Remote intelligent control system of directional control valve based on artificial intelligence

Abstract

The invention relates to a remote intelligent control system for a directional control valve based on artificial intelligence. The remote intelligent control system comprises a data acquisition module for acquiring current control parameters of the directional control valve through a sensor; the intelligent control module is used for collecting historical data, establishing a neural network model and predicting the control parameters to generate the control parameters; the feedback control module outputs a control decision to a pilot electromagnetic valve, a sensor monitors a main valve and feeds back data to the control module, whether the reality is consistent with the expectation or not is judged, and parameters are optimized if deviation exists; the control module is used for receiving feedback data, storing the feedback data and providing remote monitoring, and a user can remotely send an instruction and transmit the instruction to an underwater control system through wireless communication to execute operation. A deep learning algorithm is used for training a large amount of historical data, a main valve control model is established, the optimal control strategy of the main valve can be accurately predicted according to the data collected in real time, the optimal control strategy comprises the power-on and power-off state and the output pressure of the pilot electromagnetic valve, and the control precision is improved.

Description

Technical Field

[0001] The invention relates to a remote control system for a directional control valve, and in particular to a remote intelligent control system for a directional control valve based on artificial intelligence. Background Art

[0002] In the field of modern oil production, the underwater Christmas tree is a key facility connecting the submarine oil wells and the production platform. Its efficient and safe operation is crucial to the production of the entire oil field. Among them, the directional control valve, as one of the core components of the underwater Christmas tree, undertakes the important task of regulating the flow direction of the fluid. However, due to the complexity and unpredictability of the marine environment, the traditional underwater Christmas tree directional control valve usually adopts manual operation or simple automatic control methods, which has many limitations. Manual operation is not only labor-intensive and inefficient, but also faces huge safety risks in harsh underwater environments. Simple automatic control methods are often difficult to adapt to complex and changeable working conditions, and the control accuracy and response speed are limited, which cannot meet the requirements of modern marine oil and gas production for efficient and precise control.

[0003] With the rapid development of artificial intelligence technology, its application in the field of industrial automation is becoming more and more extensive, providing new ideas for solving the above problems. The remote intelligent control system of directional control valve based on artificial intelligence has come into being. The system integrates advanced sensors, communication technology and machine learning algorithms to realize real-time monitoring, intelligent diagnosis and adaptive control of directional control valves. Summary of the invention

[0004] The present invention aims to provide a remote intelligent control system for directional control valves based on artificial intelligence. The system realizes real-time monitoring, intelligent diagnosis and adaptive control of directional control valves by integrating advanced sensors, communication technology and machine learning algorithms.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] A remote intelligent control system for a directional control valve based on artificial intelligence, comprising a data acquisition module, an intelligent control module, a feedback control module and a control module.

[0007] Data acquisition module: collects the current control parameters of the directional control valve through sensors;

[0008] Intelligent control module: collect historical data, establish a neural network model, predict control parameters to generate control parameters;

[0009] Feedback control module: outputs control decisions to the pilot solenoid valve, and the sensor monitors the main valve and feeds back data to the control module to determine whether the actual is consistent with the expected, and optimizes the parameters if there is a deviation;

[0010] Control module: Receives feedback data storage and provides remote monitoring. Users can send instructions remotely, which are transmitted to the underwater control system via wireless communication to execute operations.

[0011] Furthermore, the data acquisition module determines the distribution area of ​​the directional control valve, constructs an electronic map covering the distribution area, divides the distribution area into a number of sub-areas on the electronic map, sets a number of monitoring points in each sub-area, arranges sensors at the monitoring points, and collects relevant data such as the main valve chamber pressure, the inlet and outlet pressures of the pilot solenoid valve, the valve core position, the energized and de-energized status of the pilot solenoid valve, and the output pressure through the sensors, and constructs the current control parameters of the directional control valve after summarizing.

[0012] Furthermore, the intelligent control module continuously monitors the directional control valve based on the real-time control parameters collected by the sensor, collects historical data, cleans and preprocesses the data, divides the data into training set, verification set and test set, collects relevant data of the main valve in real time, inputs it into the model for prediction, and generates control signals according to the prediction results of the model to control the energized and de-energized state of the pilot solenoid valve and the output pressure, thereby realizing intelligent control of the main valve.

[0013] Furthermore, the feedback control module outputs the formulated control decision to the pilot solenoid valve. At the same time, the sensor continuously monitors the operating status of the main valve and transmits the feedback data to the control module. Based on the data fed back by the sensor, it is determined whether the actual operating status of the main valve is consistent with the expected status. If there is a deviation, the parameters are optimized and adjusted.

[0014] Furthermore, the control module receives and stores feedback data and provides remote monitoring. Users can view the status and operating parameters of the directional control in real time and can send control instructions remotely, including opening and closing the main valve and adjusting control parameters. The control instructions are transmitted to the underwater control system via wireless communication, and the control system executes the corresponding operations issued by the control instructions.

[0015] Compared with the prior art, the present invention has the following beneficial effects:

[0016] Using deep learning algorithms to train a large amount of historical data, a main valve control model is established, which can accurately predict the optimal control strategy of the main valve based on real-time collected data, including the power-on and power-off status of the pilot solenoid valve and the output pressure, improve control accuracy, and provide remote monitoring functions. Users can view the status and operating parameters of the directional control valve in real time through the network without on-site supervision, reducing labor costs and operating risks. Users can send control instructions remotely to achieve remote operation of the underwater Christmas tree directional control valve, improve operational flexibility and convenience, and continuously adjust the control strategy based on sensor feedback data to achieve closed-loop control. When the actual operation of the main valve deviates from expectations, the parameters can be optimized and adjusted so that the system can adapt to different working conditions and environmental changes and achieve adaptive control. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a flow chart of the remote intelligent control system of the directional control valve based on artificial intelligence of the present invention;

[0018] Figure 2 This is a system block diagram of the artificial intelligence-based directional control valve remote intelligent control system of the present invention. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical scheme and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention, that is, the embodiments described are only part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0020] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present invention.

[0021] like Figure 1 As shown in 2, an embodiment of the present invention provides an artificial intelligence-based remote intelligent control system for a directional control valve, including a data acquisition module, an intelligent control module, a feedback control module and a control module.

[0022] Data acquisition module: collects the current control parameters of the directional control valve through sensors;

[0023] Intelligent control module: collect historical data, establish a neural network model, predict control parameters to generate control parameters;

[0024] Feedback control module: outputs control decisions to the pilot solenoid valve, and the sensor monitors the main valve and feeds back data to the control module to determine whether the actual is consistent with the expected, and optimizes the parameters if there is a deviation;

[0025] Control module: Receives feedback data storage and provides remote monitoring. Users can send instructions remotely, which are transmitted to the underwater control system via wireless communication to execute operations.

[0026] Preferably, the data acquisition module: determines the distribution area of ​​the directional control valve, constructs an electronic map covering the distribution area, divides the distribution area into a number of sub-areas on the electronic map, sets a number of monitoring points in each sub-area, arranges sensors at the monitoring points, collects relevant data such as the main valve chamber pressure, the inlet and outlet pressures of the pilot solenoid valve, the valve core position, the energized and de-energized status of the pilot solenoid valve, and the output pressure through the sensors, and constructs the current control parameters of the directional control valve after summarizing.

[0027] Preferably, the intelligent control module: based on the real-time control parameters collected by the sensor, continuously monitors the directional control valve, collects historical data, cleans and preprocesses the data, divides the data into training set, verification set and test set, collects relevant data of the main valve in real time, inputs it into the model for prediction, generates a control signal according to the prediction results of the model, controls the energized and de-energized state of the pilot solenoid valve and the output pressure, and realizes intelligent control of the main valve.

[0028] Preferably, the feedback control module: outputs the formulated control decision to the pilot solenoid valve, while the sensor continuously monitors the operating status of the main valve, and transmits the feedback data to the control module. According to the data fed back by the sensor, it is judged whether the actual operating condition of the main valve is consistent with the expectation. If there is a deviation, the parameters are optimized and adjusted.

[0029] Preferably, the control module: receives feedback data and stores it, provides remote monitoring, and the user can view the status and operating parameters of the directional control in real time. Control instructions can be sent remotely, including opening and closing the main valve and adjusting control parameters. The control instructions are transmitted to the underwater control system via wireless communication, and the control system executes the corresponding operations issued by the control instructions.

[0030] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", etc. should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be an indirect connection through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0031] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A remote intelligent control system for directional control valves based on artificial intelligence, characterized in that: Including data acquisition module, intelligent control module, feedback control module and control module, Data acquisition module: collects the current control parameters of the directional control valve through sensors; Intelligent control module: collect historical data, establish a neural network model, predict control parameters to generate control parameters; Feedback control module: outputs control decisions to the pilot solenoid valve, and the sensor monitors the main valve and feeds back data to the control module to determine whether the actual is consistent with the expected, and optimizes the parameters if there is a deviation; Control module: Receives feedback data storage and provides remote monitoring. Users can send instructions remotely, which are transmitted to the underwater control system via wireless communication to execute operations.

2. The remote intelligent control system for directional control valves based on artificial intelligence according to claim 1 is characterized in that: The data acquisition module determines the distribution area of ​​the directional control valve, constructs an electronic map covering the distribution area, divides the distribution area into several sub-areas on the electronic map, sets several monitoring points in each sub-area, arranges sensors at the monitoring points, and collects data related to the main valve chamber pressure, the inlet and outlet pressures of the pilot solenoid valve, the valve core position, the energized and de-energized status of the pilot solenoid valve, and the output pressure through the sensors, and then constructs the current control parameters of the directional control valve after summarizing.

3. The remote intelligent control system for directional control valves based on artificial intelligence according to claim 1 is characterized in that: Based on the real-time control parameters collected by the sensor, the intelligent control module continuously monitors the directional control valve, collects historical data, cleans and preprocesses the data, divides the data into training set, verification set and test set, collects relevant data of the main valve in real time, inputs it into the model for prediction, and generates control signals according to the prediction results of the model to control the energized and de-energized state of the pilot solenoid valve and the output pressure, thereby realizing intelligent control of the main valve.

4. The remote intelligent control system for directional control valves based on artificial intelligence according to claim 1 is characterized in that: The feedback control module outputs the formulated control decision to the pilot solenoid valve. At the same time, the sensor continuously monitors the operating status of the main valve and transmits the feedback data to the control module. Based on the data fed back by the sensor, it determines whether the actual operating status of the main valve is consistent with the expected status. If there is a deviation, the parameters are optimized and adjusted.

5. The remote intelligent control system for directional control valves based on artificial intelligence according to claim 1 is characterized in that: The control module receives and stores feedback data and provides remote monitoring. Users can view the status and operating parameters of the directional control in real time and send control instructions remotely, including opening and closing the main valve and adjusting control parameters. The control instructions are transmitted to the underwater control system via wireless communication, and the control system executes the corresponding operations issued by the control instructions.

Images