Adjusting method of flow adjusting valve for Christmas tree

Abstract

The invention discloses an adjusting method of a flow adjusting valve for a Christmas tree. The adjusting method comprises the following steps that 110, the flow error value and the flow error change rate of the flow adjusting valve are collected; 120, the flow error value and the flow error change rate are input into a fuzzy PID controller, and the flow control quantity is output; the method specifically comprises the following steps: S121, defining fuzzy distribution of an input quantity and an output quantity; s122, establishing a fuzzy rule, and finding a corresponding fuzzy rule according to the fuzzy subset; s123, through defuzzification processing, the output fuzzy quantity is converted into a clear value; s124, through defuzzification processing, the output fuzzy quantity is converted into a clear value; and 130, the opening degree of the needle valve is adjusted through a driving motor according to the flow control quantity, and therefore the flow is controlled.

Description

Technical Field

[0001] The invention relates to a flow valve, in particular to a method for regulating a flow regulating valve for a Christmas tree. Background Art

[0002] The Christmas tree is one of the important equipment in offshore oil drilling operations, used to control the flow and pressure of the wellhead fluid. During the oil production process, in order to ensure the stable flow and pressure of the chemical reagents in the Christmas tree, a flow control valve is required for regulation.

[0003] The flow control valve for oil production usually adopts a needle valve structure, which has the advantages of simple structure, fast response, high adjustment accuracy, etc., and is therefore widely used in the field of Christmas trees. For example, in patent application CN107035335A, the structural composition of the subsea injection metering valve device is introduced, which includes a needle valve flow control valve, but the adjustment principle and method of the flow control valve are not elaborated in detail. In actual use, due to the complex environment and large parameter changes at the oil production site, it is difficult to accurately adjust the flow. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a method for controlling the system in real time to realize adaptive adjustment of the flow control valve for the Christmas tree.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is: a method for regulating a flow regulating valve for a Christmas tree, wherein the flow regulating valve comprises a valve housing, a liquid inlet hole is arranged on the valve housing, a valve seat is arranged at one end of the valve housing, a valve body is arranged at the other end of the valve housing, a valve hole is arranged through the valve body, a liquid outlet pipe is arranged at one end of the valve body away from the valve housing, a liquid inlet groove is arranged on the side of the valve seat close to the valve body, a plurality of liquid holes are arranged on the groove wall of the liquid inlet groove on the valve seat, which are in communication with the inner cavity of the valve housing, a valve stem is arranged through the valve seat, and a valve stem is arranged on the valve stem, which is in communication with the inlet hole. The boss part matched with the liquid tank wall, the end of the valve stem passing through the valve hole is conical, and the end of the valve stem passing through the valve seat is provided with an end sealing device; the valve housing is provided with an annular connecting seat, the annular connecting seat is provided with a mounting seat, the mounting seat is provided with a sliding block moving parallel to the valve stem, the sliding block is provided with a driving rack, the end of the driving rack is provided with a valve needle connecting block, the valve needle connecting block is connected to the end of the valve stem passing through the valve seat, the mounting seat is provided with a driving motor, and the output shaft of the driving motor is provided with a driving gear meshing with the driving rack;

[0006] The flow regulating method of the flow regulating valve comprises the following steps:

[0007] Step 110: Collect the flow error value and flow error change rate of the flow control valve;

[0008] Step 120: Input the flow error value and the flow error change rate into the fuzzy PID controller and output the flow control amount; the details are as follows:

[0009] S121: Determine the fuzzy controller structure and use the differential algorithm to improve the fuzzy PID controller;

[0010] The fuzzy PID controller structure satisfies the basic formula of fuzzy PID control:

[0011] E(t)=r(t)-y(t)

[0012]

[0013] Wherein, r(t) represents the flow setting value of the flow control valve, y(t) represents the flow measured value of the flow control valve, e(t) represents the error between the flow setting value and the flow measured value, i.e., the flow error value e, de(t) / dt represents the flow error change rate ec, u(t) represents the output of the fuzzy PID controller, i.e., the valve control amount, Kp, Ki, and Kd represent the proportional coefficient setting value, the integral coefficient setting value, and the differential coefficient setting value, respectively;

[0014] The differential optimization algorithm is used to optimize the parameters of the fuzzy PID. The steps are as follows:

[0015] A1 Initialize the population: randomly generate the initial population, each individual represents a potential solution to the problem;

[0016] A2 mutation operation: For each individual, randomly select three other individuals and use the linear combination of these three individuals to create a new individual, that is, perform a mutation operation. The mutation operation can be expressed by the following formula:

[0017] h mn (t+1)=x p1n (t)+F(x p2n (t)-x p3n (t))

[0018] Among them, h mn (t+1) represents the variant individual of the nth individual in the t+1th generation, x p1 ,x p2 ,x p3 are three different population individuals, and function F is the scaling factor;

[0019] A3 Crossover operation: Cross the variant individuals with the original individuals to generate test individuals;

[0020] A4 selection operation: For each test individual, decide whether to accept the replacement by comparing its fitness value with the fitness value of the original individual;

[0021] A5 determines the stopping condition: repeat the mutation, crossover and selection operations until Kp, Ki and Kd converge to the minimum value;

[0022] S122: define fuzzy distribution of input and output quantities;

[0023] S123: Establish fuzzy rules and find corresponding fuzzy rules according to fuzzy subsets;

[0024] S124: Convert the output fuzzy value into a clear value through defuzzification processing:

[0025] Step 130: adjusting the opening of the needle valve by driving the motor according to the flow control amount, thereby controlling the flow.

[0026] Furthermore, in step 110, the flow rate of the flow control valve is monitored in real time by an ultrasonic flow meter, and the flow value is recorded, so as to determine the flow error value and the flow error change rate.

[0027] Furthermore, in step S122, the range of the input quantities e, ec and the output quantities ΔKp, ΔKi, ΔKd is defined as the domain [-6, 6], and a seven-level fuzzy subset {NB, NM, NS, ZO, PS, PM, PB} is selected, where N represents negative, P represents positive, B represents large, M represents medium, S represents small, and ZO represents 0;

[0028] Furthermore, in the step S123, according to the preset fuzzy subsets, a triangle membership function is used to divide the values ​​on the standard domain into the fuzzy subsets.

[0029] Further, as described in step 124, the fuzzy controller defuzzifies the fuzzy value of the PID coefficient and outputs the PID coefficient adjustment value; when making fuzzy subset decisions, the centroid method is used to perform actual domain mapping to map the adjustment value of the PID coefficient to the actual domain; the PID coefficient setting value is obtained according to the following formula:

[0030]

[0031] Among them, K p0 , K i0 , K d0 They respectively represent the preset value of the proportional coefficient, the preset value of the integral coefficient and the preset value of the differential coefficient, ΔKp, ΔKi, ΔKd respectively represent the adjustment value of the proportional coefficient, the adjustment value of the integral coefficient and the adjustment value of the differential coefficient, Kp, Ki, Kd respectively represent the setting value of the proportional coefficient, the setting value of the integral coefficient and the setting value of the differential coefficient.

[0032] The beneficial effects of the present invention are:

[0033] 1. Improve flow regulation stability: The fuzzy PID regulation method based on differential algorithm realizes adaptive regulation of the system through fuzzy logic control and differential algorithm. It can maintain good control performance in the face of uncertain and nonlinear working conditions and improve stability and reliability in the working process.

[0034] 2. Stronger adaptability and convergence: The fuzzy PID controller based on the differential optimization algorithm can find the optimal parameter combination through global search, thereby improving the convergence performance of the controller. Traditional fuzzy PID control may be limited by the subjectivity and limitations of manual parameter adjustment, while the differential optimization algorithm can adjust the parameters more accurately to achieve better control effects.

[0035] 3. Since the valve core of the flow control valve adopts the needle valve form, the structure is simple, and the valve has a multi-hole valve cavity, it can work stably in a high-pressure environment. And the needle valve flow control valve has high control accuracy, which can accurately adjust the flow in the oil production process and improve production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 This is the structure diagram of the needle valve type flow control valve;

[0037] Figure 2 It is a cross-sectional view of a needle valve type flow control valve;

[0038] Figure 3 It is the valve needle structure diagram;

[0039] Figure 4 It is a flow control method step diagram;

[0040] Figure 5 This is the fuzzy PID control principle diagram;

[0041] Figure 6 This is a comparison chart between fuzzy PID and traditional PID;

[0042] Figure 1 In the middle: 100, valve housing, 101, annular connecting portion, 102, annular connecting seat, 103 driving motor;

[0043] Figure 2 In the figure: 200, valve needle, 201, valve seat, 202, driving rack, 203, driving gear, 204, valve needle connecting block. DETAILED DESCRIPTION

[0044] The specific embodiments of the present invention are described in detail below in conjunction with the accompanying drawings.

[0045] like Figure 1-2As shown, a method for regulating a flow regulating valve for a Christmas tree, wherein the flow regulating valve comprises a valve housing 100, the valve housing 100 is provided with a liquid inlet hole, one end of the valve housing 100 is provided with a valve seat 201, the other end of the valve housing 100 is provided with a valve body, the valve body is provided with a penetrating valve hole, the end of the valve body away from the valve housing 100 is provided with a liquid outlet pipe, a liquid inlet groove is provided on the side of the valve seat 201 close to the valve body, a plurality of liquid holes that are connected with the inner cavity of the valve housing 100 are provided on the groove wall of the liquid inlet groove on the valve seat 201, a valve stem is passed through the valve seat 201, a boss portion that matches with the wall of the liquid inlet groove is provided on the valve stem, and the end of the valve stem that penetrates the valve hole is conical; An end sealing device is provided at the end through which the valve stem passes; an annular connecting portion 101 is provided on the valve housing 100, an annular connecting seat 102 is provided on the annular connecting portion 101, a mounting seat is provided on the annular connecting seat 102, a sliding block which moves parallel to the valve stem is provided on the mounting seat, a driving rack 202 is provided on the sliding block, a valve needle connecting block 204 is provided at the end of the driving rack 202, the valve needle connecting block 204 is connected to the end of the valve stem passing through the valve seat 201, a driving motor 103 (a brushless DC motor is used in this embodiment) is provided on the mounting seat, and a driving gear 203 meshing with the driving rack 202 is provided on the output shaft of the driving motor 103.

[0046] like Figure 3 As shown, the needle valve flow control valve in the present invention has a linear flow characteristic, which means that there is a linear relationship between the valve opening and the flow. The flow Q of the needle valve flow control valve and the valve opening n can be described by the following linear relationship:

[0047] Q=K·n#(1)

[0048] Wherein, K is a constant, indicating the flow coefficient of the valve, and in the present invention, the value of K is set to 50. The flow of the valve is proportional to the opening of the valve. When the valve is fully closed, the flow is zero; when the valve is fully opened, the flow reaches the maximum value.

[0049] For simple cases, the flow rate Q can be calculated by multiplying the flow area S and the flow velocity V:

[0050] Q=SV#(2)

[0051] The needle valve flow control valve changes the flow area S by adjusting the position of the valve core in the valve seat 201, thereby controlling the fluid flow through the valve. The following formula can be derived based on the cone relationship:

[0052]

[0053] Where r is the cone radius of the needle valve in the valve seat 201, R is the radius of the valve seat 201, and the radius of the valve seat 201 is 15 mm. h is the needle valve travel, H is the needle valve height, and the needle valve height is 37 mm.

[0054] The fluid area is:

[0055]

[0056] The needle valve flow control valve is driven by a motor. A gear is installed at one end of the motor, which meshes with the rack connected to the needle valve. Therefore, the travel h of the valve needle 200 is related to the rotation angle of the motor. The formula is:

[0057] D1=m(Z+2)#(5)

[0058]

[0059] Where D1 is the diameter of the tooth tip circle, m is the gear module, Z is the number of teeth, and n is the motor rotation angle. This study uses a wireless DC motor with a module m of 1.5 and a number of teeth of 14.

[0060] According to the above formula, we can get:

[0061]

[0062] According to the above formula, the transfer function of the needle valve flow control valve is:

[0063]

[0064] like Figure 4 As shown, the flow control method of the flow control valve comprises the following steps:

[0065] Step 110: Collect the flow error value and flow error change rate of the flow control valve: monitor the flow of the flow control valve in real time through an ultrasonic flow meter, record the flow value, and thus determine the flow error value and flow error change rate.

[0066] Step 120: Input the flow error value and the flow error change rate into the fuzzy PID controller, and output the flow control amount;

[0067] The details are as follows:

[0068] S121: Determine the fuzzy controller structure and use the differential algorithm to improve the fuzzy PID controller;

[0069] like Figure 5 As shown in the figure, the difference algorithm is used to improve the fuzzy PID controller structure to meet the basic formula of fuzzy PID control:

[0070] E(t)=r(t)-y(t)#(9)

[0071]

[0072] Wherein, r(t) represents the flow setting value of the flow control valve, y(t) represents the actual flow value of the flow control valve, e(t) represents the error between the flow setting value and the actual flow value, that is, the flow error value e, de(t) / dt represents the flow error change rate ec, u(t) represents the output of the fuzzy PID controller, that is, the valve control quantity, Kp, Ki, and Kd represent the proportional coefficient setting value, the integral coefficient setting value, and the differential coefficient setting value, respectively.

[0073] The fuzzy PID controller combines the characteristics of the classic PID controller and fuzzy control. It can overcome the limitations of the traditional PID controller in nonlinear and time-varying systems. At the same time, it uses the differential optimization algorithm to optimize the parameters of the fuzzy PID and improve the control performance.

[0074] like Figure 6 The figure shows the flow chart of the differential optimization algorithm, which is a global optimization algorithm based on group search. Its working principle is to simulate the evolution process of biological individuals in nature, and gradually optimize the fitness of individuals through continuous iteration to find the optimal solution of Kp, Ki, and Kd. The differential optimization algorithm is used to optimize the parameters of the fuzzy PID. The steps are as follows:

[0075] A1 Initialize the population: randomly generate the initial population, each individual represents a potential solution to the problem;

[0076] A2 mutation operation: For each individual, randomly select three other individuals and use the linear combination of these three individuals to create a new individual, that is, perform a mutation operation. The mutation operation can be expressed by the following formula:

[0077] h mn (t+1)=x p1n (t)+F(x p2n (t)-x p3n (t))#(11)

[0078] Among them, h mn (t+1) represents the variant individual of the nth individual in the t+1th generation, x p1 ,x p2 ,x p3 are three different population individuals, and function F is the scaling factor;

[0079] A3 Crossover operation: Cross the variant individuals with the original individuals to generate test individuals;

[0080] A4 selection operation: For each test individual, decide whether to accept the replacement by comparing its fitness value with the fitness value of the original individual;

[0081] A5 determines the stopping condition: repeat the mutation, crossover and selection operations until Kp, Ki and Kd converge to the minimum value;

[0082] S122: Define the fuzzy distribution of input and output quantities; define the range of input e, ec and output ΔKp, ΔKi, ΔKd as the domain [-6,6], and select the seven-level fuzzy subset {NB, NM, NS, ZO, PS, PM, PB}, where N represents negative, P represents positive, B represents large, M represents medium, S represents small, and ZO represents 0.

[0083] S123: Establish fuzzy rules, and find corresponding fuzzy rules according to fuzzy subsets; according to preset fuzzy subsets, use a triangle membership function to divide the values ​​on the standard domain into the fuzzy subsets.

[0084] S124: Through defuzzification processing, the output fuzzy value is converted into a clear value:

[0085] The fuzzy controller defuzzifies the fuzzy quantity of the PID coefficient and outputs the PID coefficient adjustment value; when making fuzzy subset decisions, the centroid method is used to map the actual domain to map the adjustment value of the PID coefficient to the actual domain; the PID coefficient setting value is obtained according to the following formula:

[0086]

[0087] Among them, K p0 , K i0 , K d0 They represent the preset value of proportional coefficient, the preset value of integral coefficient and the preset value of differential coefficient respectively, ΔKp, ΔKi and ΔKd represent the adjustment value of proportional coefficient, the adjustment value of integral coefficient and the adjustment value of differential coefficient respectively, Kp, Ki and Kd represent the setting value of proportional coefficient, the setting value of integral coefficient and the setting value of differential coefficient respectively;

[0088] Step 130: adjusting the needle valve opening by driving the motor 103 according to the flow control amount, thereby controlling the flow.

[0089] like Figure 6 As shown in the figure, the fuzzy PID controller is simulated in Simulink according to formula 8, the input flow is set to 10, and finally the flow regulation effect diagram is generated. When PID regulation is adopted, the overshoot is 1.74, the negative regulation is 0.12, and the regulation time is 28.02s. However, when the fuzzy PID algorithm is used for control, there is no overshoot, and the system regulation time is 2.29s. By comparison, the fuzzy PID controller has almost no overshoot phenomenon, fast response speed, and better stability and regulation effect than the traditional PID controller. Therefore, the fuzzy PID controller is more superior and suitable for the field of needle valve flow control valves.

[0090] The above-mentioned embodiments are only illustrative of the principles and effects of the invention, as well as some embodiments of its application, and are not intended to limit the invention. It should be pointed out that a person skilled in the art can make several modifications and improvements without departing from the inventive concept of the invention, and all of these belong to the protection scope of the invention.

Claims

1. A method for regulating a flow regulating valve for a Christmas tree, wherein the flow regulating valve comprises a valve housing, a liquid inlet hole is arranged on the valve housing, a valve seat is arranged at one end of the valve housing, a valve body is arranged at the other end of the valve housing, a valve hole is arranged through the valve body, a liquid outlet pipe is arranged at one end of the valve body away from the valve housing, a liquid inlet groove is arranged on the side of the valve seat close to the valve body, a plurality of liquid holes are arranged on the groove wall of the liquid inlet groove on the valve seat and are connected with the inner cavity of the valve housing, a valve stem is arranged through the valve seat, a boss portion is arranged on the valve stem and matches with the wall of the liquid inlet groove, and the end of the valve stem is inserted into the valve hole The valve seat is conical in shape, and an end sealing device is provided at the end of the valve stem passing through the valve seat; an annular connecting seat is provided on the valve housing, a mounting seat is provided on the annular connecting seat, a sliding block moving parallel to the valve stem is provided on the mounting seat, a driving rack is provided on the sliding block, a valve needle connecting block is provided at the end of the driving rack, the valve needle connecting block is connected to the end of the valve stem passing through the valve seat, a driving motor is provided on the mounting seat, and a driving gear meshing with the driving rack is provided on the output shaft of the driving motor; a flow control method of a flow control valve, comprising the following steps: Step 110: Collect the flow error value and flow error change rate of the flow control valve; Step 120: Input the flow error value and the flow error change rate into the fuzzy PID controller and output the flow control amount; the details are as follows: S121: Determine the fuzzy controller structure and use the differential algorithm to improve the fuzzy PID controller; The fuzzy PID controller structure satisfies the basic formula of fuzzy PID control: E(t)=r(t)-y(t) Wherein, r(t) represents the flow setting value of the flow control valve, y(t) represents the flow measured value of the flow control valve, e(t) represents the error between the flow setting value and the flow measured value, i.e., the flow error value e, de(t) / dt represents the flow error change rate ec, u(t) represents the output of the fuzzy PID controller, i.e., the valve control amount, Kp, Ki, and Kd represent the proportional coefficient setting value, the integral coefficient setting value, and the differential coefficient setting value, respectively; The differential optimization algorithm is used to optimize the parameters of the fuzzy PID. The steps are as follows: A1 Initialize the population: randomly generate the initial population, each individual represents a potential solution to the problem; A2 Mutation operation: For each individual, randomly select three other individuals and use the linear combination of these three individuals to create a new individual, that is, perform a mutation operation; the mutation operation can be expressed by the following formula: h mn (t+1)=x p1n (t)+F(x p2n (t)-x p3n (t)) Among them, h mn (t+1) represents the variant individual of the nth individual in the t+1th generation, x p1 ,x p2 ,x p3 are three different population individuals, and function F is the scaling factor; A3 Crossover operation: Cross the variant individuals with the original individuals to generate test individuals; A4 selection operation: For each test individual, decide whether to accept the replacement by comparing its fitness value with the fitness value of the original individual; A5 determines the stopping condition: repeat the mutation, crossover and selection operations until Kp, Ki and Kd converge to the minimum value; S122: define fuzzy distribution of input and output quantities; S123: Establish fuzzy rules and find corresponding fuzzy rules according to fuzzy subsets; S124: Through defuzzification processing, the output fuzzy value is converted into a clear value: Step 130: adjusting the opening of the needle valve by driving the motor according to the flow control amount, thereby controlling the flow.

2. The method for adjusting a flow control valve for a Christmas tree according to claim 1, characterized in that: In step 110, the flow rate of the flow control valve is monitored in real time by an ultrasonic flow meter, and the flow value is recorded, so as to determine the flow error value and the flow error change rate.

3. The method for adjusting a flow control valve for a Christmas tree according to claim 1, characterized in that: In step S122, the range of the input quantities e, ec and the output quantities ΔKp, ΔKi, ΔKd is defined as the domain [-6, 6], and a seven-level fuzzy subset {NB, NM, NS, ZO, PS, PM, PB} is selected, where N represents negative, P represents positive, B represents large, M represents medium, S represents small, and ZO represents 0.

4. The method for adjusting a flow control valve for a Christmas tree according to claim 1, characterized in that: In the step S123, according to the preset fuzzy subsets, the values ​​on the standard domain are divided into the fuzzy subsets using a triangular membership function.

5. The method for adjusting a flow control valve for a Christmas tree according to claim 1, characterized in that: As described in step 124, the fuzzy controller defuzzifies the fuzzy value of the PID coefficient and outputs the PID coefficient adjustment value; when making fuzzy subset decisions, the centroid method is used to perform actual domain mapping to map the adjustment value of the PID coefficient to the actual domain; The PID coefficient setting value is obtained according to the following formula: Among them, K p0 , K i0 , K d0 They respectively represent the preset value of the proportional coefficient, the preset value of the integral coefficient and the preset value of the differential coefficient, ΔKp, ΔKi, ΔKd respectively represent the adjustment value of the proportional coefficient, the adjustment value of the integral coefficient and the adjustment value of the differential coefficient, Kp, Ki, Kd respectively represent the setting value of the proportional coefficient, the setting value of the integral coefficient and the setting value of the differential coefficient.

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