A non-iterative debugging method and system based on a wind system pipe network calculation model and a storage medium

Abstract

The application provides a non-iterative debugging method and system based on a wind system pipe network calculation model and a storage medium. First, the wind system is measured, and the measurement parameters include the air volume of each end of the wind system and the static pressure at the outlet of the fan. Then, the characteristics of the wind system pipe network system are solved, and the solving parameters include the resistance coefficient of each branch of the wind system and the static pressure at each branch point. Then, the target resistance coefficient of the wind system is solved, which is the resistance coefficient of each end branch when the wind system reaches a balanced state. Then, the pre-judgment flow of each end is solved, which is the flow reference value to be used when each end valve is adjusted. Then, the pre-judgment flow of each end is used to guide the on-site debugging. The application provides a new debugging method, and each end valve only needs to be adjusted once to make the wind system reach a balance. This method makes the debugging work free from the trial-and-error process, improves the debugging efficiency and accuracy.

Description

Technical Field

[0001] This invention belongs to the field of ventilation system control technology, and in particular relates to a non-iterative debugging method based on a calculation model of a ventilation system duct network. Background Technology

[0002] In the design of air conditioning system duct networks, theoretically, hydraulic balance under design conditions can be achieved through methods such as selecting appropriate pipe diameters. However, due to the imprecise nature of flow calculation methods, duct design alone cannot guarantee a proper balance. Therefore, to ensure adequate balance, the valve openings in the air conditioning system must be adjusted until the design flow rate of the entire system meets the requirements of the specifications. By properly balancing the flow rate, the operating costs of the system can be reduced, the comfort of occupants in the building can be improved, and the service life of HVAC equipment can be extended.

[0003] Existing commissioning methods are iterative approaches requiring multiple measurements and repeated valve opening adjustments. First, flow rate and pressure are measured; then, the valve opening is adjusted to match the design flow rate; the flow rate is measured again, and this process of measurement and adjustment is repeated during trial and error until the design flow rate is achieved. This method is effective for simple ventilation systems. However, for ventilation systems with numerous branches and complex layouts, frequent on-site measurements and repeated adjustments by workers are necessary to bring the airflow close to the design value. This commissioning process is not only highly dependent on worker experience but also time-consuming and labor-intensive. Furthermore, errors in the measuring equipment and operation of parameters such as airflow and pressure make it difficult to guarantee the commissioning effect and efficiency of the ventilation ducts. Therefore, there is an urgent need to develop simpler and more efficient non-iterative commissioning methods for ventilation systems, freeing commissioning work from repeated trial and error and improving commissioning efficiency and accuracy. Summary of the Invention

[0004] This invention provides a non-iterative debugging method based on a wind system duct network calculation model, aiming to solve the problems of excessive reliance on debugging experience and time-consuming and labor-intensive debugging in complex ventilation systems.

[0005] The objective of this invention is achieved through the following scheme: a non-iterative debugging method based on a wind system pipeline network calculation model, comprising the following steps:

[0006] Step 1: Measure the air system using measuring equipment. The measured parameters include the air volume at each terminal of the air system and the static pressure at the fan outlet.

[0007] The measurement parameters were completed under two different operating conditions. The first operating condition was that all end valves were fully open, and the second operating condition was that the end valve farthest from the fan was closed, while the remaining end valves were fully open.

[0008] For a wind system with n terminals, there are a total of 2n+1 measurement parameters, including 2n-1 terminal air volume values ​​and 2 fan outlet static pressure values, where n is a natural number and n≥1.

[0009] Step 2: The calculation module solves for the characteristics of the air system network. The solution parameters include the resistance coefficient of each branch of the air system and the static pressure at each branch point.

[0010] For a wind system with n terminals, there are a total of 2n-1 branches and n-1 branch points, corresponding to 2n-1 branch drag coefficients and n-1 branch point static pressures;

[0011] The first set of operating conditions contains 3n solution parameters, including 2n-1 branch resistance coefficients, n-1 branch point static pressures, and 2 fan constants; the second set of operating conditions contains n-1 solution parameters, including n-1 branch point static pressures; there are a total of 4n-1 solution parameters for the characteristics of the air system network.

[0012] For a wind system with n terminals, there are 2n-1 branches, corresponding to 2n-1 pressure drop-flow equations;

[0013] The first set of operating conditions contains 2n equations, including 2n-1 pressure drop-flow rate equations and 1 fan static pressure-flow rate curve equation; the second set of operating conditions contains 2n-1 equations, including 2n-2 pressure drop-flow rate equations and 1 fan static pressure-flow rate equation; in total, there are 4n-1 equations for solving the characteristics of the air system network, which can be used to solve the characteristics of the air system network.

[0014] The static pressure-flow rate curve equation of the fan is fitted using the quadratic relationship shown in equation (1); the pressure drop-flow rate equation of the air system pipeline is fitted using the quadratic relationship shown in equation (2):

[0015] P Fan =AB*Q Fan 2 (1)

[0016] ΔP=K*Q 2 (2)

[0017] In the formula, P Fan Q is the static pressure at the fan outlet, in Pa. Fan This refers to the fan outlet flow rate, in meters per second (m³). 3 / h; A is the fan constant, in Pa; B is the fan constant, in Pa / (m 3 / h) 2 ΔP is the branch pressure drop, in Pa; Q is the branch flow rate, in m³ / s. 3 / h; K is the branch resistance coefficient, in Pa / (m)3 / h) 2 .

[0018] Step 3: The calculation module solves for the target drag coefficient of the wind system. The target drag coefficient is the drag coefficient of each terminal branch when the wind system reaches equilibrium.

[0019] For a wind system with n terminals, there are 2n solution parameters in equilibrium, including n terminal branch drag coefficients and n branch point static pressures.

[0020] For a wind system with n terminals, there are 2n equations to solve in equilibrium, including 2n-1 pressure drop-flow rate equations and 1 fan static pressure-flow rate curve equation, which can be used to solve for the target drag coefficient of the wind system.

[0021] Step 4: The calculation module calculates the predicted flow rate for each terminal. The predicted flow rate is the reference value of the flow rate that needs to be used when adjusting the valves at each terminal.

[0022] First, the predicted flow rate of branch 1, which is closest to the wind turbine, is calculated. For a wind system with n terminals, the resistance coefficient of branch 1 is set as the target value, and the other branches are set as the initial value. The flow rate of each branch under this condition is calculated. The flow rate of branch 1 is the predicted flow rate of branch 1.

[0023] The process of determining the predicted flow rate of branch 1 includes 2n solution parameters, including n end branch resistance coefficients and n branch point static pressures; the process of determining the predicted flow rate of branch 1 includes 2n solution equations, including 2n-1 pressure drop-flow rate equations and 1 fan static pressure-flow rate curve equation, which can be used to determine the predicted flow rate of branch 1.

[0024] The method for calculating the predicted flow of the remaining branches 2 to n is the same as that for branch 1.

[0025] Step 5: The computer uses the calculation module to calculate and analyze the predicted flow rate of each terminal, and displays it through the visualization module to guide on-site debugging. Each terminal only needs to be adjusted once to make the air system reach a balanced state.

[0026] The present invention has the following beneficial effects:

[0027] This invention enables the air system to reach equilibrium with only one adjustment for each terminal valve. This method addresses numerous challenges encountered when commissioning complex ventilation duct systems, such as high commissioning difficulty, heavy reliance on experienced operators, time-consuming and labor-intensive processes, and large experimental testing errors. It eliminates the need for repeated trial and error, improving commissioning efficiency and accuracy. Based on minimal measurements and a deep understanding of the duct network's characteristics, this invention solves for the air system's network characteristics, target resistance coefficient, and predicted flow rates at each terminal valve. Finally, adjustments are made to each terminal valve based on the predicted flow rates to achieve system equilibrium. Compared to traditional techniques, this method offers faster adjustment, lower power consumption, and higher accuracy, achieving a one-step commissioning effect. Attached Figure Description

[0028] Figure 1 This is a flowchart of the non-iterative debugging method based on the wind system pipeline network calculation model described in this invention;

[0029] Figure 2 This is a schematic diagram of the three-terminal wind system model described in this invention; Detailed Implementation

[0030] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, but the scope of protection of the present invention is not limited thereto.

[0031] The preferred embodiment of the present invention is as follows: Figure 2 The model shown is a three-terminal wind system built using simulation software, where the flow rate setpoints for branches 1 to 3 are 1500 m³ / s. 3 / h, 1000m 3 / h, 1000m 3 / h, under the initial operating conditions of the wind system, the flow rates of branches 1 to 3 are 1869 m³ / h. 3 / h、910m 3 / h、910m 3 / h, the three terminals of the wind system are in an unbalanced state. The non-iterative debugging method based on the wind system pipeline calculation model described in this invention is as follows: Figure 1 As shown, the specific process includes the following:

[0032] Step 1: Measure the air system using appropriate measuring equipment. The measurement parameters include the air volume at each terminal of the air system and the static pressure at the fan outlet. Input the measured data into the computer and perform subsequent analysis by the computer's calculation module.

[0033] The measurement parameters were obtained under two different operating conditions. The first condition was that all end valves were fully open, and the second condition was that the end valve farthest from the fan was closed, while the remaining end valves were fully open.

[0034] In this embodiment, the air system has 3 terminals, so there are a total of 7 measurement parameters, including 5 terminal air volume values ​​and 2 fan outlet static pressure values.

[0035] Step 2: The calculation module solves for the characteristics of the air system network. The solution parameters include the resistance coefficient of each branch of the air system and the static pressure at each branch point.

[0036] For a wind system with 3 terminals, there are a total of 5 branches and 2 branch points, corresponding to the drag coefficient of the 5 branches and the static pressure of the 2 branch points;

[0037] The first set of operating conditions includes 9 solution parameters, including 5 branch resistance coefficients, 2 branch point static pressures, and 2 fan constants; the second set of operating conditions includes 2 solution parameters, including 2 branch point static pressures; a total of 11 solution parameters for the characteristics of the air system network are calculated.

[0038] For a wind system with 3 terminals, there are 5 branches, corresponding to 5 pressure drop-flow equations;

[0039] The first set of operating conditions contains 6 solution equations, including 5 pressure drop-flow equations and 1 fan static pressure-flow curve equation; the second set of operating conditions contains 5 solution equations, including 4 pressure drop-flow equations and 1 fan static pressure-flow equation; in total, there are 11 equations for solving the characteristics of the air system network, which can be used to solve the characteristics of the air system network.

[0040] The static pressure-flow rate curve equation of the fan is fitted using the quadratic relationship shown in equation (1); the pressure drop-flow rate equation of the air system pipeline is fitted using the quadratic relationship shown in equation (2):

[0041] P Fan =AB*Q Fan 2 (1)

[0042] ΔP=K*Q 2 (2)

[0043] In the formula, P Fan Q is the static pressure at the fan outlet, in Pa. Fan This refers to the fan outlet flow rate, in meters per second (m³). 3 / h; A is the fan constant, in Pa; B is the fan constant, in Pa / (m 3 / h) 2 ΔP is the branch pressure drop, in Pa; Q is the branch flow rate, in m³ / s. 3 / h; K is the branch resistance coefficient, in Pa / (m) 3 / h) 2 . Figure 2In the diagram, the numbers 1, 2, and 3 represent the three ends; Q1, Q2, Q3, Q 45 Q 56 Represents the flow rates of each branch; K1, K2, K3, K 45 K 56 This represents the resistance coefficient of each branch road.

[0044] Step 3: The calculation module solves for the target drag coefficient of the wind system. The target drag coefficient is the drag coefficient of each terminal branch when the wind system reaches equilibrium.

[0045] For a wind system with 3 terminals, there are 6 solution parameters in equilibrium, including 3 terminal branch drag coefficients and 3 branch point static pressures.

[0046] For a wind system with three terminals, there are six equations to solve in equilibrium, including five pressure drop-flow equations and one fan static pressure-flow curve equation, which can be used to solve for the target drag coefficient of the wind system.

[0047] Step 4: The calculation module calculates the predicted flow rate for each terminal. The predicted flow rate is the reference value of the flow rate that needs to be used when adjusting the valves at each terminal.

[0048] First, the predicted flow rate of branch 1, which is closest to the fan, is calculated. For a wind system with three terminals, the resistance coefficient of branch 1 is set as the target value, and the other branches are set as the initial values. The flow rate of each branch under this condition is then calculated. The flow rate of branch 1 is the predicted flow rate of branch 1.

[0049] The process of determining the predicted flow rate of branch 1 includes 6 solution parameters, including 3 end branch resistance coefficients and 3 branch point static pressures; the process of determining the predicted flow rate of branch 1 includes 6 solution equations, including 5 pressure drop-flow equations and 1 fan static pressure-flow curve equation, which can be used to determine the predicted flow rate of branch 1.

[0050] The method for calculating the predicted flow for the remaining branches 2 and 3 is the same as that for branch 1.

[0051] Step 5: The computer uses the calculation module to calculate and analyze the predicted flow rate of each terminal, and displays it through the visualization module to guide on-site debugging. Each terminal only needs to be adjusted once to make the air system reach a balanced state.

[0052] The commissioning results of the three-terminal ventilation system in this embodiment are shown in Table 1 below:

[0053] Table 1. Commissioning results of the ventilation system in the embodiment.

[0054]

[0055] This invention also provides a non-iterative debugging system based on a wind system network calculation model, comprising a measurement device and a computer. The measurement device measures the air volume at each terminal of the wind system and the static pressure at the fan outlet, and inputs the data into the computer. The computer uses a calculation module to solve for the characteristics of the wind system network, the target resistance coefficient of the wind system, and the predicted flow rate at each terminal. Finally, the calculation results are displayed through a visualization module as reference data for on-site debugging.

[0056] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described non-iterative debugging method based on a wind system pipeline network calculation model.

[0057] The embodiments described above are preferred embodiments of the present invention, but the present invention is not limited to the above embodiments. Any obvious improvements, substitutions or modifications that can be made by those skilled in the art without departing from the essence of the present invention shall fall within the protection scope of the present invention.

Claims

1. A non-iterative debugging method based on a wind system pipeline network calculation model, characterized in that, The process includes the following: Step 1: Measure the air system using measuring equipment. The measured parameters include the air volume at each terminal of the air system and the static pressure at the fan outlet. In Step 1, the measured parameters are completed under two different operating conditions. The first condition is that all terminal valves are fully open, and the second condition is that the terminal valve farthest from the fan is closed, while the remaining terminal valves are fully open. For an air system with n terminals, there are a total of 2n+1 measured parameters, including 2n-1 terminal air volume values ​​and 2 fan outlet static pressure values; n is a natural number and n≥1. Step 2: The calculation module receives the measurement parameters, analyzes the characteristics of the air system network, and obtains the resistance coefficients and static pressures of each branch of the air system. In Step 2, the first set of operating conditions includes 2n-1 branch resistance coefficients, n-1 branch point static pressures, and 2 fan constants; the second set of operating conditions includes n-1 branch point static pressures; a total of 4n-1 solution parameters for the air system network characteristics are calculated. The first set of operating conditions includes 2n-1 pressure drop-flow rate equations and 1 fan static pressure-flow rate curve equation; the second set of operating conditions includes 2n-2 pressure drop-flow rate equations and 1 fan static pressure-flow rate equation. The calculation module analyzes and solves the air system network characteristics based on these parameters. Step 3: The calculation module calculates and obtains the target drag coefficient of the wind system. The target drag coefficient is the drag coefficient of each terminal branch when the wind system reaches equilibrium. In Step 3, for a wind system with n terminals, it includes n terminal branch drag coefficients and n branch point static pressures in equilibrium. For a wind system with n terminals, it includes 2n-1 pressure drop-flow rate equations and 1 fan static pressure-flow rate curve equation in equilibrium. The calculation module solves for the target drag coefficient of the wind system based on these equations. Step 4: The calculation module calculates and obtains the predicted flow rate of each terminal. The predicted flow rate is the flow rate reference value that needs to be used when adjusting the valves at each terminal. In step 4, the calculation module calculates and obtains the predicted flow rate for each terminal as follows: First, the predicted flow rate of branch 1, which is closest to the wind turbine, is calculated. For a wind system with n terminals, the resistance coefficient of branch 1 is set as the target value, and the other branches are set as the initial value. The flow rate of each branch under this state is calculated, and the flow rate of branch 1 is the predicted flow rate of branch 1. The process of calculating the predicted flow rate of branch 1 includes 2n calculation parameters: n end branch resistance coefficients and n branch point static pressures; the process of calculating the predicted flow rate of branch 1 includes 2n calculation equations: 2n-1 pressure drop-flow rate equations and 1 fan static pressure-flow rate curve equation. The calculation module calculates the predicted flow rate of branch 1 based on these equations. The method for calculating the predicted flow of the remaining branches 2 to n is the same as that for branch 1; Step 5: Calculate and analyze the predicted flow rate of each terminal using the calculation module and display it through the visualization module to guide on-site debugging. Each terminal only needs to be adjusted once to bring the air system to a balanced state. The static pressure-flow rate curve equation of the fan is fitted using the quadratic relationship shown in the following formula: ； in, This refers to the static pressure at the fan outlet. This refers to the fan outlet flow rate; For wind turbine constants; For wind turbine constants; The pressure drop-flow rate equation is fitted using the quadratic relationship shown in the following equation: ； in, For branch voltage drop; For branch traffic; This is the branch resistance coefficient.

2. A system for implementing the non-iterative debugging method based on the wind system pipeline network calculation model as described in claim 1, comprising a measuring device and a computer. The measuring device measures the air volume at each terminal of the wind system and the static pressure at the fan outlet, and inputs the data into the computer. The computer uses a calculation module to solve for the characteristics of the wind system pipeline network, the target resistance coefficient of the wind system, and the predicted flow rate at each terminal. Finally, the calculation results are displayed through a visualization module as reference data for on-site debugging.

3. A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the non-iterative debugging method based on a wind system pipeline network calculation model as described in claim 1.

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