Intelligent ball valve control system

Abstract

The invention discloses an intelligent ball valve control system, which comprises an acquisition module, a control module and a control module, the first determining module is used for determining a control scheme of the ball valve according to the demand information; the generation module is used for generating a control signal of the ball valve according to the control scheme; and the execution module is used for executing the control signal. The corresponding control scheme is determined according to the input demand information, the control flexibility is improved, meanwhile, comprehensive remote real-time monitoring and precise control functions can be conveniently achieved, and the adaptability and working efficiency of the ball valve under the complex working condition are improved.

Description

Technical Field

[0001] The invention relates to the field of control technology, and in particular to an intelligent ball valve control system. Background Art

[0002] At present, ball valves, as a widely used fluid control component, play an important role in many fields such as petroleum, chemical industry, water treatment, etc. However, traditional ball valve control systems cannot determine the corresponding control scheme based on the input demand information, and the control lacks flexibility. At the same time, it is difficult to achieve comprehensive remote real-time monitoring and precise control functions, which greatly limits its adaptability and work efficiency under complex working conditions. Summary of the invention

[0003] The present invention aims to solve at least one of the technical problems in the above-mentioned technology to a certain extent. To this end, the purpose of the present invention is to propose an intelligent ball valve control system, which determines the corresponding control scheme according to the input demand information, improves the flexibility of control, and facilitates the realization of comprehensive remote real-time monitoring and precise control functions, thereby improving the adaptability and working efficiency of the ball valve under complex working conditions.

[0004] To achieve the above object, the embodiment of the present invention provides an intelligent ball valve control system, including:

[0005] An acquisition module is used to obtain demand information for ball valve control;

[0006] A first determination module, used to determine a control scheme of the ball valve according to the demand information;

[0007] A generating module, used for generating a control signal of the ball valve according to a control scheme;

[0008] An execution module is used to execute the control signal.

[0009] According to some embodiments of the present invention, the first determining module includes:

[0010] A storage module, used to store a number of pieces of historical demand information after numerical processing; the historical demand information includes historical demand characteristics, and the historical demand characteristics include flow characteristics, medium characteristics, pressure changes, temperature changes, pressure control, temperature control and flow control;

[0011] A first calculation module is used to determine the demand characteristics of the demand information and calculate the matching degree between the demand characteristics and the historical demand characteristics included in the plurality of historical demand information;

[0012]

[0013] Among them, M qis the matching degree between the demand feature and the historical demand feature included in the qth historical demand information; s is the value of the sth sub-demand feature of the demand feature; P t,s is the value of the s-th sub-historical demand feature of the historical demand feature included in the t-th historical demand information; X d is the value of the d-th sub-demand feature of the demand feature; P t,d is the value of the d-th sub-historical demand feature of the historical demand feature included in the t-th historical demand information; M q,d is the value of the d-th sub-historical demand feature of the historical demand feature included in the q-th historical demand information; η is the preset discrimination coefficient, and η∈[0,1], t=1, 2, 3…L,, s=1, 2, 3…N, q=1, 2, 3…L, d=1, 2, 3…N, N is the number of sub-demand features included in the demand feature, and is also the number of sub-historical demand features included in the historical demand feature, and the two are equal; L is the number of historical demand information;

[0014] The historical control scheme corresponding to the historical demand information with the greatest matching degree is used as the control scheme of the ball valve.

[0015] According to some embodiments of the present invention, the generating module is used to generate a control signal for the ball valve according to a control scheme based on a pre-built fuzzy PID controller.

[0016] According to some embodiments of the present invention, the generating module comprises:

[0017] Establish a module for establishing the mathematical model of the ball valve control system and initializing the fuzzy PID controller parameters;

[0018] The second determination module is used to determine the input and output of the fuzzy PID controller based on the fuzzy set, determine the output adjustment strategy based on the pre-rule base, and set the membership function of each fuzzy set;

[0019] The optimization module is used to optimize the fuzzy PID controller based on the seeker optimization algorithm as an optimization tool to obtain an optimized fuzzy PID controller.

[0020] According to some embodiments of the present invention, the establishing module includes:

[0021] Description module, used to: determine the dynamic and static characteristics of the ball valve based on experimental data and system characteristics analysis, including flow-pressure relationship, response time, and hysteresis effect;

[0022] A mathematical model is used to describe the behavior of the ball valve based on its dynamic and static characteristics;

[0023] Setup module for:

[0024] Set the initial proportional, integral and derivative gains of the fuzzy PID controller;

[0025] Define the input and output variables of the fuzzy PID controller and the corresponding fuzzy sets and rules;

[0026] Sets the input range for converting actual input values ​​to the fuzzy logic system, and converting the output values ​​of the fuzzy logic system back to the input range of the actual controller.

[0027] According to some embodiments of the present invention, it also includes: an alarm module, which is used to calculate the absolute value of the difference between the target valve position value and the real-time valve position value of the ball valve after the execution module executes the control signal, and issue an alarm prompt when it is determined that the absolute value is greater than a preset threshold.

[0028] According to some embodiments of the present invention, the execution module includes a position PID controller and a current PID controller.

[0029] According to some embodiments of the present invention, the method further includes: a detection module, which is used to detect a characteristic vector of the control signal during the process of the execution module executing the control signal, and to issue an alarm prompt when an abnormality is determined based on the characteristic vector.

[0030] According to some embodiments of the present invention, the detection module includes:

[0031] The acquisition module is used to acquire the input control signals within a preset period of time at a preset time interval and save them in chronological order as a control signal vector M;

[0032] Determine the fluctuation characteristic BM of the control signal vector M;

[0033] BM i =M i+1 -M i

[0034]

[0035] Among them, BM i is the ith value of the fluctuation characteristic BM, M i+1 is the i+1th value of the control signal vector M, M i is the i-th value of the control signal vector M, BM + is the positive fluctuation value, BM - is the negative fluctuation value, lengh(BM>0) is the number of elements in the fluctuation feature BM whose values ​​are greater than 0, lengh(BM<0) is the number of elements in the fluctuation feature BM whose values ​​are less than 0, i=1, 2, 3…N; N is the number of input control signals collected;

[0036] Calculate the fluctuation frequency of the fluctuation feature BM;

[0037] T=|find1(BM i *BM i+1 ≤0)-find2(BM i *BM i+1 ≤0)|*t*2

[0038] Where T is the fluctuation frequency, find1() is the position corresponding to the first occurrence of the fluctuation feature BM that meets the conditions in brackets, and BM i *BM i+1 ≤0 means that the value of the current position of the fluctuation feature BM multiplied by the value of the next position is less than or equal to 0, find2() is the corresponding position when the fluctuation vector BM appears for the second time to meet the conditions in the brackets, and t is the preset time interval;

[0039] determining a characteristic vector of a control signal;

[0040]

[0041] Among them, XM is the characteristic vector of the control signal; max(P + ) is the maximum value of the preset positive fluctuation value, max(P - ) is the maximum value of the preset negative fluctuation value, and max(PT) is the maximum value of the preset fluctuation frequency;

[0042] The matching module is used to match the characteristic vector of the control signal with the preset characteristic vector of the disturbed control signal, and when a match is determined, an abnormality is determined and an alarm is issued.

[0043] According to some embodiments of the present invention, the matching module includes:

[0044] The third determination module is used to determine that the preset characteristic vector of the interfered control signal is:

[0045]

[0046] Wherein, XP is the preset characteristic vector of the disturbed control signal; XP + XP is the positive fluctuation value of the disturbed control signal. - is the negative fluctuation value of the disturbed control signal, T 0 is the fluctuation frequency of the disturbed control signal;

[0047] A second calculation module, used for calculating the difference between the characteristic vector of the control signal and the preset characteristic vector of the interfered control signal;

[0048]

[0049] Wherein, R is the difference between the characteristic vector of the control signal and the preset characteristic vector of the disturbed control signal; XM j is the jth value of the eigenvector of the control signal, XP j is the j-th value of the preset characteristic vector of the disturbed control signal;

[0050] When it is determined that the difference is less than the preset difference threshold, the feature vector representing the control signal matches the preset feature vector of the interfered control signal.

[0051] The present invention proposes an intelligent ball valve control system, which determines the corresponding control scheme according to the input demand information, improves the flexibility of control, and facilitates the realization of comprehensive remote real-time monitoring and precise control functions, thereby improving the adaptability and working efficiency of the ball valve under complex working conditions.

[0052] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0053] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0055] Figure 1 is a block diagram of an intelligent ball valve control system according to an embodiment of the present invention;

[0056] Figure 2 is a block diagram of a first determination module according to an embodiment of the present invention;

[0057] Figure 3 is a block diagram of a generation module according to an embodiment of the present invention. DETAILED DESCRIPTION

[0058] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0059] like Figure 1 As shown, the embodiment of the present invention proposes an intelligent ball valve control system, including:

[0060] An acquisition module is used to obtain demand information for ball valve control;

[0061] A first determination module, used to determine a control scheme of the ball valve according to the demand information;

[0062] A generating module, used for generating a control signal of the ball valve according to a control scheme;

[0063] An execution module is used to execute the control signal.

[0064] The working principle of the above technical solution is as follows: the acquisition module is responsible for collecting and acquiring demand information related to ball valve control. This information comes from various sensors, user input, preset parameters or other data sources. According to the demand information provided by the acquisition module, the first determination module is responsible for analyzing and determining the best ball valve control scheme. Once the control scheme is determined, the generation module will generate specific control signals according to this scheme. These signals exist in the form of electrical signals or digital signals, which are used to drive the ball valve to perform corresponding actions. The execution module is responsible for receiving and executing the control signal from the generation module. It directly controls the opening, closing or adjustment action of the ball valve, thereby realizing precise control of the fluid flow.

[0065] Beneficial effects of the above technical solution: The entire intelligent ball valve control system realizes intelligent control of the ball valve through the coordinated work of these four modules. This control method not only improves the accuracy and efficiency of control, but also reduces the need for manual intervention, thereby reducing operating costs and risks. The corresponding control scheme is determined according to the input demand information, which improves the flexibility of control and facilitates the realization of comprehensive remote real-time monitoring and precise control functions, thereby improving the adaptability and working efficiency of the ball valve under complex working conditions.

[0066] like Figure 2 As shown, according to some embodiments of the present invention, the first determining module includes:

[0067] A storage module, used to store a number of pieces of historical demand information after numerical processing; the historical demand information includes historical demand characteristics, and the historical demand characteristics include flow characteristics, medium characteristics, pressure changes, temperature changes, pressure control, temperature control and flow control;

[0068] A first calculation module is used to determine the demand characteristics of the demand information and calculate the matching degree between the demand characteristics and the historical demand characteristics included in the plurality of historical demand information;

[0069]

[0070] Among them, M q is the matching degree between the demand feature and the historical demand feature included in the qth historical demand information; s is the value of the sth sub-demand feature of the demand feature; P t,sis the value of the s-th sub-historical demand feature of the historical demand feature included in the t-th historical demand information; X d is the value of the d-th sub-demand feature of the demand feature; P t,d is the value of the d-th sub-historical demand feature of the historical demand feature included in the t-th historical demand information; M q,d is the value of the d-th sub-historical demand feature of the historical demand feature included in the q-th historical demand information; η is the preset discrimination coefficient, and η∈[0,1], t=1, 2, 3…L, s=1, 2, 3…N, q=1, 2, 3…L, d=1, 2, 3…N, N is the number of sub-demand features included in the demand feature, and is also the number of sub-historical demand features included in the historical demand feature, and the two are equal; L is the number of historical demand information;

[0071] The historical control scheme corresponding to the historical demand information with the greatest matching degree is used as the control scheme of the ball valve.

[0072] The working principle of the above technical solution is as follows: the storage module is responsible for storing a large amount of historical demand information, which has been processed numerically to facilitate rapid retrieval and matching by the computer. The historical demand information includes multiple historical demand characteristics, such as flow characteristics, medium characteristics, pressure changes, temperature changes, pressure control, temperature control and flow control. The storage module provides rich data support for the first calculation module, so that the system can formulate a more reasonable control scheme based on historical experience. The first calculation module is responsible for calculating the matching degree between the current demand information and the historical demand information in the storage module. By comparing the numerical differences between the two in multiple sub-demand characteristics, the matching degree is calculated to find the historical demand information most similar to the current demand. When calculating the matching degree between the demand characteristics and the historical demand characteristics included in several historical demand information, the differences of multiple sub-demand characteristics are comprehensively considered, and the discrimination coefficient η is introduced to balance the influence of different differences on the matching degree. The preset discrimination coefficient is used to adjust the weight in the matching degree calculation. After calculating the matching degree of all historical demand information, the first calculation module will select the historical control scheme corresponding to the historical demand information with the largest matching degree as the control scheme of the ball valve.

[0073] Beneficial effects of the above technical solution: Through the collaborative work of the storage module and the first calculation module, the intelligent ball valve control system can quickly and accurately determine the optimal control solution based on historical experience and current demand information. This control method not only improves the control accuracy and efficiency, but also enables the system to adaptively cope with various complex working conditions, thereby ensuring the stable operation of the ball valve and the overall performance of the system.

[0074] According to some embodiments of the present invention, the generating module is used to generate a control signal for the ball valve according to a control scheme based on a pre-built fuzzy PID controller.

[0075] Working principle of the above technical solution: Fuzzy PID controller is an advanced controller that combines fuzzy logic with traditional PID (proportional-integral-differential) control algorithm. The generation module parses the control scheme provided by the first determination module to obtain specific instructions on how the ball valve should act. The generation module inputs these instructions into the fuzzy PID controller. The fuzzy PID controller interprets and processes the input using fuzzy logic, and dynamically adjusts the PID parameters according to the real-time status of the system (such as flow, pressure, temperature, etc.) and the preset fuzzy rule set. After adjusting the PID parameters, the fuzzy PID controller applies the traditional PID control algorithm to calculate the control signal. This signal is designed to minimize the system error and make the action of the ball valve meet the requirements of the control scheme. Finally, the generation module outputs the calculated control signal to the execution module. The execution module converts the received signal into the actual action of the ball valve, thereby achieving precise control of the fluid flow.

[0076] The beneficial effect of the above technical solution is that the generation module can generate accurate control signals according to the control scheme by utilizing the pre-built fuzzy PID controller, thereby realizing intelligent control of the ball valve.

[0077] like Figure 3 As shown, according to some embodiments of the present invention, the generating module includes:

[0078] Establish a module for establishing the mathematical model of the ball valve control system and initializing the fuzzy PID controller parameters;

[0079] The second determination module is used to determine the input and output of the fuzzy PID controller based on the fuzzy set, determine the output adjustment strategy based on the pre-rule base, and set the membership function of each fuzzy set;

[0080] The optimization module is used to optimize the fuzzy PID controller based on the seeker optimization algorithm as an optimization tool to obtain an optimized fuzzy PID controller.

[0081] The working principle of the above technical solution is as follows: the establishment module is responsible for establishing the mathematical model of the ball valve control system, which is the basis for designing and optimizing the controller. The mathematical model should be able to accurately reflect the dynamic characteristics and control requirements of the ball valve. On the basis of establishing the mathematical model, the establishment module also needs to initialize the parameters of the fuzzy PID controller. These parameters include the initial values ​​of the proportional, integral and differential gains, as well as other parameters that may be involved in the fuzzy logic controller. The second determination module first determines the input and output of the fuzzy PID controller based on the fuzzy set. The fuzzy set allows the controller to process imprecise and fuzzy information, thereby improving the robustness of the system. The second determination module uses a pre-established rule base to determine the output adjustment strategy. These rules are based on the real-time state of the system and the preset fuzzy logic, and are used to dynamically adjust the PID parameters. In order to link the fuzzy set with a specific value, the second determination module also needs to set the membership function of each fuzzy set. The membership function defines the degree to which an element in the fuzzy set belongs to the set, which is a key part in fuzzy logic control. The optimization module uses the seeker optimization algorithm as an optimization tool to optimize the fuzzy PID controller. The seeker optimization algorithm is an intelligent optimization algorithm that finds the global optimal solution by simulating the search behavior in nature. During the optimization process, the optimization module continuously adjusts the parameters of the fuzzy PID controller to minimize the system error and improve the control performance. Through multiple iterations and searches, the optimization module finally obtains the optimized fuzzy PID controller.

[0082] Beneficial effects of the above technical solution: The generation module realizes the intelligent design and optimization of the fuzzy PID controller by integrating multiple submodules such as the establishment module, the second determination module and the optimization module. This design method improves the control accuracy and robustness of the ball valve control system. By continuously optimizing and adjusting the controller parameters, the intelligent ball valve control system can better adapt to various complex working conditions and changing environments, thereby achieving a more efficient and stable control effect.

[0083] According to some embodiments of the present invention, the establishing module includes:

[0084] Description module, used to: determine the dynamic and static characteristics of the ball valve based on experimental data and system characteristics analysis, including flow-pressure relationship, response time, and hysteresis effect;

[0085] A mathematical model is used to describe the behavior of the ball valve based on its dynamic and static characteristics;

[0086] Setup module for:

[0087] Set the initial proportional, integral and derivative gains of the fuzzy PID controller;

[0088] Define the input and output variables of the fuzzy PID controller and the corresponding fuzzy sets and rules;

[0089] Sets the input range for converting actual input values ​​to the fuzzy logic system, and converting the output values ​​of the fuzzy logic system back to the input range of the actual controller.

[0090] Working principle of the above technical solution: The main task of the description module is to determine the dynamic and static characteristics of the ball valve based on experimental data and system characteristics analysis. Mathematical models are used to describe the behavior of the ball valve. These models include differential equations, transfer functions or state space models, which can accurately reflect the dynamic and static characteristics of the ball valve. By building accurate mathematical models, the description module provides a solid foundation for subsequent controller design and optimization. This helps to ensure that the control system can accurately respond to the action of the ball valve and meet the expected control requirements. The setting module is first responsible for setting the initial proportional, integral and differential gains of the fuzzy PID controller. These gains are key parameters for the controller to adjust the system error, and their initial values ​​have an important impact on the performance and stability of the controller. The setting module needs to define the input and output variables of the fuzzy PID controller, as well as the corresponding fuzzy sets and rules. These fuzzy sets and rules are the core of the fuzzy logic controller, which determines how the controller adjusts the value of the output variable according to the fuzzy value of the input variable. The setting module also needs to set the input range for converting the actual input value to the fuzzy logic system, and the output value of the fuzzy logic system back to the input range of the actual controller. This step ensures that the fuzzy logic controller can seamlessly connect with the actual control system to achieve precise control.

[0091] Beneficial effects of the above technical solution: The establishment module realizes a comprehensive description of the ball valve control system and the initialization of the fuzzy PID controller by integrating multiple sub-modules such as the description module and the setting module. The work of this module provides important support for the subsequent controller design and optimization, ensuring that the intelligent ball valve control system can accurately respond to the movement of the ball valve and meet the expected control requirements. By continuously optimizing and adjusting the controller parameters, the intelligent ball valve control system can better adapt to various complex working conditions and changing environments, thereby achieving more efficient and stable control effects.

[0092] According to some embodiments of the present invention, it also includes: an alarm module, which is used to calculate the absolute value of the difference between the target valve position value and the real-time valve position value of the ball valve after the execution module executes the control signal, and issue an alarm prompt when it is determined that the absolute value is greater than a preset threshold.

[0093] The working principle of the above technical solution is as follows: the alarm module will first obtain the real-time valve position value of the ball valve from the execution module. At the same time, it will also obtain the current control signal from the control system, as well as the target valve position value calculated therefrom. The difference between the target valve position value and the real-time valve position value is calculated, and its absolute value is taken. The calculated absolute value of the difference is compared with the preset threshold. The preset threshold is determined during the system design phase based on the characteristics of the ball valve and the requirements of the control system. It represents the maximum allowable error range. If the absolute value of the difference is greater than the preset threshold, it means that there is a significant deviation between the actual operating state of the ball valve and the control requirements, and the alarm module will issue an alarm prompt. The alarm prompt includes sound, light, text information, etc., and the specific form depends on the system design and user needs.

[0094] Beneficial effects of the above technical solution: The existence of the alarm module is crucial to ensure the safe and stable operation of the ball valve control system. It can issue an alarm in time when the ball valve is abnormal, thereby preventing possible failures or accidents. The alarm module, through close cooperation with the execution module, sensor and control system, realizes real-time monitoring of the ball valve operation status and fault warning, providing a strong guarantee for the safe and stable operation of the system.

[0095] According to some embodiments of the present invention, the execution module includes a position PID controller and a current PID controller.

[0096] Working principle of the above technical solution: The main task of the position PID controller is to ensure that the ball valve can accurately reach its target valve position. It calculates the control error (i.e., the difference between the target valve position and the actual valve position) based on the position feedback signal (from the position sensor), and applies the PID control algorithm to adjust the drive signal, thereby gradually reducing the error and reaching the desired position. The parameters of the position PID controller (proportional, integral and differential gains) need to be fine-tuned according to the dynamic characteristics and control requirements of the ball valve to achieve optimal control performance and stability. The current PID controller is responsible for controlling the current of the motor or actuator that drives the ball valve. By monitoring the motor current and calculating the error between it and the desired current, the current PID controller can adjust the power input or motor control signal to ensure that the motor runs at the appropriate torque and speed. This is essential to prevent motor overload, reduce energy consumption, and improve the response speed and accuracy of the ball valve action. Similar to the position PID controller, the parameters of the current PID controller also need to be fine-tuned according to the characteristics and control requirements of the motor. The position PID controller and the current PID controller usually work together to achieve precise position control and stable power output. The position PID controller provides position feedback and position control instructions, while the current PID controller ensures that the motor can run at the appropriate torque and speed according to these instructions. This synergy enables the ball valve to reach its target valve position quickly and accurately while maintaining a stable operating state.

[0097] The beneficial effects of the above technical solution are as follows: by integrating the position PID controller and the current PID controller into the execution module, the intelligent ball valve control system can achieve precise position control and stable power output. This not only improves the response speed and accuracy of the ball valve, but also enhances the robustness and stability of the system.

[0098] According to some embodiments of the present invention, the method further includes: a detection module, which is used to detect a characteristic vector of the control signal during the process of the execution module executing the control signal, and to issue an alarm prompt when an abnormality is determined based on the characteristic vector.

[0099] The working principle of the above technical solution is as follows: the detection module first obtains the data of the control signal from the execution module in real time, and uses signal processing algorithms and techniques to extract the feature vector of the control signal. After extracting the feature vector, the detection module compares the feature vector with the preset feature vector and determines whether it is abnormal based on the comparison result. Once an abnormality is detected, the detection module will immediately issue an alarm prompt.

[0100] The beneficial effects of the above technical solution are: real-time monitoring and abnormality detection of control signals are realized. When an abnormality is detected, the detection module will immediately issue an alarm and record relevant information of the abnormal event. This real-time monitoring and abnormality detection mechanism provides a strong guarantee for the safe and stable operation of the ball valve control system.

[0101] According to some embodiments of the present invention, the detection module includes:

[0102] The acquisition module is used to acquire the input control signals within a preset period of time at a preset time interval and save them in chronological order as a control signal vector M;

[0103] Determine the fluctuation characteristic BM of the control signal vector M;

[0104] BM i =M i+1 -M i

[0105]

[0106] Among them, BM i is the ith value of the fluctuation characteristic BM, M i+1 is the i+1th value of the control signal vector M, M i is the i-th value of the control signal vector M, BM + is the positive fluctuation value, BM -is the negative fluctuation value, lengh(BM>0) is the number of elements in the fluctuation feature BM whose values ​​are greater than 0, lengh(BM<0) is the number of elements in the fluctuation feature BM whose values ​​are less than 0, i=1, 2, 3…N; N is the number of input control signals collected;

[0107] Calculate the fluctuation frequency of the fluctuation feature BM;

[0108] T=|find1(BM i *BM i+1 ≤0)-find2(BM i *BM i+1 ≤0)|*t*2

[0109] Where T is the fluctuation frequency, find1() is the position corresponding to the first occurrence of the fluctuation feature BM that meets the conditions in brackets, and BM i *BM i+1 ≤0 means that the value of the current position of the fluctuation feature BM multiplied by the value of the next position is less than or equal to 0, find2() is the corresponding position when the fluctuation vector BM appears for the second time to meet the conditions in the brackets, and t is the preset time interval;

[0110] determining a characteristic vector of a control signal;

[0111]

[0112] Among them, XM is the characteristic vector of the control signal; max(P + ) is the maximum value of the preset positive fluctuation value, max(P - ) is the maximum value of the preset negative fluctuation value, and max(PT) is the maximum value of the preset fluctuation frequency;

[0113] The matching module is used to match the characteristic vector of the control signal with the preset characteristic vector of the disturbed control signal, and when a match is determined, an abnormality is determined and an alarm is issued.

[0114] The working principle of the above technical solution is as follows: the control signal data is read from the control system or related sensors regularly through a timer and stored in a vector M. For each adjacent element in the control signal vector M, their difference is calculated to obtain the fluctuation feature BM. This difference reflects the local rate of change of the control signal. The positive fluctuation value and the negative fluctuation value are calculated respectively, and the positive fluctuation value represents the overall strength of the positive fluctuation. The negative fluctuation value represents the overall strength of the negative fluctuation. The starting point and the end point of the fluctuation are determined by finding the position where the product of the adjacent elements in the fluctuation feature BM is less than or equal to 0. Then, the fluctuation frequency T is calculated according to the preset time interval t. The calculation of the fluctuation frequency takes into account the time interval between adjacent fluctuations and the periodicity of the fluctuation. The positive fluctuation value, negative fluctuation value and fluctuation frequency of the fluctuation feature BM are normalized to form a feature vector XM of the control signal. Each component of XM reflects the characteristics of the control signal in a specific aspect, which is convenient for subsequent matching and abnormality detection. The feature vector XM of the control signal is matched with the preset feature vector of the disturbed control signal. If XM successfully matches the preset feature vector, it is determined that the control signal is abnormal and an alarm prompt is issued.

[0115] The beneficial effects of the above technical solution are as follows: the detection module realizes real-time monitoring and abnormality detection of the control signal by collecting the control signal, calculating the fluctuation characteristics, determining the characteristic vector and matching, so as to ensure the safe and stable operation of the ball valve control system. Through the preset characteristic vector and matching algorithm, the module can accurately identify the control signal that is disturbed and issue an alarm prompt in time, providing valuable reaction time for the operator.

[0116] According to some embodiments of the present invention, the matching module includes:

[0117] The third determination module is used to determine that the preset characteristic vector of the interfered control signal is:

[0118]

[0119] Wherein, XP is the preset characteristic vector of the disturbed control signal; XP + XP is the positive fluctuation value of the disturbed control signal. - is the negative fluctuation value of the disturbed control signal, T 0 is the fluctuation frequency of the disturbed control signal;

[0120] A second calculation module, used for calculating the difference between the characteristic vector of the control signal and the preset characteristic vector of the interfered control signal;

[0121]

[0122] Wherein, R is the difference between the characteristic vector of the control signal and the preset characteristic vector of the disturbed control signal; XM j is the jth value of the eigenvector of the control signal, XP j is the j-th value of the preset characteristic vector of the disturbed control signal;

[0123] When it is determined that the difference is less than the preset difference threshold, the feature vector representing the control signal matches the preset feature vector of the interfered control signal.

[0124] The working principle of the above technical solution is as follows: the preset feature vector is pre-set according to experience and experimental data during the system design phase, and it reflects the typical characteristics of the disturbed control signal in terms of positive fluctuations, negative fluctuations and fluctuation frequency. Each component of the preset feature vector is normalized. The difference between the feature vector of the control signal and the preset feature vector of the disturbed control signal is calculated, taking into account the components of the feature vector and the interaction between them. This formula is intended to measure the distance or similarity between two feature vectors in a multidimensional space. The square root part of the formula calculates the square of the Euclidean norm of the two feature vectors, but subtracts the square of the sum of their components, in order to adjust the influence of the vector length and highlight the difference between the components. The denominator part calculates the product of the three times the dot product of the two feature vectors minus the sum of their components, which reflects the adjustment of the three times the cosine value of the angle between the vectors and the product of the vector length, so as to provide a comprehensive difference index that takes into account both the vector length and the vector direction. When it is determined that the difference is less than the preset difference threshold, it means that the feature vector of the control signal matches the preset feature vector of the disturbed control signal. The matching module believes that the control signal has been disturbed and triggers an alarm prompt. Matching judgment is a key step in the detection module, which directly determines whether the system can identify abnormal patterns in the control signal in a timely manner. Through precise calculation and judgment, the matching module provides a strong guarantee for the safe operation of the system.

[0125] The beneficial effect of the above technical solution is that the matching module realizes the accurate matching of the control signal feature vector and the preset feature vector through the coordinated work of the third determination module and the second calculation module. This mechanism can timely detect abnormal patterns in the control signal and judge whether to trigger an alarm prompt by comparing the difference with the preset threshold, so as to ensure the safe and stable operation of the ball valve control system.

[0126] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. An intelligent ball valve control system, characterized in that: include: An acquisition module is used to obtain demand information for ball valve control; A first determination module, used to determine a control scheme of the ball valve according to the demand information; A generating module, used for generating a control signal of the ball valve according to a control scheme; An execution module is used to execute the control signal.

2. The intelligent ball valve control system according to claim 1, characterized in that: The first determining module includes: A storage module, used to store a number of pieces of historical demand information after numerical processing; the historical demand information includes historical demand characteristics, and the historical demand characteristics include flow characteristics, medium characteristics, pressure changes, temperature changes, pressure control, temperature control and flow control; A first calculation module is used to determine the demand characteristics of the demand information and calculate the matching degree between the demand characteristics and the historical demand characteristics included in the plurality of historical demand information; Among them, M q is the matching degree between the demand feature and the historical demand feature included in the qth historical demand information; s is the value of the sth sub-demand feature of the demand feature; P t,s is the value of the s-th sub-historical demand feature of the historical demand feature included in the t-th historical demand information; X d is the value of the d-th sub-demand feature of the demand feature; P t,d is the value of the d-th sub-historical demand feature of the historical demand feature included in the t-th historical demand information; M q,d is the value of the d-th sub-historical demand feature of the historical demand feature included in the q-th historical demand information; η is the preset discrimination coefficient, and η∈[0,1], t=1, 2, 3…L,, s=1, 2, 3…N, q=1, 2, 3…L, d=1, 2, 3…N, N is the number of sub-demand features included in the demand feature, and is also the number of sub-historical demand features included in the historical demand feature, and the two are equal; L is the number of historical demand information; The historical control scheme corresponding to the historical demand information with the greatest matching degree is used as the control scheme of the ball valve.

3. The intelligent ball valve control system according to claim 1, characterized in that: The generating module is used to generate a control signal of the ball valve according to a control scheme based on a pre-built fuzzy PID controller.

4. The intelligent ball valve control system according to claim 3, characterized in that: The generating module comprises: Establish a module for establishing the mathematical model of the ball valve control system and initializing the fuzzy PID controller parameters; The second determination module is used to determine the input and output of the fuzzy PID controller based on the fuzzy set, determine the output adjustment strategy based on the pre-rule base, and set the membership function of each fuzzy set; The optimization module is used to optimize the fuzzy PID controller based on the seeker optimization algorithm as an optimization tool to obtain an optimized fuzzy PID controller.

5. The intelligent ball valve control system according to claim 4, characterized in that: The establishment module comprises: Description module, used to: determine the dynamic and static characteristics of the ball valve based on experimental data and system characteristics analysis, including flow-pressure relationship, response time, and hysteresis effect; A mathematical model is used to describe the behavior of the ball valve based on its dynamic and static characteristics; Setup module for: Set the initial proportional, integral and derivative gains of the fuzzy PID controller; Define the input and output variables of the fuzzy PID controller and the corresponding fuzzy sets and rules; Sets the input range for converting actual input values ​​to the fuzzy logic system, and converting the output values ​​of the fuzzy logic system back to the input range of the actual controller.

6. The intelligent ball valve control system according to claim 1, characterized in that: Also includes: The alarm module is used to calculate the absolute value of the difference between the target valve position value and the real-time valve position value of the ball valve after the execution module executes the control signal, and to issue an alarm prompt when it is determined that the absolute value is greater than a preset threshold.

7. The intelligent ball valve control system according to claim 1, characterized in that: The execution module includes a position PID controller and a current PID controller.

8. The intelligent ball valve control system according to claim 1, characterized in that: Also includes: The detection module is used to detect the characteristic vector of the control signal during the process of the execution module executing the control signal, and to issue an alarm prompt when an abnormality is determined based on the characteristic vector.

9. The intelligent ball valve control system according to claim 8, characterized in that: The detection module comprises: The acquisition module is used to acquire the input control signals within a preset period of time at a preset time interval and save them in chronological order as a control signal vector M; Determine the fluctuation characteristic BM of the control signal vector M; BM i =M i+1 -M i Among them, BM i is the ith value of the fluctuation characteristic BM, M i+1 is the i+1th value of the control signal vector M, M i is the i-th value of the control signal vector M, BM + is the positive fluctuation value, BM - is the negative fluctuation value, lengh(BM>0) is the number of elements in the fluctuation feature BM whose values ​​are greater than 0, lengh(BM<0) is the number of elements in the fluctuation feature BM whose values ​​are less than 0, i=1, 2, 3…N; N is the number of input control signals collected; Calculate the fluctuation frequency of the fluctuation feature BM; T=|find1(BM i *BM i+1 ≤0)-find2(BM i *BM i+1 ≤0)|*t*2 Where T is the fluctuation frequency, find1() is the position corresponding to the first occurrence of the fluctuation feature BM that meets the conditions in brackets, and BM i *BM i+1 ≤0 means that the value of the current position of the fluctuation feature BM multiplied by the value of the next position is less than or equal to 0, find2() is the corresponding position when the fluctuation vector BM appears for the second time to meet the conditions in the brackets, and t is the preset time interval; determining a characteristic vector of a control signal; Among them, XM is the characteristic vector of the control signal; max(P + ) is the maximum value of the preset positive fluctuation value, max(P - ) is the maximum value of the preset negative fluctuation value, and max(PT) is the maximum value of the preset fluctuation frequency; The matching module is used to match the characteristic vector of the control signal with the preset characteristic vector of the disturbed control signal, and when a match is determined, an abnormality is determined and an alarm is issued.

10. The intelligent ball valve control system according to claim 9, characterized in that: The matching module comprises: The third determination module is used to determine that the preset characteristic vector of the interfered control signal is: Wherein, XP is the preset characteristic vector of the disturbed control signal; XP + XP is the positive fluctuation value of the disturbed control signal. - is the negative fluctuation value of the disturbed control signal, and T0 is the fluctuation frequency of the disturbed control signal; A second calculation module, used for calculating the difference between the characteristic vector of the control signal and the preset characteristic vector of the interfered control signal; Wherein, R is the difference between the characteristic vector of the control signal and the preset characteristic vector of the disturbed control signal; XM j is the jth value of the eigenvector of the control signal, XP j is the j-th value of the preset characteristic vector of the disturbed control signal; When it is determined that the difference is less than the preset difference threshold, the feature vector representing the control signal matches the preset feature vector of the interfered control signal.

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