically a pressure differential sensor with a range of 0-500Pa for real-time feedback adjustment;

[0037] Intelligent filter management system: integrated pressure difference sensor-machine vision detection device;

[0038] Energy collaborative optimization module: connects to the photovoltaic-heat pump composite energy supply system.

[0039] Specifically, the gradient porous ceramic matrix of the composite heat exchange module is prepared by CO2 gas-assisted deposition process, the pore formation rate is controlled at 0.1 μm / min, and the gradient distribution satisfies the exponential function relationship: ρ(x)=ρ0×e^(kx), where ρ0=0.3mm, k=0.05mm / m, and x is the airflow direction coordinate.

[0040] The deposition process requires the use of CO2 gas-assisted arc spraying technology. In a nitrogen protection environment with a pressure of 0.5 MPa, zirconium titanate powder and CO2 gas are mixed in a volume ratio of 1:4, and the pore formation rate is controlled by adjusting the spraying power.

[0041] Specifically, the thickness of the nano silver-TiO2 coating is 50-100 nm, wherein the particle size of the silver nanoparticles is 20-50 nm, the TiO2 has an anatase structure as the main phase, and the photocatalyst degradation efficiency is ≥90%.

[0042] Nanosilver-TiO2 coating was deposited in two steps by magnetron sputtering. Silver layer: sputtering power 1.5kW, vacuum degree 5×10 -4 Pa, deposition rate 0.5nm / s, thickness 20-30nm; TiO2 layer: RF sputtering Ti target, deposition rate 1nm / s, total thickness 70-80nm; under the excitation of ultraviolet light with a wavelength of 365nm, formaldehyde degradation rate ≥90%, methyl orange decolorization rate ≥95%, silver ion concentration ≥1×10 8 / cm 3 The antibacterial rate against Escherichia coli and Staphylococcus aureus is ≥ 99.9%.

[0043] Specifically, the multimodal sensing network includes at least three sets of distributed optical fiber temperature measurement units, which are arranged at the outlet, return air outlet and the middle of the heat exchange module of the fresh air system. The temperature sampling frequency is 1Hz, the measurement accuracy is ±0.1℃, and the laser scattering PM2.5 sensor and CO2 concentration array are integrated. The detection limit of the laser scattering PM2.5 sensor is 3μg / m 3 , range 0-500μg / m 3 The range of the CO2 concentration array is 0-5000ppm, with a resolution of ±1ppm.

[0044] The fiber optic temperature measurement unit needs to be equipped with 3 groups of distributed fiber Bragg grating sensors with a spacing of 50 cm to monitor the air duct temperature field in real time, with a sampling frequency of 1 Hz and an accuracy of ±0.1°C. The PM2.5 sensor adopts the principle of β-ray scattering and is equipped with a self-cleaning purge device (air flow rate 50 mL / min) with a detection limit of 3 μg / m 3 , range 0-500μg / m 3The CO2 array needs to be based on non-dispersive infrared technology, including 4 independent sensors with a range of 0-5000ppm and a cross-sensitivity of ≤0.1%. The comprehensive air quality index is calculated through the Kalman filter algorithm to achieve data fusion.

[0045] Specifically, there are two hidden layers in the fuzzy neural network controller, in which the first hidden layer adopts the LeakyReLU activation function (α=0.01), the second hidden layer adopts the ReLU function, the output layer integrates the PID parameter tuning algorithm, the dynamic weight adjustment factor α(t)=0.6sin(ωt)+0.4(ω=0.05rad / s), and the network training adopts an adaptive learning rate scheduling strategy with an initial value of 0.01 and a decay rate of 0.95 / epoch.

[0046] A time-related factor α(t)=0.6sin(ωt)+0.4(ω=0.05rad / s) is introduced to enhance the adaptability to environmental changes. The Adam optimizer with an initial learning rate of 0.01 and a decay rate of 0.95 / epoch is used, and the loss function is MSE+L1 regularization. The control logic is to update the control parameters every 50ms, and the air valve opening is closed-loop adjusted by the PID algorithm.

[0047] Specifically, the pressure difference feedback actuator of the variable-section air duct system includes a voice coil motor with a thrust of 50N and a ball screw transmission assembly with a lead of 10mm. The positioning accuracy is ±0.02mm. The pressure difference sensor is a high-precision silicon piezoresistive sensor with a temperature compensation accuracy of ±0.05Pa / ℃.

[0048] The voice coil motor with a stroke of ±50mm and a thrust of 50N drives the ball screw to drive the rotation angle of the axial guide vane; the full-bridge circuit and the silicon piezoresistive sensor with a sensitivity of 2mV / Pa monitor the duct pressure difference in real time, which is converted into a digital signal by the AD7606 chip; the control logic is that when the pressure difference exceeds 50Pa, the blade angle is adjusted through the PID controller (Kp=1.2, Ki=0.05, Kd=0.5) to stabilize the pressure difference within the range of ±5Pa.

[0049] Specifically, the intelligent filter management system integrates a pressure differential sensor-machine vision composite detection device, in which the pressure differential sensor threshold is 50Pa±5%. When the cumulative pressure differential exceeds 120% of the design value, the machine vision detection module is triggered. This module uses a linear array CCD camera with a resolution of 2592×1944 to capture the filter image and predicts the remaining service life through the LSTM network, with an error rate of ≤8%.

[0050] The pressure difference sensor is used to monitor the pressure difference on both sides of the filter. When the cumulative pressure drop exceeds 120% of the design value, machine vision detection is triggered. The linear array CCD camera takes the filter image and calculates the transmittance through OpenCV, where the ROI area occupies 60% of the screen. The LSTM network with an input sequence length of 50 frames predicts the remaining life. The pulse backwash device with a pressure of 0.3-0.5MPa and a frequency of 1Hz is automatically executed every 30 minutes, or started in advance according to the life prediction results.

[0051] Specifically, the photovoltaic-heat pump composite energy supply subsystem of the energy collaborative optimization module includes: the photovoltaic panels use double-sided monocrystalline silicon components, where the conversion efficiency is ≥24%, the heat pump circulation fluid is R410A / R32 mixed refrigerant, COP ≥3.8 under the design conditions, the system integrates a peak load shaving algorithm, and predicts the load change trend in the next 30 minutes through discrete Fourier transform, with a peak shaving efficiency ≥25%.

[0052] The double-sided monocrystalline silicon photovoltaic panels with a conversion efficiency of ≥24% are installed at an angle of 30°, and are matched with an MPPT controller with an efficiency of ≥98% to maximize light energy capture; R410A / R32 mixed working fluid circulation, compressor frequency control at 50-150Hz, COP≥3.8 under design conditions; the sampling period is 1 minute, and the historical load data is analyzed based on FFT to predict the peak load in the next 30 minutes. When the predicted value exceeds 80% of the rated power, photovoltaic power supply is used first and the heat pump assistance is started.

[0053] Specifically, the system executes the following energy-saving modes when it is running: When the indoor PM2.5 concentration is detected to be greater than 50μg / m 3 When the temperature is high, it will automatically switch to enhanced purification mode. At this time, the heat recovery efficiency is allowed to drop to 78%, the fresh air volume is maintained at 80% of the baseline value, and the UVC wavelength is 275nm, and the negative ion concentration is ≥5×10 6 / cm 3 Ultraviolet-negative ion combined disinfection module.

[0054] The trigger condition is PM2.5 concentration > 50 μg / m 3 Lasts for 10 minutes; the execution actions are: the fresh air volume is adjusted to 80% of the baseline value; the UVC-negative ion module is started, where the UVC wavelength is 275nm and the intensity is ≥5W / cm 2 , negative ion concentration ≥5×10 6 / cm 3 ; Close the air valve in the area of ​​the heat exchange module with a porosity of less than 0.4mm to reduce wind resistance; start the self-cleaning mode and use UV light + negative ion combined disinfection for 20 minutes.

[0055] When in use, efficient heat recovery is achieved by adopting a composite heat exchange module with a 3D printed gradient structure. At the same time, the nano-silver-TiO2 coating on the surface enhances the air purification effect. The system has a built-in multimodal sensor network to monitor temperature, humidity, PM2.5 and CO2 concentration in real time. After the data is processed by the fuzzy neural network controller, the PID parameters and air valve opening are intelligently adjusted to maintain indoor constant temperature and air quality. The variable-section duct system adjusts the duct section in real time according to the feedback from the pressure difference sensor to optimize the air flow distribution. The intelligent filter management system integrates pressure difference sensing and machine vision technology to accurately predict the filter life. The energy collaborative optimization module integrates high-efficiency photovoltaic and heat pump systems, and combines the peak load shaving algorithm to predict and adjust energy supply. When the indoor PM2.5 exceeds the standard, the system automatically switches to enhanced purification mode, reduces the heat recovery efficiency but maintains the fresh air volume, and starts ultraviolet-negative ion combined disinfection to fully ensure indoor air quality and energy efficiency.

[0056] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and alterations may be made to the embodiments without departing from the principles and spirit thereof, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A full heat exchange fresh air constant temperature debugging air system, characterized by: include: Composite heat exchange module: This module is composed of a gradient porosity ceramic matrix coated with a nano-silver-TiO2 coating. The ceramic matrix adopts a 3D printed gradient structure, and the porosity is exponentially distributed along the airflow direction; Multimodal sensing network: including distributed fiber optic temperature measurement units, laser scattering PM2.5 sensors and CO2 concentration arrays; Fuzzy neural network controller: It has an input layer for receiving real-time data of temperature, humidity, PM2.5, and CO2 concentration, a hidden layer, and an output layer for outputting PID parameter setting values ​​and air valve opening instructions, a three-layer nonlinear structure, and a dynamic weight adjustment mechanism; Variable cross-section air duct system: equipped with axial guide vanes with an angle adjustment range of 0°-35° and a step accuracy of 0.1°, and equipped with a pressure differential feedback actuator, specifically a pressure differential sensor with a range of 0-500Pa for real-time feedback adjustment; Intelligent filter management system: integrated pressure difference sensor-machine vision detection device; Energy collaborative optimization module: connects to the photovoltaic-heat pump composite energy supply system.

2. A full heat exchange fresh air constant temperature debugging air system according to claim 1, characterized in that: The gradient porous ceramic matrix of the composite heat exchange module is prepared by a CO2 gas-assisted deposition process, the pore formation rate is controlled at 0.1 μm / min, and the gradient distribution satisfies an exponential function relationship: ρ(x)=ρ0×e^(kx), where ρ0=0.3 mm, k=0.05 mm / m, and x is the airflow direction coordinate.

3. A full heat exchange fresh air constant temperature debugging air system according to claim 1, characterized in that: The thickness of the nano silver-TiO2 coating is 50-100nm, wherein the particle size of the silver nano particles is 20-50nm, the TiO2 has an anatase structure as the main phase, and the photocatalyst degradation efficiency is ≥90%.

4. A full heat exchange fresh air constant temperature debugging air system according to claim 1, characterized in that: The multimodal sensing network includes at least 3 sets of distributed optical fiber temperature measurement units, which are arranged at the air outlet, return air outlet and the middle of the heat exchange module of the fresh air system. The temperature sampling frequency is 1Hz, the measurement accuracy is ±0.1℃, and the laser scattering PM2.5 sensor and CO2 concentration array are integrated. The detection limit of the laser scattering PM2.5 sensor is 3μg / m 3 , range 0-500μg / m 3 The range of the CO2 concentration array is 0-5000ppm, with a resolution of ±1ppm.

5. A full heat exchange fresh air constant temperature debugging air system according to claim 1, characterized in that: There are two hidden layers in the fuzzy neural network controller, wherein the first hidden layer adopts the LeakyReLU activation function (α=0.01), the second hidden layer adopts the ReLU function, the output layer integrates the PID parameter tuning algorithm, the dynamic weight adjustment factor α(t)=0.6sin(ωt)+0.4(ω=0.05rad / s), and the network training adopts an adaptive learning rate scheduling strategy with an initial value of 0.01 and a decay rate of 0.95 / epoch.

6. A full heat exchange fresh air constant temperature debugging air system according to claim 1, characterized in that: The pressure difference feedback actuator of the variable cross-section air duct system includes a voice coil motor with a thrust of 50N and a ball screw transmission assembly with a lead of 10mm, with a positioning accuracy of ±0.02mm. The pressure difference sensor is a high-precision silicon piezoresistive sensor with a temperature compensation accuracy of ±0.05Pa / ℃.

7. A full heat exchange fresh air constant temperature debugging air system according to claim 1, characterized in that: The intelligent filter management system integrates a pressure difference sensor-machine vision composite detection device, wherein the pressure difference sensor threshold is 50Pa±5%. When the accumulated pressure difference exceeds 120% of the design value, the machine vision detection module is triggered. The module uses a linear array CCD camera with a resolution of 2592×1944 to capture the filter image and predicts the remaining service life through the LSTM network, with an error rate of ≤8%.

8. A full heat exchange fresh air constant temperature debugging air system according to claim 1, characterized in that: The photovoltaic-heat pump composite energy supply subsystem of the energy collaborative optimization module includes: the photovoltaic panels use double-sided monocrystalline silicon components, where the conversion efficiency is ≥24%, the heat pump circulation working fluid is R410A / R32 mixed refrigerant, COP is ≥3.8 under the design conditions, the system integrates a peak load shaving algorithm, and predicts the load change trend in the next 30 minutes through discrete Fourier transform, and the peak shaving efficiency is ≥25%.

9. A full heat exchange fresh air constant temperature debugging air system according to claim 1, characterized in that: The system performs the following energy-saving mode when it is running: When the indoor PM2.5 concentration is detected to be greater than 50 μg / m 3 When the temperature is high, it will automatically switch to enhanced purification mode. At this time, the heat recovery efficiency is allowed to drop to 78%, the fresh air volume is maintained at 80% of the baseline value, and the UVC wavelength is 275nm, and the negative ion concentration is ≥5×10 6 / cm 3 Ultraviolet-negative ion combined disinfection module.

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