Flow detection method and control method of intelligent air valve

Abstract

The invention provides a flow detection method and control method for an intelligent air valve, and the method comprises the step of constructing a flow detection model, and specifically comprises the steps: constructing a correction function based on a Bernoulli equation, the correction function is used for indicating the incidence relation between a pressure coefficient and a valve plate angle, the valve plate angle is the rotation angle of a target intelligent air valve plate, and the correction function is used for indicating the incidence relation between the pressure coefficient and the valve plate angle; the pressure coefficient is a correction coefficient of a pressure difference, and the pressure difference is a difference value between a windward port total pressure and a side port static pressure measured by an average pitot tube in the intelligent air valve; and a flow detection model corresponding to the target intelligent air valve is constructed based on the correction function, the flow detection model is used for indicating the relation among the pressure difference of the target intelligent air valve, the valve plate angle and the flow, and the flow is the flow of air passing through the target intelligent air valve. The built flow detection model can be suitable for intelligent air valves of different models, accurate detection of the flow of the intelligent air valves under different working conditions and different valve plate angles is guaranteed, and good feasibility and universality are achieved.

Description

Technical Field

[0001] The present invention relates to the field of ventilation system control, and in particular to a flow detection method and a control method of an intelligent air valve. Technical Background

[0002] At present, the flow detection of the air valve often needs to be placed in the air duct, and the length of the air duct before and after needs to be greater than 5 times the diameter of the air valve. The traditional air valve is mainly used as an actuator of the host computer without autonomous control function. The air guide structure adopts two cross-crossed pipes, and its structure will greatly affect the accuracy of the pressure difference measurement. The intelligent air valve is equipped with an STM32 controller, has an independent control function, and adopts an average pitot tube structure. It is installed on the air inlet side of the intelligent air valve, which is close to the valve plate and can achieve accurate pressure difference measurement. The intelligent air valve not only reduces the length of the air valve, saves the production cost, but also ensures the accuracy of the flow measurement. The existing flow detection method of the intelligent air valve is mainly aimed at the situation where the air valve is fully opened. The flow value is calculated based on the difference between the total pressure of the windward port and the static pressure of the side port measured by the average pitot tube, that is, the pressure difference. However, when the valve plate angle changes, the relative error between the actual flow and the flow detected by the air valve will increase, and the flow measurement is inaccurate. Inaccurate flow measurement will further reduce the accuracy of ventilation system control, and inaccurate ventilation will lead to a decrease in indoor air quality or cause unnecessary energy waste. Therefore, achieving accurate flow measurement is of great research significance, and an accurate air valve flow detection method is needed to improve the accuracy of flow measurement. Summary of the invention

[0003] The present invention aims to solve the problems existing in the above-mentioned prior art and proposes a flow detection method for an intelligent air valve. A correction function is constructed based on the Bernoulli equation, and then a flow detection model is constructed to realize flow detection at different valve angles. The detection method is suitable for different models of intelligent air valves and has universality.

[0004] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0005] A flow detection method for an intelligent air valve is characterized by comprising the steps of constructing a flow detection model, specifically:

[0006] A correction function is constructed based on the Bernoulli equation, wherein the correction function is used to indicate the correlation between the pressure coefficient and the valve plate angle, wherein the valve plate angle is the rotation angle of the valve plate of the target intelligent air valve, and the pressure coefficient is the correction coefficient of the pressure difference, wherein the pressure difference is the difference between the total pressure at the windward port and the static pressure at the side port measured by the average pitot tube in the intelligent air valve;

[0007] A flow detection model corresponding to the target intelligent air valve is constructed based on the correction function. The flow detection model is used to indicate the relationship between the pressure difference, valve plate angle and flow of the target intelligent air valve. The flow is the air flow through the target intelligent air valve.

[0008] Further, the construction of the correction function includes the following steps:

[0009] Acquire sample data, the sample data including a plurality of air valve disc angles, and pressure difference sample data and flow rate sample data corresponding to the air valve disc angles;

[0010] According to the pressure difference sample data and flow sample data corresponding to the valve plate angles of each air valve, the corresponding pressure sample coefficient is calculated;

[0011] The least square method is used to fit the curve of the pressure sample coefficient changing with the valve angle, and the functional relationship between the pressure sample coefficient and the valve angle is obtained through regression analysis, thereby obtaining the correction function.

[0012] Furthermore, the specific steps of obtaining sample data are:

[0013] Configure the test air volume of the target intelligent air valve;

[0014] Configure several air valve blade angles;

[0015] Based on the test air volume and the air valve disc angle, the pressure difference and flow rate of the target intelligent air valve are monitored to obtain pressure difference sample data and flow rate sample data corresponding to the valve disc angle.

[0016] Furthermore, the calculation formula of the pressure sample coefficient is:

[0017]

[0018] Among them, u1 is the pressure sample coefficient, Q is the flow rate, D p is the pressure difference; D p0 is the zero drift of the differential pressure sensor.

[0019] Further, the correction function is:

[0020]

[0021] Among them, u2 is the pressure coefficient, A, B, F are fitting parameters, and θ is the valve angle.

[0022] Further, the flow detection model is:

[0023]

[0024] Furthermore, after constructing the flow detection model based on the correction function, a model verification step is also included, specifically:

[0025] Based on the angle of the air valve plate, a corresponding flow calculation value is obtained according to the flow detection model;

[0026] Perform error calculation based on the flow sample data and flow calculation value corresponding to the air valve plate angle to obtain error data;

[0027] If the error data exceeds a preset error threshold, the correction function is reconstructed.

[0028] Further, the flow rate of the intelligent air valve is detected based on the air flow calibration platform, and the air flow calibration platform includes a shell;

[0029] An air inlet is provided on one side of the shell, and an air outlet is provided on the other side. The air inlet is connected to a fan to provide input air volume, and a wind speed sensor is installed on the air outlet to measure the flow value of the smart air valve outlet in real time;

[0030] The inner cavity of the shell is a closed chamber, and the inner cavity is connected to the outside through the air inlet and the air outlet;

[0031] A first gas rectifier and a second gas rectifier are sequentially arranged in the inner cavity of the shell from the air inlet to the air outlet, and the first gas rectifier and the second gas rectifier divide the inner cavity into three chambers, which are the first chamber, the second chamber and the third chamber from the air inlet to the air outlet;

[0032] The target intelligent air valve is placed in the second chamber.

[0033] Furthermore, the first gas rectifier is movably connected to the inner wall of the shell through a slide rail, and the first gas rectifier moves along the slide rail in the inner cavity of the shell toward the air outlet or away from the air outlet to adjust the size of the second chamber.

[0034] Furthermore, a control method of an intelligent method includes:

[0035] Get the target air volume;

[0036] Based on the intelligent air valve flow detection model constructed by the above-mentioned intelligent air valve flow detection method, the valve plate angle corresponding to the target air volume is calculated;

[0037] The opening and closing of the corresponding intelligent air valve is controlled based on the valve plate angle.

[0038] The beneficial effects of the present invention are as follows: the intelligent air valve flow detection method realizes accurate measurement of the air valve flow by constructing a new flow detection model. The model adds valve angle compensation through the design of a correction function, thereby ensuring accurate detection of the flow at different valve angles, effectively solving the problem of inaccurate measurement of existing flow detection methods and further improving the measurement accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 This is the structure diagram of the intelligent air valve.

[0040] Figure 2 This is the external structure diagram of the wind flow calibration platform.

[0041] Figure 3 This is the internal structure diagram of the wind flow calibration platform.

[0042] Figure 4 It is a flow chart of the intelligent air valve flow detection method.

[0043] Figure 5 It is a parameter acquisition flow chart.

[0044] Figure 6 It is the fitting curve diagram of pressure coefficient u2. DETAILED DESCRIPTION

[0045] The present invention is further described in detail below in conjunction with the accompanying drawings.

[0046] The present invention discloses a flow detection method for an intelligent air valve, which provides a complete flow detection method applicable to intelligent air valves of different models. The present application exemplarily provides a structural diagram of an intelligent air valve, such as Figure 1 As shown, it includes: a housing 21, the intelligent air valve can be either rectangular or circular, and the corresponding air valve shape is selected according to the shape of the ventilation duct, an STM32 controller 22 is installed above the intelligent air valve, an average pitot tube 23 is installed on the air inlet side, and is connected to the pressure difference sensor through a hose to measure the pressure difference between the total pressure at the windward port and the dynamic pressure at the side port to calculate the flow value, a valve plate 24 and a steering gear 25 are installed in the middle of the air valve, and the steering gear is controlled by PWM to realize the rotation of the valve plate, and the rotation angle range of the valve plate is between 0 and 90 degrees.

[0047] The detection method is based on the wind flow calibration platform, and its external structure is as follows Figure 2 As shown, the air flow calibration platform is mainly composed of an air inlet 1, a shell 2 and three air outlets 3. The airflow enters the closed inner cavity from the air inlet and flows out from the air outlet after passing through the inner cavity.

[0048] The air inlet is connected to a fan, and the fan is set to different speeds to provide different input air volumes to the air inlet. Similar to the working conditions in an actual ventilation system, the input air volume can be changed.

[0049] The internal structure of the wind flow calibration platform is as follows: Figure 3 As shown, the inner cavity of the shell is divided into three chambers from front to back by two gas rectifiers, and from the air inlet to the air outlet, they are the first chamber 4, the second chamber 5 and the third chamber 6, respectively. The two gas rectifiers are the first gas rectifier 7 and the second gas rectifier 8. The airflow becomes regular after passing through the gas rectifier, which is more similar to the airflow of the ventilation duct. The second chamber is provided with a wind valve bracket 9 to place the intelligent wind valve. The two sides of the top of the bracket are flat and can stably place rectangular wind valves of different sizes, and there is a triangular groove in the middle of the top of the bracket, which can stably place circular wind valves of different diameters, and has good versatility. Since the lengths of different types of intelligent wind valves are different, the first gas rectifier is connected to the inner wall of the shell through a slide rail. The first gas rectifier can move along the slide rail in the inner cavity of the shell to the direction close to or away from the air inlet, and the size of the second chamber is manually adjusted to adapt to different types of intelligent wind valves. The first gas rectifier is close to the air inlet of the wind valve, the air outlet of the wind valve is close to the second gas rectifier, and a wind shield 10 is arranged between the second gas rectifier and the air outlet of the wind valve. There is a hole on the wind shield with the same shape and size as the air outlet of the wind valve, which ensures that the airflow can only flow out from the air outlet of the intelligent air valve and reach the third chamber. The third gas rectifier 11 is installed between the third chamber and the air outlet of the wind flow calibration platform. The airflow reaches the air outlet after being rectified by the third gas rectifier and finally flows out.

[0050] There are three air outlets in total. Since different models of smart air valves have different flow ranges, three air outlets with different diameters are set according to the commonly used air valve models and flow measurement accuracy. The air outlet diameter increases proportionally from top to bottom. When the smallest air outlet diameter is set to D, the other two are set to 2D and 3D respectively. Select the appropriate air outlet according to the flow range of the smart air valve, and manually install a circular baffle of the corresponding diameter at the air outlet, and block the other two by physical blocking, which not only ensures smooth and stable air flow, but also ensures the accuracy of the air valve flow detection. A wind speed sensor is installed at each air outlet to measure the air flow rate of the air outlet in real time, which is used as a standard value to compare with the air valve measured flow rate to determine the accuracy of the smart air valve flow detection.

[0051] The air flow calibration platform needs to be used with an electrical control box and Raspberry Pi. The electrical control box contains a frequency converter, a switching power supply, an intermediate controller and a 485 hub. The switching power supply supplies power to the smart air valve and the frequency converter. The frequency converter controls the speed of the fan to provide different input air volumes. The Raspberry Pi connects the air flow calibration platform, the smart air valve and the frequency converter through an RS485 communication cable, and sends instructions to the intermediate controller through the Modbus bus. The intermediate controller outputs a 0-10V voltage signal to control the frequency converter in the electrical control box, thereby changing the frequency of the frequency converter. At the same time, the Raspberry Pi reads the valve angle of the smart air valve, the pressure difference of the pressure difference sensor and the flow data of the wind speed sensor at the air outlet of the air flow calibration platform based on the Modbus protocol.

[0052] The intelligent air valve flow detection method is based on building a flow detection model to achieve accurate flow measurement. The existing flow detection model is mainly for the case where the air valve is fully open. However, when the valve angle of the intelligent air valve gradually increases, the detection error will gradually increase, and the flow measurement is very inaccurate. Therefore, it is necessary to build a more accurate flow detection model. Due to the limitations of materials and design, ventilation ducts generally have a flow rate range. When the input air flow rate is too large, the pressure in the valve and the pipe will rise sharply, which may cause damage to the device. At the same time, high-speed airflow will cause noise problems; when the input air flow rate is too small, it will lead to a decrease in system performance, unable to maintain sufficient ventilation, and cause health problems for users. Therefore, the ventilation system generally has a minimum ventilation volume. The flow rate range of the intelligent air valve is 1-5m / s, and when the air valve blade angle is greater than 70°, the air valve flow in most cases is lower than the minimum flow. At the same time, for the concept of energy saving, the angle of the air valve blade should be reduced as much as possible to avoid excessive energy consumption. Therefore, this flow detection method is only for the case where the air valve blade angle is 0-70°.

[0053] The flow detection method of the intelligent air valve is mainly divided into two steps. The first step is to construct a correction function based on the Bernoulli equation, and the second step is to construct a flow detection model based on the correction function. Based on the constructed flow detection model, the accurate measurement of the air valve flow can be achieved. Figure 4 As shown, the specific flow detection method includes the following steps:

[0054] S100, constructing a correction function based on the Bernoulli equation;

[0055] The average Pitot tube is used in the intelligent air valve to measure the pressure difference and calculate the airflow rate. At the same time, the functional relationship between the flow rate and the airflow rate and the Bernoulli equation is used to obtain the functional relationship between the flow rate and the pressure difference. Since factors such as the shape and surface roughness of the air valve will affect the flow characteristics of the airflow, the flow coefficient is introduced into the flow calculation formula to better adapt to the complex situations in actual engineering. The flow calculation formula is shown in formula (1).

[0056]

[0057] Where Q is the flow rate, s is the cross-sectional area, C is the flow coefficient, and D p is the pressure difference, D p0 is the zero drift of the differential pressure sensor, and ρ is the fluid density.

[0058] Since the fluid density and the cross-sectional area of ​​the air valve are constant under the same environment, but the measurement error of the intelligent air valve flow rate will increase with the increase of the valve angle, it means that the size of the air valve flow rate will be affected by the valve angle. Due to the existence of the air valve, different valve openings will produce different resistance and disturbances to the air flow, which in turn affects the distribution of the wind flow field, resulting in changes in the flow coefficient. The flow coefficient is no longer a fixed value, but has a certain functional relationship with the air valve angle.

[0059] Introduce a pressure sample coefficient u1 related to the valve angle and construct a correction function, which is defined as

[0060]

[0061] According to equations (1) and (2), the calculation formula for the pressure sample coefficient u1 is:

[0062]

[0063] Based on the calculated pressure sample coefficient u1, the functional relationship between it and the valve angle is obtained through regression analysis, and a correction function for the valve angle is constructed as shown in formula (4).

[0064]

[0065] Among them, u2 is the pressure coefficient, A, B, F are fitting parameters, and θ is the valve angle.

[0066] The correction function has parameters A, B, and F, so it is necessary to obtain the values ​​of the parameters to obtain an accurate functional relationship. The specific acquisition process is as follows: Figure 5 As shown, the specific steps include:

[0067] S110, determine the fan frequency range:

[0068] Place the smart air valve on the bracket of the second chamber of the air flow calibration platform to ensure that the inner cavity of the shell is airtight. First, set the test air volume of the target smart air valve. Since different models of smart air valves have different flow ranges, the fan needs to provide different input air volumes. Therefore, it is necessary to determine the frequency range of the fan. Set the maximum and minimum values ​​of the fan frequency to f and f respectively. max and f min .

[0069] S120, equipment initialization:

[0070] Measure the zero drift of the differential pressure sensor, set the air valve angle to 0°, and adjust the fan frequency to the middle frequency f in the set frequency range. middle , wait for the fan to run stably, where the calculation formula of the intermediate frequency is shown in formula (5).

[0071]

[0072] S130, obtaining sample data:

[0073] Raspberry Pi is used as the host computer to obtain sample data through RS485 communication. The sample data includes several air valve disc angles, and pressure difference sample data and flow sample data corresponding to the air valve disc angles. The flow sample data measured by the wind speed sensor at the air outlet and the pressure difference sample data measured by the average Pitot tube are read every 1s. A total of 30 groups are read and the average value is taken. The air valve disc angle is gradually increased by 10° each time. 30 groups of pressure difference sample data and flow sample data are read and the average value is taken until the air valve disc angle is 70°, and the data collection is ended.

[0074] S140, Regression analysis:

[0075] According to the pressure difference sample data and flow sample data corresponding to the valve plate angle of each air valve, the corresponding pressure sample coefficient u1 is calculated based on formula (3). The curve of the pressure sample coefficient changing with the valve plate angle is fitted using the least squares method. The functional relationship between the pressure sample coefficient and the valve plate angle is obtained through regression analysis, and then the correction function u2 is obtained.

[0076] S200, constructing a flow detection model based on the correction function;

[0077] The traffic detection model based on the correction function u2 is:

[0078]

[0079] Furthermore, based on the acquired parameters and the constructed traffic detection model, the model is verified. The specific steps are as follows:

[0080] Based on the angle of the air valve plate, a corresponding flow calculation value is obtained according to the flow detection model;

[0081] Perform error calculation based on the flow sample data and flow calculation value corresponding to the air valve plate angle to obtain error data;

[0082] If the error data exceeds a preset error threshold, the correction function is reconstructed.

[0083] This embodiment calculates the relative error between the air valve detection flow and the actual flow within the flow range of the intelligent air valve for model verification. If the detection error is less than the preset error threshold under different air valve angles and different test air volumes, it means that the parameter settings are correct and the flow detection model is built. If the error is greater than the preset error threshold, the parameter value needs to be readjusted. At this time, the fan frequency needs to be reduced and the fan frequency is set to (f middle -5)Hz, repeat steps S130 and S140 in the parameter acquisition method, obtain the corresponding sample data, perform regression analysis, obtain new parameter values, calculate the average value with the original parameters, set it as the new parameter, and perform model verification again until the detection errors under all conditions are within the preset error threshold.

[0084] Construct a flow detection model for a circular air valve with a diameter of 150 mm. The zero drift of its differential pressure sensor is 0.01 Pa. Collect flow sample data and differential pressure sample data, calculate the pressure sample coefficient u1, and draw a curve that changes with the angle of the air valve, as shown in the figure. Figure 6 As shown, regression analysis is used to obtain the correction function u2, and then the flow detection model is constructed, as shown in formula (7).

[0085]

[0086] Model verification is performed based on the constructed flow detection model, and the relative error between the air valve flow and the actual flow under different input air volumes is calculated. At this time, the detection error is within 10%, and accurate air valve flow detection can be achieved.

[0087] The same experimental scheme was used for a circular air valve with a diameter of 100 mm and a rectangular air valve with a size of 200×120 mm, and the corresponding flow detection model was constructed. The air valve flow obtained based on the new flow detection model was compared with the actual flow process, and the maximum relative errors were 6.1% and 6.6%, respectively. The flow detection model added valve angle compensation through the design of the correction function, solved the problems of the existing flow detection method, and realized the accurate measurement of flow at different valve angles. Moreover, the flow detection model can be applied to different types of intelligent air valves, and has good universality and versatility.

[0088] The control method of a smart air valve described in the present invention is specifically as follows:

[0089] Get the target air volume;

[0090] Based on the flow detection model constructed by the flow detection method of the intelligent air valve, the valve plate angle corresponding to the target air volume is calculated;

[0091] The opening and closing of the corresponding intelligent air valve is controlled based on the valve plate angle.

[0092] Smart air valves need to be calibrated for flow before they are put into actual use. For example, when installed in ventilation ducts or fume hoods, the accuracy of the smart air valve flow detection needs to be measured before use. Only by achieving accurate flow detection can precise flow control be guaranteed. By obtaining corresponding parameter values ​​for different types of smart air valves, the air flow value passing through the smart air valve at this time can be accurately calculated, ensuring accurate measurement of the air volume.

[0093] The above is a detailed introduction to the technical solution of the present invention. Any infringement involving the present invention and related scopes shall be regarded as plagiarism.

Claims

1. A flow detection method for an intelligent air valve, characterized in that: The steps of building a traffic detection model are as follows: A correction function is constructed based on the Bernoulli equation, wherein the correction function is used to indicate the correlation between the pressure coefficient and the valve plate angle, wherein the valve plate angle is the rotation angle of the valve plate of the target intelligent air valve, and the pressure coefficient is the correction coefficient of the pressure difference, wherein the pressure difference is the difference between the total pressure at the windward port and the static pressure at the side port measured by the average pitot tube in the intelligent air valve; A flow detection model corresponding to the target intelligent air valve is constructed based on the correction function. The flow detection model is used to indicate the relationship between the pressure difference, valve plate angle and flow of the target intelligent air valve. The flow is the air flow through the target intelligent air valve.

2. A flow detection method for an intelligent air valve according to claim 1, characterized in that: The construction of the correction function comprises the following steps: Acquire sample data, the sample data including a plurality of air valve disc angles, and pressure difference sample data and flow rate sample data corresponding to the air valve disc angles; According to the pressure difference sample data and flow sample data corresponding to the valve plate angles of each air valve, the corresponding pressure sample coefficient is calculated; The least square method is used to fit the curve of the pressure sample coefficient changing with the valve angle, and the functional relationship between the pressure sample coefficient and the valve angle is obtained through regression analysis, thereby obtaining the correction function.

3. A flow detection method for an intelligent air valve according to claim 2, characterized in that: The specific steps to obtain sample data are: Configure the test air volume of the target intelligent air valve; Configure several air valve blade angles; Based on the test air volume and the air valve disc angle, the pressure difference and flow rate of the target intelligent air valve are monitored to obtain pressure difference sample data and flow rate sample data corresponding to the valve disc angle.

4. A flow detection method for an intelligent air valve according to claim 3, characterized in that: The calculation formula of the pressure sample coefficient is: Among them, u1 is the pressure sample coefficient, Q is the flow rate, D p is the pressure difference; D p0 is the zero drift of the differential pressure sensor.

5. A flow detection method for an intelligent air valve according to any one of claims 1 to 4, characterized in that: The correction function is: Among them, u2 is the pressure coefficient, A, B, F are fitting parameters, and θ is the valve angle.

6. A flow detection method for an intelligent air valve according to claim 5, characterized in that: The flow detection model is:

7. The flow detection method of an intelligent air valve according to claim 2, characterized in that: After the flow detection model is constructed based on the correction function, a model verification step is also included, which is specifically: Based on the angle of the air valve plate, a corresponding flow calculation value is obtained according to the flow detection model; Perform error calculation based on the flow sample data and flow calculation value corresponding to the air valve plate angle to obtain error data; If the error data exceeds a preset error threshold, the correction function is reconstructed.

8. The flow detection method of an intelligent air valve according to claim 1, characterized in that: The flow rate detection of the intelligent air valve is performed based on the air flow rate calibration platform, and the air flow rate calibration platform includes a shell; An air inlet is provided on one side of the shell, and an air outlet is provided on the other side. The air inlet is connected to a fan to provide input air volume, and a wind speed sensor is installed on the air outlet to measure the flow value of the smart air valve outlet in real time; The inner cavity of the shell is a closed chamber, and the inner cavity is connected to the outside through the air inlet and the air outlet; A first gas rectifier and a second gas rectifier are sequentially arranged in the inner cavity of the shell from the air inlet to the air outlet, and the first gas rectifier and the second gas rectifier divide the inner cavity into three chambers, which are the first chamber, the second chamber and the third chamber from the air inlet to the air outlet; The target intelligent air valve is placed in the second chamber.

9. A flow detection method for an intelligent air valve according to claim 8, characterized in that: The first gas rectifier is movably connected to the inner wall of the shell through a slide rail, and the first gas rectifier moves along the slide rail in the inner cavity of the shell toward the air outlet or away from the air outlet to adjust the size of the second chamber.

10. A control method for an intelligent air valve, characterized in that: Get the target air volume; Based on the flow detection model constructed by the flow detection method of the intelligent air valve according to claims 1 to 9, the valve plate angle corresponding to the target air volume is calculated; The opening and closing of the corresponding intelligent air valve is controlled based on the valve plate angle.

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