Control device of a drilling machine, data transmission method, system and storage medium

Abstract

The application discloses a drilling machine control device, a data transmission method and system, and a storage medium, and belongs to the technical field of engineering machinery. The drilling machine control device comprises a sensor arranged on multiple components of the drilling machine, which is used for uploading collected measurement parameters to a collection system controller; a whole machine controller, which is used for sending action parameters and engine state parameters of the drilling machine to the collection system controller; the collection system controller, which is used for sending the measurement parameters, the action parameters and the engine state parameters to an industrial computer; and the industrial computer, which is used for inputting the measurement parameters, the action parameters and the engine state parameters into an AI prediction model to obtain control parameters, and sending the control parameters to the whole machine controller, so as to control the drilling machine. The application can obtain various working parameters in the working process of the drilling machine, and realizes precise control of the drilling machine.

Description

Technical Field

[0001] This application relates to the field of engineering machinery technology, and in particular to a control device, data transmission method, system and storage medium for drilling machinery. Background Technology

[0002] Data acquisition devices for drilling machinery such as rotary drilling rigs and core drilling rigs are mostly bench-tested. When certain data needs to be collected, the data acquisition device is manually installed on-site. This lack of comprehensive analysis of data during normal operation and various complex working conditions makes it impossible to optimize control parameters in real time, resulting in low control accuracy of the drilling machinery.

[0003] Therefore, how to improve the control accuracy of drilling machinery is a technical problem that needs to be solved by those skilled in the art. Summary of the Invention

[0004] The purpose of this application is to provide a control device for drilling machinery, a data transmission method, a data transmission system, and a storage medium, which can improve the control accuracy of drilling machinery.

[0005] To solve the above-mentioned technical problems, this application provides a control device for drilling machinery, comprising:

[0006] Sensors installed on multiple components of the drilling machinery are used to upload the collected measurement parameters to the acquisition system controller;

[0007] The whole machine controller is used to send the action parameters and engine status parameters of the drilling machinery to the acquisition system controller;

[0008] The data acquisition system controller is used to send the measurement parameters, the action parameters, and the engine status parameters to the industrial control computer;

[0009] The industrial control computer is used to input the measurement parameters, the action parameters, and the engine status parameters into the AI ​​prediction model to obtain control parameters, and then send the control parameters to the whole machine controller to control the drilling machinery.

[0010] Optionally, the acquisition system controller includes an acquisition system master controller and an acquisition system slave controller;

[0011] The sensors include a first type of sensor connected to the main controller of the acquisition system, and a second type of sensor connected to the slave controller of the acquisition system;

[0012] The acquisition system is controlled by a controller, which uploads the measurement parameters acquired by the second type of sensor to the main controller of the acquisition system.

[0013] The main controller of the acquisition system is used to receive the measurement parameters collected by the first type of sensor and the action parameters and engine status parameters sent by the whole machine controller, and send the measurement parameters collected by the second type of sensor, the measurement parameters collected by the first type of sensor, the action parameters and the engine status parameters to the industrial control computer.

[0014] Optionally, the industrial control computer is used to send the control parameters to the whole machine controller through the main controller of the acquisition system.

[0015] Optionally, the data acquisition system controller is used to package the measurement parameters, the action parameters, and the engine status parameters into a whole machine status data packet, and send the whole machine status data packet to the industrial control computer;

[0016] Accordingly, the industrial control computer is used to parse the whole machine status data packet into the measurement parameters, the action parameters and the engine status parameters, and input the measurement parameters, the action parameters and the engine status parameters into the AI ​​(Artificial Intelligence) prediction model to obtain the control parameters.

[0017] Optional, also includes:

[0018] The communication terminal connected to the data acquisition system controller;

[0019] Correspondingly, the acquisition system controller is also used to send the whole machine status data packet to the communication terminal, so that the communication terminal can upload the whole machine status data packet to the cloud computer.

[0020] Optionally, the cloud computer runs an AI prediction model that is to be trained or validated.

[0021] Optionally, the AI ​​prediction model includes:

[0022] The electromechanical-hydraulic integration model is used to predict the control parameters of the actuators and the main hoist.

[0023] And / or, engine models, used to predict the control parameters of the transmitter;

[0024] And / or, a power head model, used to predict the control parameters of the power head motor.

[0025] This application also provides a data transmission method applied to the acquisition system controller in the control device of the aforementioned drilling machinery, the data transmission method comprising:

[0026] It receives engine status parameters, drilling machinery motion parameters, and measurement data collected by sensors;

[0027] The engine status parameters, the action parameters, and the measurement data are packaged into a whole machine status data package;

[0028] The overall machine status data packet is sent to the industrial control computer so that the industrial control computer can use the AI ​​prediction model to calculate the control parameters corresponding to the overall machine status data packet;

[0029] The system receives control parameters returned by the industrial computer and sends the control parameters to the overall controller to control the drilling machinery.

[0030] This application also provides a data transmission system, applied to the acquisition system controller in the control device of the aforementioned drilling machinery, the data transmission system comprising:

[0031] The data receiving module is used to receive engine status parameters, drilling machinery motion parameters, and measurement data collected by sensors.

[0032] The data packaging module is used to package the engine status parameters, the action parameters, and the measurement data into a whole machine status data package;

[0033] The data transmission module is used to send the whole machine status data packet to the industrial control computer, so that the industrial control computer can use the AI ​​prediction model to calculate the control parameters corresponding to the whole machine status data packet;

[0034] The data forwarding module is used to receive the control parameters returned by the industrial control computer and send the control parameters to the whole machine controller so as to control the drilling machine.

[0035] This application also provides a storage medium on which a computer program is stored, wherein the computer program, when executed, implements the steps of the above-described data transmission method.

[0036] This application provides a control device for drilling machinery, comprising: sensors disposed on multiple components of the drilling machinery for uploading collected measurement parameters to a data acquisition system controller; a machine controller for sending the drilling machinery's motion parameters and engine status parameters to the data acquisition system controller; the data acquisition system controller for sending the measurement parameters, motion parameters, and engine status parameters to an industrial control computer; and the industrial control computer for inputting the measurement parameters, motion parameters, and engine status parameters into an AI prediction model to obtain control parameters, and sending the control parameters to the machine controller for controlling the drilling machinery.

[0037] The control device for drilling machinery provided in this application includes sensors installed in multiple components, a whole-machine controller, a data acquisition system controller, and an industrial computer. The data acquisition system controller can receive measurement parameters uploaded by the sensors and action parameters and engine status parameters sent by the whole-machine controller to achieve comprehensive data acquisition. The data acquisition system controller sends the measurement parameters, action parameters, and engine status parameters to the industrial computer. The industrial computer uses an AI prediction model to predict the measurement parameters, action parameters, and engine status parameters to obtain the control parameters for the whole-machine controller in the next step. This application can acquire multiple working parameters during the drilling machinery's operation, achieving precise control of the drilling machinery. This application also provides a control device for drilling machinery, a data transmission method, a data transmission system, and a storage medium, which have the above-mentioned beneficial effects and will not be elaborated further here. Attached Figure Description

[0038] To more clearly illustrate the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 This is a schematic diagram of the structure of a control device for drilling machinery provided in an embodiment of this application;

[0040] Figure 2 A flowchart illustrating a data transmission method provided in an embodiment of this application;

[0041] Figure 3 A flowchart illustrating a data transmission system provided in an embodiment of this application;

[0042] Figure 4 This is a schematic diagram of the structure of a digital twin data acquisition system for a rotary drilling rig provided in an embodiment of this application;

[0043] Figure 5 This is a flowchart illustrating the signal flow of a digital twin data acquisition system for a rotary drilling rig, as provided in an embodiment of this application.

[0044] Figure 6 This is a communication principle block diagram of a digital twin data acquisition system for rotary drilling rigs provided in an embodiment of this application. Detailed Implementation

[0045] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0046] Please see below. Figure 1 , Figure 1 This is a schematic diagram of the structure of a control device for a drilling machine provided in an embodiment of this application.

[0047] Sensors 101, installed on multiple components of the drilling machinery, are used to upload the collected measurement parameters to the acquisition system controller 102.

[0048] In this embodiment, sensors can be installed on the engine exhaust manifold, main pump, power head motor, and other parts of the drilling machinery. These sensors include, but are not limited to, pressure sensors, air flow sensors, and displacement sensors. Each sensor uploads the signals it collects to the acquisition system controller 102.

[0049] The whole machine controller 103 is used to send the action parameters of the drilling machinery and the engine status parameters to the acquisition system controller 102;

[0050] The overall controller 103 controls the drilling machinery and collects its motion parameters and engine status parameters. These parameters are then sent to the data acquisition system controller 102 for aggregation. The motion parameters of the drilling machinery can be important operational parameters, such as the X-axis position of the left handle, the status of the buttons on the left handle, the status of the right foot pedal, the forward rotation of the power head, and the lifting of the main winding mechanism.

[0051] The data acquisition system controller 103 is used to send the measurement parameters, the action parameters and the engine status parameters to the industrial control computer 104;

[0052] The data acquisition system controller 103 can package and send the measurement parameters, action parameters and engine status parameters acquired in the same cycle or at the same time to the industrial control computer 104.

[0053] The industrial control computer 104 is used to input the measurement parameters, the action parameters and the engine status parameters into the AI ​​prediction model to obtain control parameters, and send the control parameters to the whole machine controller so as to control the drilling machinery.

[0054] The industrial control computer 104 runs an AI prediction model. After the measurement parameters, action parameters, and engine status parameters are input into the AI ​​prediction model, the model can output the control parameters required by the overall machine controller. After the control parameters are sent to the overall machine controller, the drilling machinery can be controlled.

[0055] Furthermore, the aforementioned AI prediction model may include any one or a combination of any of the following: an electromechanical-hydraulic integrated model, an engine model, and a power head model. The electromechanical-hydraulic integrated model is used to predict the control parameters of the actuator and the main winch; the engine model is used to predict the control parameters of the transmitter; and the power head model is used to predict the control parameters of the power head motor.

[0056] The control device for drilling machinery provided in this embodiment includes sensors installed in multiple components, a machine controller, a data acquisition system controller, and an industrial computer. The data acquisition system controller can receive measurement parameters uploaded by the sensors and action parameters and engine status parameters sent by the machine controller to achieve comprehensive data acquisition. The data acquisition system controller sends the measurement parameters, action parameters, and engine status parameters to the industrial computer. The industrial computer uses an AI prediction model to predict the measurement parameters, action parameters, and engine status parameters to obtain the control parameters for the machine controller in the next step. This embodiment can acquire multiple operating parameters during the drilling machinery's operation, achieving precise control of the drilling machinery.

[0057] As for Figure 1 As further described in the corresponding embodiment, when there are many measurement parameters to be collected, a single controller may not have enough channels to process sensor data. Therefore, a controller cascading approach can be used to collect the measurement parameters. Specifically, the aforementioned acquisition system controller includes a main acquisition system controller and a slave acquisition system controller; the sensors include a first type of sensor connected to the main acquisition system controller and a second type of sensor connected to the slave acquisition system controller.

[0058] The acquisition system is controlled by a controller, which uploads the measurement parameters acquired by the second type of sensor to the main controller of the acquisition system.

[0059] The main controller of the acquisition system is used to receive the measurement parameters collected by the first type of sensor and the action parameters and engine status parameters sent by the whole machine controller, and send the measurement parameters collected by the second type of sensor, the measurement parameters collected by the first type of sensor, the action parameters and the engine status parameters to the industrial control computer.

[0060] The aforementioned industrial control computer can send the control parameters to the overall machine controller through the main controller of the acquisition system.

[0061] As for Figure 1 In a further description of the corresponding embodiment, the above-mentioned acquisition system controller is used to package the measurement parameters, the action parameters and the engine status parameters into a whole machine status data packet, and send the whole machine status data packet to the industrial control computer;

[0062] Accordingly, the industrial control computer is used to parse the whole machine status data packet into the measurement parameters, the action parameters and the engine status parameters, and input the measurement parameters, the action parameters and the engine status parameters into the AI ​​prediction model to obtain the control parameters.

[0063] As for Figure 1 In a further description of the corresponding embodiment, the control device for the drilling machinery also includes a communication terminal connected to the data acquisition system controller. The data acquisition system controller is also used to send the overall machine status data packet to the communication terminal, so that the communication terminal can upload the overall machine status data packet to a cloud computer.

[0064] As for Figure 1 As further described in the corresponding embodiment, the aforementioned cloud computer runs an AI prediction model that needs to be trained or verified. The cloud computer can parse the overall machine status data packet into the measurement parameters, the action parameters, and the engine status parameters, and then use the measurement parameters, action parameters, and engine status parameters to train the AI ​​prediction model in the cloud computer, or use the measurement parameters, action parameters, and engine status parameters to verify the AI ​​prediction model in the cloud computer.

[0065] Please see below. Figure 2 , Figure 2 A flowchart of a data transmission method provided in this application embodiment, the specific steps of which may include:

[0066] S201: Receives engine status parameters, drilling machinery motion parameters, and measurement data collected by sensors;

[0067] This embodiment can be applied to the acquisition system controller in the control device of any of the drilling machines described in the above embodiments.

[0068] S202: Package the engine status parameters, the action parameters, and the measurement data into a whole machine status data package;

[0069] Specifically, the aforementioned system status data packet can be a UDP (User Datagram Protocol) data packet.

[0070] S203: Send the whole machine status data packet to the industrial control computer so that the industrial control computer can use the AI ​​prediction model to calculate the control parameters corresponding to the whole machine status data packet;

[0071] The AI ​​prediction model mentioned above is a trained and validated model. It can predict the control parameters required for the next step of the drilling machine based on its current overall state. After receiving the control parameters, the industrial control computer can send them to the data acquisition system controller, which in turn sends them to the overall machine controller.

[0072] S204: Receive the control parameters returned by the industrial control computer and send the control parameters to the whole machine controller so as to control the drilling machine.

[0073] The control device for drilling machinery provided in this embodiment includes sensors installed in multiple components, a machine controller, a data acquisition system controller, and an industrial computer. The data acquisition system controller can receive measurement parameters uploaded by the sensors and action parameters and engine status parameters sent by the machine controller to achieve comprehensive data acquisition. The data acquisition system controller sends the measurement parameters, action parameters, and engine status parameters to the industrial computer. The industrial computer uses an AI prediction model to predict the measurement parameters, action parameters, and engine status parameters to obtain the control parameters for the machine controller in the next step. This embodiment can acquire multiple operating parameters during the drilling machinery's operation, achieving precise control of the drilling machinery.

[0074] Please see below. Figure 3 , Figure 3 A flowchart illustrating a data transmission system provided in this application embodiment. This data transmission system can be applied to the acquisition system controller in the control device of drilling machinery. The data transmission system includes:

[0075] The data receiving module 301 is used to receive engine status parameters, drilling machinery action parameters, and measurement data collected by sensors.

[0076] Data packaging module 302 is used to package the engine status parameters, the action parameters and the measurement data into a whole machine status data package;

[0077] Data sending module 303 is used to send the whole machine status data packet to the industrial control computer so that the industrial control computer can use the AI ​​prediction model to calculate the control parameters corresponding to the whole machine status data packet;

[0078] The data forwarding module 304 is used to receive the control parameters returned by the industrial control computer and send the control parameters to the whole machine controller so as to control the drilling machine.

[0079] The control device for drilling machinery provided in this embodiment includes sensors installed in multiple components, a machine controller, a data acquisition system controller, and an industrial computer. The data acquisition system controller can receive measurement parameters uploaded by the sensors and action parameters and engine status parameters sent by the machine controller to achieve comprehensive data acquisition. The data acquisition system controller sends the measurement parameters, action parameters, and engine status parameters to the industrial computer. The industrial computer uses an AI prediction model to predict the measurement parameters, action parameters, and engine status parameters to obtain the control parameters for the machine controller in the next step. This embodiment can acquire multiple operating parameters during the drilling machinery's operation, achieving precise control of the drilling machinery.

[0080] The process described in the above embodiments is illustrated below through a practical application of a 5G communication-based digital twin data acquisition system for rotary drilling rigs.

[0081] To improve the working efficiency of rotary drilling rigs, reduce energy consumption, and enhance the reliability and safety of construction machinery, research in this field typically focuses on one or two aspects such as dynamic characteristics, power matching, structural analysis, and construction methods. However, comprehensive analyses of the overall performance improvement, reliability, safety, and maintainability of rotary drilling rigs are rare, and data acquisition systems capable of comprehensively analyzing the overall performance of construction machinery are lacking. Furthermore, existing rotary drilling rig data acquisition systems are mostly bench-tested, requiring data acquisition under specific working conditions before installing the data acquisition device on-site. They lack comprehensive analysis of data from normal machine operation and various complex working conditions. Moreover, after data analysis, they cannot achieve real-time optimization of control parameters and feed these parameters back to the machine for real-time optimized control.

[0082] To address the technical problems existing in the aforementioned related technologies, this embodiment provides a digital twin data acquisition system for rotary drilling rigs based on 5G communication. Please refer to [link to relevant documentation]. Figure 4 , Figure 4 This is a schematic diagram of a digital twin data acquisition system for a rotary drilling rig provided in an embodiment of this application. The system includes sensors such as a high-temperature pressure sensor, pressure sensors A1-A14, flow sensors 1-5, pressure sensors B1-B12, an air flow sensor, a temperature sensor, and a displacement sensor. The system also includes a main controller, slave controllers, an industrial camera, a 5G communication terminal, a vehicle-mounted industrial computer, and the rotary drilling rig's overall controller. The 5G communication terminal includes a switch and a 5G router. The 5G communication terminal can transmit data to the cloud (such as a cloud computer or cloud server). Figure 4 The document also shows analog signals, Ethernet signals, and CAN (Controller Area Network, serial communication protocol) signals.

[0083] The data acquisition system collects analog signals from 12 pressure sensors, 1 air flow sensor, 1 temperature sensor, and 1 displacement sensor from the controller, and sends all analog data to the main controller via the CAN bus. In addition to receiving sensor signals from the controller, the main controller directly acquires analog signals from 1 high-temperature pressure sensor, 14 pressure sensors, and 5 flow sensors. It then converts these analog signals into pressure, flow, temperature, and displacement signals. Simultaneously, the main controller reads key operational parameters, engine speed, torque, and fuel consumption rate from the CAN bus with the rotary drilling rig's overall controller. All acquired and read data is then transmitted via Ethernet communication, passing through a switch, 5G router, and 5G antenna to a cloud computer. The cloud interface allows for real-time reading, viewing, and analysis of the acquired data, as well as historical data storage, analysis, and export. The vehicle-mounted industrial control computer can receive all data sent by the main controller of the acquisition system through the 5G terminal's switch. The vehicle-mounted industrial control computer can store all the received data and provide real-time data to various modeling models, including the engine model, the electromechanical-hydraulic integration model, and the power head model. The 5G terminal consists of a switch, a 5G router, and a 5G antenna, etc.

[0084] The aforementioned high-temperature pressure sensor is installed at the engine exhaust manifold to measure the gas pressure. Specifically, pressure sensors A1, A4, A12, flow sensor 1, and flow sensor 4 are described on the main controller. Pressure sensor A1 is installed at the main pump outlet to detect the main pump outlet pressure. Pressure sensor 4 is installed at the power head motor inlet to detect the power head motor inlet pressure. Pressure sensor A12 is installed at the G port of the power head motor to detect the G port pressure of power head motor 1. Flow sensor 1 is installed at the main pump outlet to detect the main pump outlet flow rate. Flow sensor 4 is installed at the power head motor outlet to detect the power head motor outlet flow rate. The G port is an oil port used for synchronous control of multiple components and remote pressure control.

[0085] Please see Figure 5 , Figure 5This document presents a signal flow flowchart for a digital twin data acquisition system for a rotary drilling rig, as provided in an embodiment of this application. After the rotary drilling rig digital twin data acquisition system is powered on, the operation of the acquisition system's controller includes: receiving analog signals from sensors; determining whether the sensors are faulty based on the analog signals; if so, invalidating the data or setting it to 0 and issuing a fault alarm; otherwise, converting the data acquired by the sensors into CAN data packets and sending the CAN data packets to the acquisition system's main controller. The operation of the acquisition system's main controller includes: after the system is powered on, determining the data source; if the data source is an analog signal from a sensor, determining whether the sensor is faulty; if so, invalidating the data or setting it to 0 and issuing a fault alarm; otherwise, performing analog-to-digital conversion. If the data source is a CAN data packet transmitted from the acquisition system's controller, parsing the CAN data packet into an analog signal and performing analog-to-digital conversion; determining whether the converted data exceeds the calibration range; if so, issuing an over-limit alarm. The acquisition system's main controller can also receive CAN data packets sent by the main controller, and then convert the converted data and the CAN data packets sent by the main controller into UDP data packets, sending the UDP data packets to an industrial computer or a remote interface in the cloud. In the remote interface, the cloud-based computer can send received data to the offline electromechanical-hydraulic integrated model, engine model, and power head model. In the industrial control unit (ICU), the onboard ICU can send received data to the online electromechanical-hydraulic integrated model, engine model, and power head model. The onboard ICU can send sensor calibration parameters to the acquisition system's main controller, which converts them into UDP data packets. The ICU can determine whether the transmitter model has been verified successfully and, upon completion, output the vehicle control parameters so that the acquisition system's main controller can forward the vehicle control parameter CAN data packets to the vehicle controller.

[0086] After the system is powered on, the master and slave controllers of the acquisition system are powered on and started. The master controller determines whether the sensor is faulty based on the detected sensor signal. If the sensor is faulty, it will upload the sensor fault information. If the sensor is normal, it will convert the detected sensor analog signal (current or voltage signal) into the corresponding pressure, flow and other signals, and package the pressure, flow and other data into UDP data packets and send them out. If the sensor pressure and flow exceed the calibrated range, an over-limit alarm will be triggered.

[0087] The data acquisition system, based on the detected sensor signals from the controller, determines whether the sensor is faulty. If a fault is detected, a sensor fault report is uploaded; if the sensor is functioning normally, the detected analog sensor signal is packaged into a CAN data packet and sent to the main controller. Simultaneously, the main controller parses the CAN data packet sent from the controller into analog sensor signals (current or voltage signals), converts these signals into corresponding pressure, flow, temperature, and displacement signals, and packages these data into UDP data packets for transmission. If the sensor's pressure, flow, temperature, or displacement exceeds the calibrated range, an over-limit alarm is triggered. Furthermore, the main controller directly packages the CAN data packets sent from the main controller into UDP data packets and forwards them to the onboard industrial computer and the cloud computer.

[0088] The onboard industrial control computer parses the received UDP data packets into pressure, flow, temperature, and displacement signals from the sensors and displays them on the sensor interface. It also displays engine speed, torque, and lever actuation signals from the vehicle controller on the engine interface. Simultaneously, it can input data such as sensor signals received from the industrial control computer, vehicle operation signals from the vehicle controller, and engine signals into the industrial control computer's electromechanical-hydraulic integrated model, power head model, and engine model for online verification. After model verification, the model provides control parameters for the next stage of overall system control based on the parameters collected by the acquisition system. The industrial control computer packages these control parameters and sends them to the acquisition system's main controller. The main controller parses the UDP data packets and transmits the control parameters back to the overall system controller via CAN data packets, thus achieving overall system control.

[0089] The cloud-based computer parses received UDP data packets into pressure, flow, temperature, and displacement signals from sensors in various parts of the rotary drilling rig. The main display interface allows real-time viewing of signal values ​​from the power head pressure and flow, main pump pressure and flow, multi-way valve pressure, engine intake air flow, exhaust temperature, speed, torque, pressurized cylinder pressure and displacement, and the operation of the machine's handles and foot pedals. The right side displays real-time curves for selected pressure and flow rates. The cloud-based computer's historical curve and data interface allows for viewing and exporting historical data and curves. Historical curves can display multiple parameters simultaneously or individual parameters for convenient parameter comparison and analysis. The electromechanical-hydraulic integration model (offline), power head model (offline), and engine model (offline) can be trained and validated using historical data from the cloud. After model validation, control parameters for optimizing overall machine performance can be output.

[0090] The input parameters for the mechatronics integrated model include pump pressure, pump flow rate, main hoist pressure, motor pressure, actuator pressure, actuator flow rate, control component pressure, cylinder pressure, cylinder displacement, actuator pressure, handle / foot pedal action signal, and solenoid valve current parameters. The mechatronics integrated model calculates the input parameters at time t using an AI (such as a fuzzy neural network) model and compares this calculation with the actuator pressure and flow rate at time t+1. Based on the comparison, the results are fed back to the actuator's AI model for further training until the model can predict the target signal values ​​of the actuator pressure and flow rate at time t+1 using the input parameters at time t (the prediction error reaches 0.25% of the measurement accuracy of the pressure and flow sensors). The output parameters of the mechatronics integrated model include actuator pressure and flow rate, actuator pressure, main hoist pressure and speed, and actuator torque and speed.

[0091] The power head model inputs include one each of inlet pressure, outlet pressure, G-port pressure, and inlet / outlet flow rate, as well as parameters such as main winding pressure, cylinder pressure and displacement, left handle and foot pedal action signals, and control component pressure. The power head model calculates the input parameters at time t using an AI (e.g., fuzzy neural network) model and compares the results with the pressure and inlet / outlet flow rates at time t+1 of the power head outlet and G-port. Based on the comparison, the results are fed back to the power head's AI model for further training until the model can predict the target signal values ​​for the power head outlet and G-port pressure and inlet / outlet flow rates at time t+1 using the input parameters at time t (the prediction error reaches 0.25% of the measurement accuracy of the pressure and flow sensors). The power head model output parameters include the torque and speed of the power head motor, and the motor outlet pressure and flow rate.

[0092] The engine model inputs include parameters such as actual engine torque percentage, engine speed, engine load rate, instantaneous engine fuel consumption, intake manifold pressure, intake manifold temperature, fuel consumption, engine coolant temperature, engine oil pressure, engine intake manifold airflow, exhaust manifold pressure, exhaust manifold temperature, main pump pressure, main pump flow, power head inlet pressure, power head flow, main auger inlet pressure, main auger inlet flow, auxiliary pump pressure, and auxiliary pump flow. The engine model calculates the input parameters at time t using an AI (such as a BP neural network) model and compares them with the values ​​at time t+1 for engine speed, engine torque percentage, engine oil pressure, and instantaneous engine fuel consumption. Based on the comparison, the results are fed back to the AI ​​model for further training until the model can predict the target signal values ​​for these parameters at time t+1 using the input parameters at time t (when the prediction error reaches a measurement accuracy of 0.25%). The engine model output parameters include engine speed, torque percentage, oil pressure, and instantaneous fuel consumption.

[0093] Please see Figure 6 , Figure 6 This is a communication principle block diagram of a digital twin data acquisition system for a rotary drilling rig provided in an embodiment of this application. The overall controller of the rotary drilling rig is connected to the main controller of the acquisition system via a CAN bus. The main controller of the acquisition system is connected to the slave controller of the acquisition system. The main controller of the acquisition system is connected to a 5G communication terminal. The 5G communication terminal includes a switch and a 5G router. The switch is connected to an on-board industrial control computer, and the 5G router is connected to a cloud computer. Figure 6 Ethernet and CAN signals are also shown.

[0094] The data transmission of the acquisition system uses a CAN bus between the main controller and the overall controller of the acquisition system, and between the slave controllers. The main controller communicates with the industrial computer and the cloud computer via Ethernet. The main controller and the overall controller are located close to each other. The rotary drilling rig primarily uses CAN communication. Without changing the original overall control communication method, the main controller and the overall controller use CAN bus communication. The slave controllers are located together with the main controller, and communication between the main controller and the slave controllers also uses CAN bus. The main controller communicates with the onboard industrial computer via Ethernet to achieve real-time, high-speed transmission of large amounts of data. Simultaneously, the main controller transmits data to the cloud computer via Ethernet through a switch and a 5G router. Using 5G communication enables long-distance transmission of large amounts of data with low latency, long transmission distance, and good data stability.

[0095] The aforementioned data acquisition system enables a comprehensive analysis of data from the normal operation and complex working conditions of rotary drilling rigs, providing a tool for comprehensive performance analysis of the entire rig. The analysis results guide technicians in optimizing design and improving control methods to enhance the overall performance of the rotary drilling rig. This tool can also guide technicians in cost reduction and efficiency improvement in the research and development of rotary drilling rigs. After data analysis, this embodiment can achieve real-time optimization of control parameters and feed these parameters back to the mechanical equipment to achieve real-time optimized control. This addresses the problem of onboard data acquisition and communication, and remote real-time data analysis, which cannot achieve real-time optimization of control parameters. Taking engine modeling as an example, the data acquired by the data acquisition system trains the engine simulation model, identifies the main parameters for improving engine energy utilization efficiency and reducing energy consumption, and uses these parameters to optimize the overall vehicle control. The acquisition system's main controller communicates with slave controllers and the overall machine controller via CAN, while the main controller communicates with the onboard industrial computer and cloud computer via 5G. Data is transferred through internal data packets within the main controller. This communication scheme allows for the transmission of large amounts of data over long distances without altering the original communication methods of the construction machinery, and also enables real-time optimization of vehicle control. This embodiment primarily acquires analog signals, but it can also be applied to acquiring other signal types such as digital signals. This embodiment can solve the problems of lacking comprehensive analysis of the overall performance of construction machinery and the inability to optimize control parameters in real time.

[0096] This application also provides a storage medium on which a computer program is stored, which, when executed, can perform the steps provided in the above embodiments. The storage medium may include various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0097] This application also provides an electronic device that may include a memory and a processor. The memory stores a computer program, and when the processor calls the computer program in the memory, it can implement the steps provided in the above embodiments. Of course, the electronic device may also include various network interfaces, power supplies, and other components.

[0098] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to in the method section. It should be noted that those skilled in the art can make various improvements and modifications to this application without departing from the principles of this application, and these improvements and modifications also fall within the protection scope of the claims of this application.

[0099] It should also be noted that, in this specification, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

Claims

1. A control device of a boring machine, characterized in that, include: Sensors installed on multiple components of the drilling machinery are used to upload the collected measurement parameters to the acquisition system controller; The whole machine controller is used to send the action parameters and engine status parameters of the drilling machinery to the acquisition system controller; The data acquisition system controller is used to send the measurement parameters, the action parameters, and the engine status parameters to the industrial control computer; The industrial control computer is used to input the measurement parameters, the action parameters, and the engine status parameters into the AI ​​prediction model to obtain control parameters, and send the control parameters to the whole machine controller in order to control the drilling machinery; The acquisition system controller includes an acquisition system master controller and an acquisition system slave controller; The sensors include a first type of sensor connected to the main controller of the acquisition system, and a second type of sensor connected to the slave controller of the acquisition system; The acquisition system is controlled by a controller, which uploads the measurement parameters acquired by the second type of sensor to the main controller of the acquisition system. The main controller of the acquisition system is used to receive the measurement parameters acquired by the first type of sensor and the action parameters and engine status parameters sent by the whole machine controller, and send the measurement parameters acquired by the second type of sensor, the measurement parameters acquired by the first type of sensor, the action parameters and the engine status parameters to the industrial control computer; The operation process of the acquisition system from the controller includes: receiving the analog signal from the first type of sensor, determining whether the sensor is faulty based on the analog signal, and if so, invalidating or setting the data to 0 and issuing a fault alarm; otherwise, converting the data acquired by the sensor into a CAN data packet and sending the CAN data packet to the acquisition system main controller. The working process of the main controller of the acquisition system includes: determining the data source; if the data source is an analog signal from a sensor, determining whether the sensor is faulty; if so, invalidating the data or setting it to 0 and issuing a fault alarm; otherwise, performing analog-to-digital conversion; if the data source is a CAN data packet transmitted from the controller by the acquisition system, parsing the CAN data packet into an analog signal and performing analog-to-digital conversion, determining whether the data after analog-to-digital conversion exceeds the calibration range; if so, issuing an over-limit alarm.

2. The control device for a boring machine according to claim 1, characterized in that The industrial control computer is used to send the control parameters to the main controller of the acquisition system.

3. The control device for the boring machine according to claim 1, wherein The data acquisition system controller is used to package the measurement parameters, the action parameters, and the engine status parameters into a whole machine status data packet, and send the whole machine status data packet to the industrial control computer; Accordingly, the industrial control computer is used to parse the whole machine status data packet into the measurement parameters, the action parameters and the engine status parameters, and input the measurement parameters, the action parameters and the engine status parameters into the AI ​​prediction model to obtain the control parameters.

4. The control device for a boring machine according to claim 3, wherein Also includes: The communication terminal connected to the data acquisition system controller; Correspondingly, the acquisition system controller is also used to send the whole machine status data packet to the communication terminal, so that the communication terminal can upload the whole machine status data packet to the cloud computer.

5. The control device for a boring machine according to claim 4, wherein The cloud computer runs AI prediction models that are yet to be trained or validated.

6. The control device for a boring machine according to claim 1, wherein The AI ​​prediction model includes: The electromechanical-hydraulic integration model is used to predict the control parameters of the actuators and the main hoist. And / or, engine models, used to predict the control parameters of the transmitter; And / or, a power head model, used to predict the control parameters of the power head motor.

7. A data transmission method, characterized in that, The data transmission method of the acquisition system controller applied in the control device of the drilling machinery according to any one of claims 1 to 6 includes: It receives engine status parameters, drilling machinery motion parameters, and measurement data collected by sensors; The engine status parameters, the action parameters, and the measurement data are packaged into a whole machine status data package; The overall machine status data packet is sent to the industrial control computer so that the industrial control computer can use the AI ​​prediction model to calculate the control parameters corresponding to the overall machine status data packet; The system receives control parameters returned by the industrial computer and sends the control parameters to the overall controller to control the drilling machinery.

8. A data transmission system, characterized by A data acquisition system controller is applied in the control device of the drilling machinery according to any one of claims 1 to 6, wherein the data transmission system comprises: The data receiving module is used to receive engine status parameters, drilling machinery motion parameters, and measurement data collected by sensors. The data packaging module is used to package the engine status parameters, the action parameters, and the measurement data into a whole machine status data package; The data transmission module is used to send the whole machine status data packet to the industrial control computer, so that the industrial control computer can use the AI ​​prediction model to calculate the control parameters corresponding to the whole machine status data packet; The data forwarding module is used to receive the control parameters returned by the industrial control computer and send the control parameters to the whole machine controller so as to control the drilling machine.

9. A storage medium, characterized by The storage medium stores computer-executable instructions, which, when loaded and executed by a processor, implement the steps of the data transmission method as described in claim 7 above.

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