Flow calculation method for high-precision intelligent measurement and control valve under multi-parameter coordinated regulation and control

Abstract

The invention discloses a flow calculation method for a high-precision intelligent measurement and control valve under multi-parameter cooperative regulation and control, and relates to the technical field of intelligent measurement and control valve flow measurement. The method comprises the following steps: establishing a valve flow test experiment platform, selecting a working range of valve pressure difference and valve opening and a proper independent variable interval to carry out a flow test experiment, carrying out coefficient fitting on a flow function and an opening function according to actually measured data, and calculating the flow of the valve according to the flow function obtained by fitting. The flow value of the valve can be calculated according to any group of instantaneous valve opening and valve pressure difference data in practice, and the corresponding valve opening can be calculated according to any group of valve pressure difference and flow value in practice according to the opening function obtained through fitting; according to the flow calculation method for the high-precision intelligent measurement and control valve under the multi-parameter cooperative regulation and control, the flow function and the opening function are fitted through real data, the precision is high, and the flow calculation method is controllable within a certain range.

Description

Technical Field

[0001] The present invention relates to the technical field of flow measurement of intelligent measuring and control valves, and in particular to a flow calculation method for high-precision intelligent measuring and control valves under multi-parameter coordinated regulation. Background Art

[0002] The integrated meter-valve design for heating systems integrates the meter and control valve into a single unit, saving space, simplifying installation, and reducing costs. It also reduces pipe connection points, improves sealing, and mitigates leakage risks. Existing integrated meter-valve designs simply connect the meter and control valve in series, failing to demonstrate the true technical and price advantages of integrated meter-valve designs. This is primarily due to limitations in flow measurement technology. Traditional differential pressure flow calculation methods utilize the Bernoulli principle to calculate flow, which has numerous limitations. For example, to ensure that the pressure differential at the measuring point matches the pressure value required by the calculation formula, a certain length of regular piping must exist before and after the flowmeter, and the cross-sectional shape of the measuring section must be regular and unchanging. Failure to meet these requirements significantly affects measurement accuracy. Valves are typically short, and the cross-sectional shape of the valve opening is not a regular circle or rectangle. Furthermore, the cross-sectional area of ​​the valve opening changes during operation as the valve opening varies. These issues render traditional differential pressure flow calculation methods unsuitable. Furthermore, for intelligent measurement and control valves, existing technology cannot calculate the precise valve opening corresponding to a given flow rate, requiring only gradual approach to the desired opening through repeated debugging. Summary of the Invention

[0003] The purpose of the present invention is to provide a flow calculation method for high-precision intelligent measurement and control valves under multi-parameter coordinated regulation, which breaks through the limitations of pipeline geometric parameters and has wider applicability. The intelligent measurement and control valve based on this calculation method can simplify the hardware structure design, achieve lightweight equipment while ensuring control accuracy, thereby achieving the dual goals of reducing construction and operating production costs and improving system efficiency.

[0004] To achieve the above objectives, the present invention provides a flow calculation method for a high-precision intelligent measurement and control valve under multi-parameter coordinated regulation, comprising the following steps:

[0005] S1. Build a valve flow test experimental platform;

[0006] S2. Select the valve pressure difference, valve opening working range and appropriate independent variable spacing to carry out flow test experiment;

[0007] S3, fitting the coefficients of the flow function and the opening function according to the measured data in S2;

[0008] S4. Based on the flow function obtained by fitting in S3, the flow value of the valve can be calculated from any set of instantaneous valve opening and valve pressure difference data in practice;

[0009] S5. Based on the opening function obtained by fitting in S3, the corresponding valve opening can be calculated from any set of valve pressure difference and flow values ​​in practice.

[0010] Preferably, the specific process in S1 is as follows:

[0011] S11. Install an actuator on the valve in the constructed valve flow test experimental platform;

[0012] S12. Install differential pressure transmitters at two pressure measuring points located before and after the valve;

[0013] S13. Install a recording and calibrated flow meter upstream of the valve.

[0014] Preferably, the specific process in S2 is as follows:

[0015] S21, fix the valve pressure difference, and adjust the valve opening from small to large according to the selected independent variable interval;

[0016] S22. After the readings of the differential pressure transmitter and the recorder calibration flowmeter are stable, record the values ​​on the differential pressure transmitter and the recorder calibration flowmeter at each valve opening;

[0017] S23. Increase the valve pressure difference according to the selected independent variable interval, and repeat the above process until the valve pressure difference reaches the maximum value within the selected working range.

[0018] Preferably, the working range of the valve opening in S2 is set to 0-70 degrees, the working range of the valve pressure difference is set to 0-200000Pa, the independent variable spacing includes the valve opening spacing and the valve pressure difference spacing, the valve opening spacing is selected to be 2.5 degrees, and the valve pressure difference spacing is selected to be 25000Pa.

[0019] Preferably, the specific formula of the flow function in S3 is as follows:

[0020] Q(x,y)=(a1+a2x+a3x 2 +…+a m+1 x m )(b1+b2y+b3y 2 +…+b n+1 y n );

[0021] Where x is the valve opening, y is the valve pressure difference, a1~a m+1 and b1~b n+1 are the coefficients obtained by fitting, m,n∈N, and N is a set of positive integers.

[0022] Preferably, the specific formula of the opening function in S3 is as follows:

[0023] O(z,y)=(c1+c2z+c3z 2 +…+c j+1 z j )(d1+d2y+d3y 2 +…+d k+1 y k );

[0024] Where z is the valve flow, c1~c j+1 and d1~d k+1 are the coefficients obtained by fitting, j,k∈N.

[0025] Preferably, the coefficient fitting in S3 uses the Levenberg-Marquardt optimization algorithm to solve the nonlinear least squares problem to obtain the coefficients of the fitting function, and the process is as follows:

[0026] S31. Construct a fitting function model:

[0027] z=f(x,y;β);

[0028] Among them, β = [β1, β2, β3,...,β M ] T is the coefficient matrix of the fitting function to be solved, T is the transpose symbol of the matrix, β1~β M is an element in the coefficient matrix, M∈N, x and y are the two independent variables of the fitting function, and z is the dependent variable of the fitting function;

[0029] S32. Determine the optimization objective function. The optimization objective is to minimize the residual sum of squares. The residual sum of squares S(β) is as follows:

[0030]

[0031] Among them, f(x i ,y i ; β) is the known data x i 、y i Substitute the calculated value obtained by fitting formula, z i is the i-th known data of the dependent variable z, x i is the i-th known data of the independent variable x, y i is the i-th known data of the independent variable y, i∈N;

[0032] Then the residual vector r(β) is expressed as:

[0033] r(β)=[r1,r2,r3,...,r t ] T;

[0034] where r i =z i -f(x i ,y i ;β),t∈N;

[0035] S33, initializing the algorithm and coefficient matrix β;

[0036] S34, using the Levenberg-Marquardt optimization algorithm to iterate until the termination condition is met, and the coefficient matrix β is obtained to obtain the complete fitting function;

[0037] S35. For the kth iteration, the core iteration formula of the Levenberg-Marquardt optimization algorithm is expressed as:

[0038]

[0039] Among them, μ k is the damping factor, D k is the scaling matrix, r k is the residual vector, J k is the Jacobian matrix of the residual, δ k is the parameter increment to be solved in the iterative process.

[0040] Therefore, the present invention adopts the above-mentioned flow calculation method for high-precision intelligent measurement and control valve under multi-parameter coordinated control, which has the following beneficial effects compared with the prior art:

[0041] 1. This application can effectively solve the current defects of the meter and the regulating valve being difficult to integrate into one unit and the inability to calculate the precise opening of the valve at a certain flow rate;

[0042] 2. This application can make the measurement accuracy of flow rate and opening controllable within a certain range, and is suitable for most scenarios such as heating, air conditioning and water supply.

[0043] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 This is an overall flow chart of a flow calculation method for a high-precision intelligent measurement and control valve under multi-parameter coordinated regulation according to the present invention;

[0045] Figure 2 This is a flow function fitting result diagram of a flow calculation method for a high-precision intelligent measurement and control valve under multi-parameter coordinated regulation according to the present invention;

[0046] Figure 3This is a diagram of the opening function fitting results of a flow calculation method for a high-precision intelligent measurement and control valve under multi-parameter coordinated regulation according to the present invention. DETAILED DESCRIPTION

[0047] In the description of the present invention, it should be noted that the terms "upper", "lower", "inside", "outside", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, or are the orientations or positional relationships in which the inventive product is usually placed when in use. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, they should not be understood as limiting the present invention.

[0048] Example

[0049] like Figure 1-Figure 3 As shown, a flow calculation method for a high-precision intelligent measurement and control valve under multi-parameter coordinated regulation of the present invention includes the following steps:

[0050] S1. Build a valve flow test experimental platform;

[0051] S11. Install an actuator on the valve in the constructed valve flow test experimental platform;

[0052] S12. Install differential pressure transmitters at two pressure measuring points located before and after the valve;

[0053] S13. Install a recording and calibrating flow meter upstream of the valve;

[0054] S2. Select the valve pressure difference, valve opening working range and appropriate independent variable spacing to carry out flow test experiments; the valve opening working range is set to 0-70 degrees, the valve pressure difference working range is set to 0-200000Pa, and the independent variable spacing includes the valve opening spacing and the valve pressure difference spacing. The valve opening spacing is selected as 2.5 degrees, and the valve pressure difference spacing is selected as 25000Pa. For different types of valves, the values ​​of these parameters are not fixed and should be selected and adjusted as needed according to actual conditions;

[0055] S21, fix the valve pressure difference, and adjust the valve opening from small to large according to the selected independent variable interval;

[0056] S22. After the readings of the differential pressure transmitter and the recorder calibration flowmeter are stable, record the values ​​on the differential pressure transmitter and the recorder calibration flowmeter at each valve opening;

[0057] S23, increasing the valve pressure difference according to the selected independent variable interval, and repeating the above process until the valve pressure difference reaches the maximum value within the selected working range;

[0058] S3, fitting the coefficients of the flow function and the opening function according to the measured data in S2;

[0059] The specific formula of the flow function is as follows:

[0060] Q(x,y)=(a1+a2x+a3x 2 +…+a m+1 x m )(b1+b2y+b3y 2 +…+b n+1 y n );

[0061] Where x is the valve opening, y is the valve pressure difference, a1~a m+1 and b1~b n+1 are the coefficients obtained by fitting, m, n∈N, N is a set of positive integers, the specific formula of the flow function is not limited to this and can be adjusted as needed;

[0062] The specific formula of the opening function is as follows:

[0063] O(z,y)=(c1+c2z+c3z 2 +…+c j+1 z j )(d1+d2y+d3y 2 +…+d k+1 y k );

[0064] Where z is the valve flow, c1~c j+1 and d1~d k+1 are the coefficients obtained by fitting, j, k∈N, the specific formula of the opening function is not limited to this and can be adjusted as needed;

[0065] The coefficient fitting in S3 uses the Levenberg-Marquardt optimization algorithm to solve the nonlinear least squares problem and obtain the coefficients of the fitting function. The process is as follows:

[0066] S31. Construct a fitting function model:

[0067] z=f(x,y;β);

[0068] Among them, β = [β1, β2, β3,...,β M ] T is the coefficient matrix of the fitting function to be solved, T is the transpose symbol of the matrix, β1~β M is an element in the coefficient matrix, M∈N, x and y are the two independent variables of the fitting function, and z is the dependent variable of the fitting function;

[0069] S32. Determine the optimization objective function. The optimization objective is to minimize the residual sum of squares. The residual sum of squares S(β) is as follows:

[0070]

[0071] Among them, f(x i ,y i ; β) is the known data x i 、y i Substitute the calculated value obtained by the fitting formula, z i is the i-th known data of the dependent variable z, x i is the i-th known data of the independent variable x, y i is the i-th known data of the independent variable y, i∈N;

[0072] Then the residual vector r(β) is expressed as:

[0073] r(β)=[r1,r2,r3,...,r t ] T ;

[0074] where r i =z i -f(x i ,y i ;β),t∈N;

[0075] S33, initializing the algorithm and coefficient matrix β;

[0076] S34, using the Levenberg-Marquardt optimization algorithm to iterate until the termination condition is met, and the coefficient matrix β is obtained to obtain the complete fitting function;

[0077] S35. For the kth iteration, the core iteration formula of the Levenberg-Marquardt optimization algorithm is expressed as:

[0078]

[0079] Among them, μ k is the damping factor, D k is the scaling matrix, r k is the residual vector, J k is the Jacobian matrix of the residual, δ k is the parameter increment to be solved in the iterative process;

[0080] S4. Based on the flow function obtained by fitting in S3, the flow value of the valve can be calculated from any set of instantaneous valve opening and valve pressure difference data in practice;

[0081] S5. Based on the opening function obtained by fitting in S3, the corresponding valve opening can be calculated from any set of valve pressure difference and flow values ​​in practice.

[0082] Therefore, the present invention adopts the above-mentioned content as a flow calculation method for high-precision intelligent measurement and control valves under multi-parameter coordinated control. It addresses the defects of traditional differential pressure flow calculation methods, such as many limitations when used and difficulty in calculating the flow and opening under multi-parameter coordinated control of intelligent measurement and control valves. It breaks through the limitations of pipeline geometric parameters and has a wider applicability. The intelligent measurement and control valve based on this calculation method can simplify the hardware structure design, achieve lightweight equipment while ensuring control accuracy, thereby achieving the dual goals of reducing construction and operation production costs and improving system efficiency.

[0083] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit the same. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solutions of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A flow calculation method for high-precision intelligent measurement and control valves under multi-parameter coordinated control, characterized by: The following steps are involved: S1. Build a valve flow test experimental platform; S2. Select the valve pressure difference, valve opening working range and appropriate independent variable spacing to carry out flow test experiment; S3, fitting the coefficients of the flow function and the opening function according to the measured data in S2; S4. Based on the flow function obtained by fitting in S3, the flow value of the valve can be calculated from any set of instantaneous valve opening and valve pressure difference data in practice; S5. Based on the opening function obtained by fitting in S3, the corresponding valve opening can be calculated from any set of valve pressure difference and flow values ​​in practice.

2. The flow calculation method for high-precision intelligent measurement and control valve under multi-parameter coordinated regulation according to claim 1 is characterized by: The specific process in S1 is as follows: S11. Install an actuator on the valve in the constructed valve flow test experimental platform; S12. Install differential pressure transmitters at two pressure measuring points located before and after the valve; S13. Install a recording and calibrated flow meter upstream of the valve.

3. The flow calculation method for high-precision intelligent measurement and control valve under multi-parameter coordinated control according to claim 2 is characterized by: The specific process in S2 is as follows: S21, fix the valve pressure difference, and adjust the valve opening from small to large according to the selected independent variable interval; S22. After the readings of the differential pressure transmitter and the recorder calibration flowmeter are stable, record the values ​​on the differential pressure transmitter and the recorder calibration flowmeter at each valve opening; S23. Increase the valve pressure difference according to the selected independent variable interval, and repeat the above process until the valve pressure difference reaches the maximum value within the selected working range.

4. The flow calculation method for high-precision intelligent measurement and control valve under multi-parameter coordinated regulation according to claim 3 is characterized by: The working range of valve opening in S2 is set to 0-70 degrees, and the working range of valve pressure difference is set to 0-200000Pa. The independent variable spacing includes valve opening spacing and valve pressure difference spacing. The valve opening spacing is selected as 2.5 degrees, and the valve pressure difference spacing is selected as 25000Pa.

5. The flow calculation method for high-precision intelligent measurement and control valve under multi-parameter coordinated regulation according to claim 4 is characterized in that: The specific formula of the traffic function in S3 is as follows: <h2 style=";text-align:left;direction:ltr">Q(x,y)=(a1+a2x+a3x<h2 style=";text-align:left;direction:ltr"> 2 <h2 style=";text-align:left;direction:ltr"> +…+a<h2 style=";text-align:left;direction:ltr"> m+1 <h2 style=";text-align:left;direction:ltr"> x<h2 style=";text-align:left;direction:ltr"> m <h2 style=";text-align:left;direction:ltr"> b1+b2y+b3y<h2 style=";text-align:left;direction:ltr"> 2 <h2 style=";text-align:left;direction:ltr"> +…+b<h2 style=";text-align:left;direction:ltr"> n+1 <h2 style=";text-align:left;direction:ltr"> y<h2 style=";text-align:left;direction:ltr"> n <h2 style=";text-align:left;direction:ltr"> ); Where x is the valve opening, y is the valve pressure difference, a1~a m+1 and b1~b n+1 are the coefficients obtained by fitting, m,n∈N, and N is a set of positive integers.

6. The flow calculation method for high-precision intelligent measurement and control valve under multi-parameter coordinated regulation according to claim 5 is characterized in that: The specific formula of the opening function in S3 is as follows: O(z,y)=(c1+c2z+c3z 2 +…+c j+1 z j )(d1+d2y+d3y 2 +…+d k+1 y k ); Where z is the valve flow, c1~c j+1 and d1~d k+1 are the coefficients obtained by fitting, j, k∈.

7. The flow calculation method for high-precision intelligent measurement and control valve under multi-parameter coordinated regulation according to claim 6 is characterized in that: The coefficient fitting in S3 uses the Levenberg-Marquardt optimization algorithm to solve the nonlinear least squares problem and obtain the coefficients of the fitting function. The process is as follows: S31. Construct a fitting function model: z=f(x,y;β); Among them, β = [β1, β2, β3,...,β M ] T is the coefficient matrix of the fitting function to be solved, T is the transpose symbol of the matrix, β1~β M is an element in the coefficient matrix, M∈N, x and y are the two independent variables of the fitting function, and z is the dependent variable of the fitting function; S32. Determine the optimization objective function. The optimization objective is to minimize the residual sum of squares. The residual sum of squares S(β) is as follows: Among them, f(x i ,y i ; β) is the known data x i 、y i Substitute the calculated value obtained by fitting formula, z i is the i-th known data of the dependent variable z, x i is the i-th known data of the independent variable x, y i is the i-th known data of the independent variable y, i∈N; Then the residual vector r(β) is expressed as: r(β)＝[r1,r2,r3,...,r t ] T ； among them i =z i -f(x i ,y i ;b),t∈N; S33, initializing the algorithm and coefficient matrix β; S34, using the Levenberg-Marquardt optimization algorithm to iterate until the termination condition is met, and the coefficient matrix β is obtained to obtain the complete fitting function; S35. For the kth iteration, the core iteration formula of the Levenberg-Marquardt optimization algorithm is expressed as: Among them, μ k is the damping factor, D k is the scaling matrix, r k is the residual vector, J k is the Jacobian matrix of the residual, δ k is the parameter increment to be solved in the iterative process.

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