Air volume detection and control method and system of composite air pipe

Abstract

The invention relates to the technical field of air volume regulation and control, and provides an air volume detection and control method and system for a composite air duct, and the method comprises the steps: constructing a load torque observer of an air conditioner fan connected with a to-be-detected composite air duct; a relational expression between the observed load torque and the actual load torque is obtained through a load torque observer, and the actual load torque is obtained through calculation according to the relational expression; the wind resistance coefficient of the to-be-detected composite air duct is calculated according to the actual load torque; according to the wind resistance coefficient of the to-be-detected composite air duct and a preset constant, real-time air volume is obtained through calculation; and the difference value between the real-time air volume and the target air volume is obtained, and when the difference value exceeds a preset threshold value, a preset air volume regulation and control strategy is started so that the composite air pipe can output the target air volume. The air volume detection cost and difficulty of the composite air pipe can be effectively reduced, the air volume of the composite air pipe can be accurately and efficiently controlled, and the user experience is effectively improved.

Description

Technical Field

[0001] The present application belongs to the technical field of air volume control, and in particular, relates to an air volume detection and control method and system of a composite air duct. Background Art

[0002] Composite air duct is a new type of building material, which is now widely used in air conditioning delivery and outlet systems. In the prior art, the air volume detection of composite air duct is mostly carried out by using a detection device (for example, a pitot tube, a venturi tube, an electric heating device, etc.) to detect each air duct separately. However, there are a large number of branch air ducts in the air conditioning delivery and outlet system. This method not only makes the air conditioning delivery and outlet system extremely complicated, but also the detection device itself will cause a certain pressure loss, the detection accuracy cannot be guaranteed, the detection method has a large workload, and requires a lot of manpower and time, and the detection cost is very high.

[0003] At the same time, the existing air-conditioning air delivery system is difficult to meet the user's air adjustment requirements, that is, the target air volume set by the user often deviates greatly from the actual air volume, resulting in a poor user experience. Summary of the invention

[0004] The embodiments of the present application provide an air volume detection and control method and system for a composite air duct to solve the above-mentioned problems in the prior art.

[0005] A first aspect of an embodiment of the present application provides an air volume detection and control method for a composite air duct, comprising:

[0006] Construct a load torque observer for the air-conditioning fan connected to the composite air duct to be tested;

[0007] The load torque observer obtains the relation between the observed load torque and the actual load torque, and the actual load torque is calculated based on the relation;

[0008] The wind resistance coefficient of the composite air duct to be tested is calculated according to the actual load torque;

[0009] The real-time air volume is calculated based on the drag coefficient of the composite air duct to be tested and a preset constant;

[0010] The real-time air volume is subtracted from the target air volume. When the difference exceeds a preset threshold, the preset air volume control strategy is activated to make the composite air duct output the target air volume.

[0011] In some embodiments, the load torque observer of the air conditioner fan connected to the composite air duct to be detected is constructed as follows:

[0012] A dynamic state equation is constructed according to operation-related parameters of the air-conditioning fan connected to the composite air duct to be tested;

[0013] The load torque observer is constructed based on the dynamic state equation.

[0014] In some embodiments, the dynamic state equation is constructed based on operation-related parameters of the air-conditioning fan connected to the composite air duct to be detected.

[0015] In some embodiments, the drag coefficient of the composite air duct to be tested is calculated based on the actual load torque.

[0016] In some embodiments, the real-time air volume is calculated based on the drag coefficient of the composite air duct to be tested and a preset constant, specifically:

[0017] The real-time wind pressure is calculated based on the wind resistance coefficient of the composite air duct to be tested and the preset constant;

[0018] The real-time wind volume is obtained based on the real-time wind pressure and the static pressure sensor.

[0019] In some embodiments, the real-time air volume is subtracted from the target air volume. When the difference exceeds a preset threshold, a preset air volume control strategy is activated to enable the composite air duct to output the target air volume. The preset air volume control strategy includes the following contents:

[0020] A regulation model is constructed based on the target air volume, and the constraints in the regulation model are optimized to obtain a nonlinear unconstrained regulation model.

[0021] The partial derivative of wind resistance is obtained according to the node air volume balance equation and the loop wind pressure balance equation, and the sensitivity of each branch air volume to the change of wind resistance is obtained jointly, and the ventilation network air volume sensitivity matrix is ​​obtained;

[0022] According to the air volume sensitivity matrix, the branch dominance of each element in the sensitivity matrix is ​​solved, and then the air volume adjustment branch pipe is determined according to the sensitivity matrix and the branch dominance;

[0023] Based on the nonlinear unconstrained regulation model and the air volume regulation branch duct, the optimal air regulation parameters are solved according to the preset optimization algorithm, and then the air conditioning fan is controlled to achieve air volume regulation.

[0024] In some embodiments, the regulation model is constructed based on the target air volume, and the constraints in the regulation model are optimized to obtain a nonlinear unconstrained regulation model, specifically:

[0025] By optimizing the penalty term through precise penalty function and combining with preset probability algorithm, the constraints in the regulation model are optimized to obtain a nonlinear unconstrained regulation model.

[0026] In some embodiments, the method of solving the branch dominance of each element in the sensitivity matrix according to the air volume sensitivity matrix, and then determining the air volume adjustment branch duct according to the sensitivity matrix and the branch dominance, includes the following steps:

[0027] Arrange the elements of the preset row in the air volume sensitivity matrix in descending order to obtain a first branch pipe set;

[0028] Arrange the elements in the branch dominance in descending order to obtain the second branch pipeline set;

[0029] The intersection of the first branch pipeline set and the second branch pipeline set is taken to obtain the third branch pipeline set, and the third branch pipeline set is excluded from the first branch pipeline set to obtain the air volume adjustment branch pipeline.

[0030] In some embodiments, the nonlinear unconstrained regulation model and the air volume regulation branch duct solve the optimal air regulation parameters according to a preset optimization algorithm, and then control the corresponding air regulation facilities to achieve air volume regulation, wherein the preset optimization algorithm is a longhorn beard search algorithm, and the longhorn beard search algorithm includes the following steps:

[0031] Step 541, initializing the population information and related parameters of the longicorn beetle whiskers, determining the adjustment branch set and the adjustment resistance range, the corresponding variable dimension and the upper and lower limits, and generating the initial population using the Latin hypercube sampling method;

[0032] Step 542, calculating the wind volume fitness of each longhorn beetle and sorting them, obtaining the current maximum fitness and its corresponding position;

[0033] Step 543, updating the position of the longhorn beetle group, and determining whether to feedback the updated longhorn beetle step length and the distance between the two whiskers;

[0034] Step 544, based on the greedy rule, calculate the wind volume fitness of all updated swarms and compare them with the current maximum fitness. If the wind volume fitness of the updated swarm is greater than the current maximum fitness, the current maximum fitness and its corresponding position are replaced by the wind volume fitness of the updated swarm and its corresponding position.

[0035] Step 545, determine whether the current iteration reaches the maximum number of iterations, if so, execute the next step, otherwise, return to step 542;

[0036] Step 546, outputting the optimal longhorn beetle individual, that is, outputting the wind resistance of the optimal adjustment branch set and the maximum adjustable air volume of the wind demand branch.

[0037] A second aspect of an embodiment of the present application provides an air volume detection and control system for a composite air duct, comprising:

[0038] A construction module is used to construct a load torque observer of an air conditioner fan connected to the composite air duct to be detected;

[0039] A first calculation module, used for obtaining a relational expression between an observed load torque and an actual load torque through a load torque observer, and calculating the actual load torque according to the relational expression;

[0040] The second calculation module is used to calculate the drag coefficient of the composite air duct to be tested according to the actual load torque;

[0041] A detection module, used to calculate the real-time air volume according to the drag coefficient of the composite air duct to be detected and a preset constant;

[0042] The control module is used to make a difference between the real-time air volume and the target air volume. When the difference exceeds a preset threshold, the preset air volume control strategy is activated to make the composite air duct output the target air volume.

[0043] A third aspect of an embodiment of the present application provides a terminal, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method described in the first aspect when executing the computer program.

[0044] A fourth aspect of an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method described in the first aspect are implemented.

[0045] A fifth aspect of the present application provides a computer program product, which, when executed on a terminal, enables the terminal to execute the steps of the method described in the first aspect.

[0046] As can be seen from the above, the embodiment of the present application does not need to set up a detection device for each air duct for separate detection, but only needs to construct a load torque observer through the operating data of the air-conditioning fan to realize the air volume detection of the composite air duct, which not only effectively reduces the detection cost and difficulty, but also has high detection accuracy.

[0047] At the same time, the embodiment of the present application makes a difference between the detected real-time air volume and the target air volume. When the difference exceeds a preset threshold, the preset air volume control strategy is activated, so that the composite air duct can output the target air volume, meet the user's air adjustment requirements, and effectively improve the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0049] Figure 1 It is a flow chart of an air volume detection and control method of a composite air duct provided in an embodiment of the present application;

[0050] Figure 2 It is a structural schematic diagram of an air volume detection and control system of a composite air duct provided in an embodiment of the present application;

[0051] Figure 3 It is a structural diagram of a terminal provided in an embodiment of the present application. DETAILED DESCRIPTION

[0052] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0053] In order to illustrate the technical solution described in this application, a specific embodiment is provided below for illustration.

[0054] Embodiment 1

[0055] See also Figure 1 , Figure 1 FIG. 1 is a flow chart of a method for detecting and controlling the air volume of a composite air duct provided in an embodiment of the present application. Figure 1 As shown, a method for detecting and controlling the air volume of a composite air duct comprises the following steps:

[0056] Step 1, constructing a load torque observer of the air conditioner fan connected to the composite air duct to be tested;

[0057] Step 2, obtaining a relational expression between the observed load torque and the actual load torque through a load torque observer, and calculating the actual load torque according to the relational expression;

[0058] Step 3, calculating the drag coefficient of the composite air duct to be tested according to the actual load torque;

[0059] Step 4, calculating the real-time air volume according to the drag coefficient of the composite air duct to be tested and a preset constant;

[0060] Step 5: Subtract the real-time air volume from the target air volume. When the difference exceeds a preset threshold, the preset air volume control strategy is activated to make the composite air duct output the target air volume.

[0061] Obviously, the embodiment of the present application does not need to set up a detection device for each air duct for separate detection, but only needs to construct a load torque observer through the operating data of the air-conditioning fan to realize the air volume detection of the composite air duct, which not only effectively reduces the detection cost and difficulty, but also has high detection accuracy.

[0062] At the same time, the embodiment of the present application makes a difference between the detected real-time air volume and the target air volume. When the difference exceeds a preset threshold, the preset air volume control strategy is activated, so that the composite air duct can output the target air volume, meet the user's air adjustment requirements, and effectively improve the user experience.

[0063] In the embodiment of the present application, step 1 is to construct a load torque observer of the air conditioner fan connected to the composite air duct to be detected, which can be specifically:

[0064] Step 11, constructing a dynamic state equation according to operation-related parameters of the air-conditioning fan connected to the composite air duct to be tested, wherein the operation-related parameters include speed, current, voltage, friction coefficient, moment of inertia, etc.;

[0065] Step 12: construct a load torque observer based on the dynamic state equation.

[0066] For example, in step 11, a dynamic state equation is constructed according to operation-related parameters of the air-conditioning fan connected to the composite air duct to be detected, wherein the dynamic state equation can be expressed by the following formula:

[0067]

[0068] In the above formula, Indicates the actual mechanical angular velocity of the fan, T L Indicates the actual load torque, represents the electromagnetic torque of the fan motor, B represents the friction coefficient, Indicates the rotational inertia of the entire motor and fan.

[0069] For example, in step 12, a load torque observer is constructed based on the dynamic state equation, wherein the load torque observer can be expressed by the following formula:

[0070]

[0071] In the above formula, represents the observed state variable acceleration, A represents two different matrices, B represents the friction coefficient, u represents the state input, K represents the state feedback gain, represents the observed state output, and y represents the actual state output.

[0072] Specifically, the observed state variables It can be expressed by the following formula:

[0073]

[0074] In the above formula, represents the observed mechanical angular velocity of the fan, represents the observed load torque;

[0075] Specifically, the matrix A can be calculated by the following formula:

[0076]

[0077] In the above formula, B represents the friction coefficient, Indicates the rotational inertia of the entire motor and fan.

[0078] Generally, the electrical response speed of an air-conditioning fan is much higher than its mechanical response speed. Therefore, it can be considered that within one control cycle of the frequency conversion controller, the load torque of the fan remains unchanged. Therefore, the dynamic state equation of the air-conditioning fan can be simplified to obtain the above dynamic state equation, and then the load torque observer can be quickly constructed to effectively save computing costs.

[0079] In the embodiment of the present application, step 2 is to obtain a relational expression between the observed load torque and the actual load torque through a load torque observer, and calculate the actual load torque according to the relational expression, wherein the relational expression between the observed load torque and the actual load torque can be expressed by the following formula:

[0080]

[0081] In the above formula, represents the observed load torque, T L represents the actual load torque, α and β represent two different desired observer poles, and s represents the fan speed.

[0082] Obviously, due to the above reasonable design of the load torque observer, real-time observation of the fan load torque can be achieved, thereby providing a reliable data basis for high-precision and high-dynamic performance air volume detection.

[0083] In the embodiment of the present application, in step 3, the drag coefficient of the composite air duct to be tested is calculated according to the actual load torque, wherein the calculation formula can be expressed by the following formula:

[0084]

[0085] In the above formula, T Lrepresents the actual load torque, f represents the drag coefficient of the composite air duct to be tested, ω r Indicates the actual mechanical angular velocity of the fan.

[0086] Obviously, when the structural parameters of the composite air duct are fixed, f is a constant. However, in practice, the composite air duct structure is affected by many factors. For example, the swing of the air guide plate, dirt and blockage and other factors will only affect the drag coefficient, and the change of the drag coefficient is the main factor affecting the air volume. The greater the wind resistance of the composite air duct, the smaller f, and different wind resistances have only a unique drag coefficient f corresponding to them. Therefore, the wind resistance level of the air duct can be reflected by the drag coefficient f, that is, the deviation between the output air volume and the actual air volume can be grasped in real time.

[0087] In the embodiment of the present application, step 4 is to calculate the real-time air volume according to the drag coefficient of the composite air duct to be detected and a preset constant, which can be specifically:

[0088] Step 41, calculating the real-time wind pressure according to the wind resistance coefficient of the composite air duct to be tested and a preset constant;

[0089] Step 42, obtaining the real-time wind volume according to the real-time wind pressure in combination with the static pressure sensor.

[0090] For example, in step 41, the real-time wind pressure is calculated according to the wind resistance coefficient of the composite air duct to be tested and a preset constant, wherein the calculation formula can be expressed by the following formula:

[0091]

[0092] In the above formula, p represents the real-time wind pressure, H and J0 are different preset constant coefficients, Indicates the actual mechanical angular velocity of the fan.

[0093] Among them, the constant coefficients H and f0 can be obtained through experimental tests. For a fixed duct system, the constant coefficients H and f0 are both constant values.

[0094] It can be seen that the above-mentioned air volume detection method provided in the embodiment of the present application does not require an external sensor, effectively reduces the detection cost, and ensures the accuracy of air volume detection.

[0095] In the embodiment of the present application, in step 5, the real-time air volume is subtracted from the target air volume. When the difference exceeds a preset threshold, a preset air volume control strategy is started to make the composite air duct output the target air volume. The preset air volume control strategy may include the following contents:

[0096] Step 51, constructing a regulation model based on the target air volume, and optimizing the constraints in the regulation model to obtain a nonlinear unconstrained regulation model;

[0097] Step 52, find the partial derivative of wind resistance according to the node air volume balance equation and the loop wind pressure balance equation, and jointly find the sensitivity of each branch air volume to the change of wind resistance to obtain the ventilation network air volume sensitivity matrix;

[0098] Step 53, according to the air volume sensitivity matrix, solving the branch dominance of each element in the sensitivity matrix, and then determining the air volume adjustment branch duct according to the sensitivity matrix and the branch dominance;

[0099] Step 54, based on the nonlinear unconstrained regulation model and the air volume regulation branch duct, the optimal air regulation parameters are solved according to the preset optimization algorithm, and then the corresponding air regulation facilities (for example, air conditioning fans) are controlled to achieve air volume regulation.

[0100] Obviously, the embodiment of the present application performs air volume control by using a preset air volume control strategy, which can not only quickly and accurately solve the optimal air volume value of the branch to be adjusted, but also the adjusted branch air volume meets the user's air adjustment requirements.

[0101] For example, in step 51, a regulation model is constructed based on the target air volume, and the constraints in the regulation model are optimized to obtain a nonlinear unconstrained regulation model, which may be:

[0102] By optimizing the penalty term through an accurate penalty function combined with a preset probability algorithm, the constraints in the regulation model are optimized to obtain a nonlinear unconstrained regulation model, wherein the preset probability algorithm may be a simulated annealing algorithm.

[0103] Combining the basic laws of air volume flow and the analysis of the constraints of air volume regulation, it can be seen that if the mathematical model for optimizing the air volume regulation of the ventilation network is nonlinear and has constraints, it is not conducive to calculation and solution. Therefore, the application of precise penalty function to convert the solution of the mathematical model for optimizing the air volume regulation into the solution of nonlinear unconstrained type problems can greatly improve the calculation efficiency and save calculation costs.

[0104] For example, step 53, according to the air volume sensitivity matrix, solving the branch dominance of each element in the sensitivity matrix, and then determining the air volume adjustment branch duct according to the sensitivity matrix and the branch dominance, may include the following steps:

[0105] Step 531, arranging the elements of the preset row in the air volume sensitivity matrix in descending order to obtain a first branch pipe set;

[0106] Step 532, arranging the elements in the branch dominance in descending order to obtain a second branch pipeline set;

[0107] Step 533, taking the intersection of the first branch pipeline set and the second branch pipeline set to obtain the third branch pipeline set, excluding the third branch pipeline set from the first branch pipeline set, and obtaining the air volume adjustment branch pipeline.

[0108] For example, step 54, based on the nonlinear unconstrained regulation model and the air volume regulation branch pipeline, the optimal air regulation parameters are solved according to the preset optimization algorithm, and then the corresponding air regulation facilities are controlled to achieve air volume regulation, wherein the preset optimization algorithm may be a longhorn beard search algorithm, and specifically, the longhorn beard search algorithm may include the following steps:

[0109] Step 541, initializing the population information and related parameters of the longicorn beetle whiskers, determining the adjustment branch set and the adjustment resistance range, the corresponding variable dimension and the upper and lower limits, and generating the initial population using the Latin hypercube sampling method;

[0110] Step 542, calculating the wind volume fitness of each longhorn beetle and sorting them, obtaining the current maximum fitness and its corresponding position;

[0111] Step 543, updating the position of the longhorn beetle group, and determining whether to feedback the updated longhorn beetle step length and the distance between the two whiskers;

[0112] Step 544, based on the greedy rule, calculate the wind volume fitness of all updated swarms and compare them with the current maximum fitness. If the wind volume fitness of the updated swarm is greater than the current maximum fitness, the current maximum fitness and its corresponding position are replaced by the wind volume fitness of the updated swarm and its corresponding position.

[0113] Step 545, determine whether the current iteration reaches the maximum number of iterations, if so, execute the next step, otherwise, return to step 542;

[0114] Step 546, outputting the optimal longhorn beetle individual, that is, outputting the wind resistance of the optimal adjustment branch set and the maximum adjustable air volume of the wind demand branch.

[0115] Obviously, the embodiment of the present application generates the initial population through the Latin hypercube sampling method, which effectively improves the population diversity, enhances the global and local optimization capabilities, and thus can achieve fast and accurate optimization.

[0116] Embodiment 2

[0117] See also Figure 2 , Figure 2 This is a structural schematic diagram of an air volume detection and control system for a composite air duct provided in an embodiment of the present application. For ease of explanation, only the parts related to the embodiment of the present application are shown.

[0118] An air volume detection and control system for a composite air duct provided in an embodiment of the present application includes:

[0119] Building module 1, used to build a load torque observer of the air conditioner fan connected to the composite air duct to be tested;

[0120] A first calculation module 2, used for obtaining a relational expression between an observed load torque and an actual load torque through a load torque observer, and calculating the actual load torque according to the relational expression;

[0121] The second calculation module 3 is used to calculate the drag coefficient of the composite air duct to be tested according to the actual load torque;

[0122] The detection module 4 is used to calculate the real-time air volume according to the drag coefficient of the composite air duct to be detected and a preset constant;

[0123] The control module 5 is used to make a difference between the real-time air volume and the target air volume. When the difference exceeds a preset threshold, a preset air volume control strategy is activated to make the composite air duct output the target air volume.

[0124] Obviously, the embodiment of the present application does not need to set up a detection device for each air duct for separate detection, but only needs to construct a load torque observer through the operating data of the air-conditioning fan to realize the air volume detection of the composite air duct, which not only effectively reduces the detection cost and difficulty, but also has high detection accuracy.

[0125] At the same time, the embodiment of the present application makes a difference between the detected real-time air volume and the target air volume. When the difference exceeds a preset threshold, the preset air volume control strategy is activated, so that the composite air duct can output the target air volume, meet the user's air adjustment requirements, and effectively improve the user experience.

[0126] Embodiment 3

[0127] Figure 3 is a structural diagram of a terminal provided in an embodiment of the present application. As shown in the figure, the terminal 3 of the embodiment includes: at least one processor 30 ( Figure 3 Only one is shown in the figure), a memory 31, and a computer program 32 stored in the memory 31 and executable on the at least one processor 30, wherein the processor 30 implements the steps of any of the above-mentioned method embodiments when executing the computer program 32.

[0128] The terminal 3 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The terminal 3 may include, but is not limited to, a processor 30 and a memory 31. Those skilled in the art will appreciate that Figure 3 It is only an example of terminal 3 and does not constitute a limitation on terminal 3. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the terminal may also include input and output devices, network access devices, buses, etc.

[0129] The processor 30 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0130] The memory 31 may be an internal storage unit of the terminal 3, such as a hard disk or memory of the terminal 3. The memory 31 may also be an external storage device of the terminal 3, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the terminal 3. Further, the memory 31 may also include both an internal storage unit of the terminal 3 and an external storage device. The memory 31 is used to store the computer program and other programs and data required by the terminal. The memory 31 may also be used to temporarily store data that has been output or is to be output.

[0131] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0132] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for detecting and controlling the air volume of a composite air duct, characterized in that: include: Construct a load torque observer for the air-conditioning fan connected to the composite air duct to be tested; The load torque observer obtains the relation between the observed load torque and the actual load torque, and the actual load torque is calculated based on the relation; The wind resistance coefficient of the composite air duct to be tested is calculated according to the actual load torque; The real-time air volume is calculated based on the drag coefficient of the composite air duct to be tested and a preset constant; The real-time air volume is subtracted from the target air volume. When the difference exceeds a preset threshold, the preset air volume control strategy is activated to make the composite air duct output the target air volume.

2. The method according to claim 1, characterized in that The load torque observer of the air conditioner fan connected to the composite air duct to be detected is constructed as follows: A dynamic state equation is constructed according to operation-related parameters of the air-conditioning fan connected to the composite air duct to be tested; The load torque observer is constructed based on the dynamic state equation.

3. The method according to claim 2, characterized in that The dynamic state equation is constructed according to the operation-related parameters of the air-conditioning fan connected to the composite air duct to be tested.

4. The method according to claim 1, characterized in that: The wind resistance coefficient of the composite air duct to be tested is calculated based on the actual load torque.

5. The method according to claim 1, characterized in that The real-time air volume is calculated based on the drag coefficient of the composite air duct to be tested and a preset constant, specifically: The real-time wind pressure is calculated based on the wind resistance coefficient of the composite air duct to be tested and the preset constant; The real-time wind volume is obtained based on the real-time wind pressure and the static pressure sensor.

6. The method according to claim 1, characterized in that The real-time air volume is subtracted from the target air volume. When the difference exceeds a preset threshold, a preset air volume control strategy is started to make the composite air duct output the target air volume. The preset air volume control strategy includes the following contents: A regulation model is constructed based on the target air volume, and the constraints in the regulation model are optimized to obtain a nonlinear unconstrained regulation model. The partial derivative of wind resistance is obtained according to the node air volume balance equation and the loop wind pressure balance equation, and the sensitivity of each branch air volume to the change of wind resistance is obtained jointly, and the ventilation network air volume sensitivity matrix is ​​obtained; According to the air volume sensitivity matrix, the branch dominance of each element in the sensitivity matrix is ​​solved, and then the air volume adjustment branch pipe is determined according to the sensitivity matrix and the branch dominance; Based on the nonlinear unconstrained regulation model and the air volume regulation branch duct, the optimal air regulation parameters are solved according to the preset optimization algorithm, and then the air conditioning fan is controlled to achieve air volume regulation.

7. The method according to claim 6, characterized in that The regulation model is constructed based on the target air volume, and the constraints in the regulation model are optimized to obtain a nonlinear unconstrained regulation model, which is specifically: By optimizing the penalty term through precise penalty function and combining with preset probability algorithm, the constraints in the regulation model are optimized to obtain a nonlinear unconstrained regulation model.

8. The method according to claim 6, characterized in that The method of solving the branch dominance of each element in the sensitivity matrix according to the air volume sensitivity matrix, and then determining the air volume adjustment branch pipe according to the sensitivity matrix and the branch dominance, comprises the following steps: Arrange the elements of the preset row in the air volume sensitivity matrix in descending order to obtain a first branch pipe set; Arrange the elements in the branch dominance in descending order to obtain the second branch pipeline set; The intersection of the first branch pipeline set and the second branch pipeline set is taken to obtain the third branch pipeline set, and the third branch pipeline set is excluded from the first branch pipeline set to obtain the air volume adjustment branch pipeline.

9. The method according to claim 6, characterized in that The nonlinear unconstrained regulation model and the air volume regulation branch pipeline are used to solve the optimal air regulation parameters according to the preset optimization algorithm, and then control the corresponding air regulation facilities to achieve air volume regulation, wherein the preset optimization algorithm is the beetle whisker search algorithm, and the beetle whisker search algorithm includes the following steps: Step 541, initializing the population information and related parameters of the longicorn beetle whiskers, determining the adjustment branch set and the adjustment resistance range, the corresponding variable dimension and the upper and lower limits, and generating the initial population using the Latin hypercube sampling method; Step 542, calculating the wind volume fitness of each longhorn beetle and sorting them, obtaining the current maximum fitness and its corresponding position; Step 543, updating the position of the longhorn beetle group, and determining whether to feedback the updated longhorn beetle step length and the distance between the two whiskers; Step 544, based on the greedy rule, calculate the wind volume fitness of all updated swarms and compare them with the current maximum fitness. If the wind volume fitness of the updated swarm is greater than the current maximum fitness, the current maximum fitness and its corresponding position are replaced by the wind volume fitness of the updated swarm and its corresponding position. Step 545, determine whether the current iteration reaches the maximum number of iterations, if so, execute the next step, otherwise, return to step 542; Step 546, outputting the optimal longhorn beetle individual, that is, outputting the wind resistance of the optimal adjustment branch set and the maximum adjustable air volume of the wind demand branch.

10. An air volume detection and control system for a composite air duct, the system implementing the method according to claim 1, characterized in that: include: A construction module is used to construct a load torque observer of an air conditioner fan connected to the composite air duct to be detected; A first calculation module, used for obtaining a relational expression between an observed load torque and an actual load torque through a load torque observer, and calculating the actual load torque according to the relational expression; The second calculation module is used to calculate the drag coefficient of the composite air duct to be tested according to the actual load torque; A detection module, used to calculate the real-time air volume according to the drag coefficient of the composite air duct to be detected and a preset constant; The control module is used to make a difference between the real-time air volume and the target air volume. When the difference exceeds a preset threshold, the preset air volume control strategy is activated to make the composite air duct output the target air volume.

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