Fully mechanized coal mining face three-machine driving method, device, equipment and medium

Abstract

The invention relates to the field of data processing, in particular to a fully mechanized coal mining face three-machine driving method, device and equipment and a medium. The method comprises the steps that an initial model of three machines of a current fully mechanized coal mining face is obtained, operation data are collected in real time, the data are synchronized into the model to achieve dynamic updating, and therefore the virtual three-machine state is accurately simulated, a solid foundation is provided for subsequent generation of a scientific and reasonable three-machine cooperation strategy, three machines are driven based on the strategy, and the efficiency of three-machine cooperation is improved. The three machines can be highly coordinated in the operation process, the overall operation efficiency of the fully mechanized coal mining face is effectively improved, the system stability is enhanced, the fault risk caused by equipment incoordination is reduced, and the reliability of three-machine collaborative operation is improved.

Description

Technical Field

[0001] The present application relates to the field of data processing, and in particular to a three-machine driving method, device, equipment and medium for a fully mechanized mining face. Background Art

[0002] Three-machine drive technology for fully mechanized mining faces is a crucial component of coal mining. It primarily involves the coordinated operation of shearers, face conveyors, and hydraulic supports. With the continuous advancement of coal mining technology, the efficiency and safety of these three-machine collaborations directly impact the overall profitability of coal mine production. Traditional three-machine drive technology for fully mechanized mining faces has enhanced the automation level of coal mining through mechanical structure optimization and control strategy improvements, providing important support for improving coal mine production efficiency and reducing manual intervention. Technological developments in this area have not only driven the modernization of the coal mining industry but also played a key role in ensuring miner safety and improving resource utilization.

[0003] In existing technology, achieving coordinated operation of three machines typically involves using sensors to collect operational data from each device and independently controlling it using pre-set control logic. This method monitors the operating status of each device and adjusts its operating parameters according to pre-set rules, aiming to achieve coordinated operation. This approach is widely used in fully mechanized mining faces across various coal mines and is a common technical measure within the industry.

[0004] However, the above methods have obvious shortcomings, especially when faced with complex working conditions. It is difficult to generate the optimal coordination strategy based on the actual operating conditions, resulting in low equipment operating efficiency, increased energy consumption, and potential safety hazards. Therefore, there is an urgent need for a method that can solve the problem of insufficient accuracy of three-machine coordination to improve the reliability of three-machine collaborative operation. Summary of the Invention

[0005] In order to improve the reliability of the three-machine collaborative operation, the present application provides a three-machine driving method, device, equipment and medium for a fully mechanized mining working face.

[0006] In the first aspect, the present application provides a three-machine driving method for a fully mechanized mining face, which adopts the following technical solution: A three-machine driving method for a fully mechanized mining face, comprising: Obtaining the initial models of the three machines in the current fully mechanized mining face, and collecting the operating data corresponding to the three machines in the current fully mechanized mining face in real time; Synchronizing the operating data into the initial model to obtain a dynamically updated virtual three-machine state; A three-machine coordination strategy is generated based on the virtual three-machine state, and the three machines in the current fully mechanized mining face are driven based on the three-machine coordination strategy.

[0007] By adopting the above technical solution, by obtaining the initial model of the three machines in the current fully mechanized mining face and collecting operating data in real time, the data is synchronized to the model for dynamic updating, thereby accurately simulating the virtual three-machine status. This provides a solid foundation for the subsequent generation of a scientific and reasonable three-machine coordination strategy. Driving the three machines based on this strategy can enable the three machines to achieve high coordination and cooperation during operation, effectively improving the overall operating efficiency of the fully mechanized mining face, enhancing system stability, reducing the risk of failure due to equipment incoordination, and improving the reliability of the three-machine collaborative operation.

[0008] In a possible implementation, before obtaining the initial models of the three machines in the current fully mechanized mining face, the following steps are further included: Obtain the equipment models of the three machines of the current fully mechanized mining face, and obtain the component sub-models corresponding to the equipment models; Assembling the component sub-models to obtain a device model; Based on the equipment model, a physical model and a behavioral model of the three machines of the current fully mechanized mining face are established; Based on the physical model and the behavioral model, an initial model of the three machines in the current fully mechanized mining face is obtained.

[0009] In a possible implementation, a physical model of the three machines in the current fully mechanized mining face is established based on the equipment model, including: Based on the operation data, a physical model of the shearer, a physical model of the scraper conveyor, and a physical model of the hydraulic support of the three machines of the current fully mechanized mining face is established; Based on the physical model of the coal mining machine, the physical model of the scraper conveyor and the physical model of the hydraulic support, the physical models of the three machines of the current fully mechanized mining working face are obtained.

[0010] In a possible implementation, based on the equipment model, a behavior model of the three machines in the current fully mechanized mining face is established, including: Obtaining a current driving strategy for the three machines of the current fully mechanized mining face, wherein the current driving strategy includes a driving sub-strategy corresponding to each component; Based on the current driving strategy, a behavior model of the three machines in the current fully mechanized mining face is established.

[0011] In one possible implementation, the operating data includes motor current, vibration spectrum, traction force, coal flow weight, and travel displacement, and generating a three-machine coordination strategy based on the virtual three-machine states includes: Obtaining first operating sub-data and second operating sub-data corresponding to the three machines of the current fully mechanized mining face in a current cycle, wherein the first operating sub-data includes motor current and vibration spectrum, and the second operating sub-data includes motor current and traction force; Integrating the first operation sub-data based on Kalman filtering to obtain multi-source operation sub-data; Determine, based on the multi-source operation sub-data, a coal seam region corresponding to the three machines of the current fully mechanized mining face, and determine a coal cutting mode corresponding to the coal seam region, wherein the coal seam region is a stable region or other region, and the coal cutting mode is a bidirectional coal cutting model or a unidirectional coal cutting mode; Determining the current coal and rock hardness corresponding to the three machines of the current fully mechanized mining face based on the second operation sub-data, and determining the traction speed of the three machines of the current fully mechanized mining face based on the current coal and rock hardness; Obtaining the coal quantity distribution of the current coal mine, and determining the chain speeds of the three machines of the current fully mechanized mining face based on the coal quantity distribution and the coal flow weight; Determine the support moving step distances corresponding to the three machines in the current fully mechanized mining face based on the walking displacement; A three-machine coordination strategy is generated based on the coal cutting mode, the traction speed, the chain speed, and the support moving step.

[0012] In a possible implementation, the operation data further includes a current traction speed and a current cutting time. The determining of the support movement step distances corresponding to the three machines of the current fully mechanized mining face based on the walking displacement includes: Obtain the drum inclination angles corresponding to the three machines in the current fully mechanized mining face; Based on the current cutting time, the drum inclination angle, and the travel displacement, the theoretical cutting depth corresponding to the three machines of the current fully mechanized mining working face is calculated; Based on the theoretical cutting depth, the support moving step distances corresponding to the three machines in the current comprehensive mining working face are determined.

[0013] In the second aspect, the present application provides a three-machine drive device for a fully mechanized mining face, which adopts the following technical solution: A three-machine driving device for a fully mechanized mining face, comprising: The model acquisition module is used to obtain the initial model of the three machines in the current fully mechanized mining face and collect the operating data corresponding to the three machines in the current fully mechanized mining face in real time; A synchronization module, configured to synchronize the operating data with the initial model to obtain a dynamically updated virtual three-machine state; A generation module is used to generate a three-machine coordination strategy based on the virtual three-machine state, and drive the three machines of the current fully mechanized mining face based on the three-machine coordination strategy.

[0014] In a possible implementation, the apparatus further includes: A model acquisition module is used to obtain the equipment models of the three machines in the current fully mechanized mining face and obtain the component sub-models corresponding to the equipment models; An assembly module, used for assembling the component sub-models to obtain a device model; An establishment module is used to establish a physical model and a behavior model of the three machines of the current fully mechanized mining face based on the equipment model; An obtaining module is used to obtain the initial model of the three machines of the current fully mechanized mining face based on the physical model and the behavioral model.

[0015] In a third aspect, the present application provides an electronic device, which adopts the following technical solution: An electronic device, comprising: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the method described in any one of the first aspects above.

[0016] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium, comprising: storing a computer program that can be loaded by a processor and execute any one of the methods described in the first aspect above.

[0017] In summary, this application has the following beneficial technical effects: By obtaining the initial model of the three machines in the current fully mechanized mining face and collecting operating data in real time, the data is synchronized to the model for dynamic updating, thereby accurately simulating the status of the three virtual machines. This provides a solid foundation for the subsequent generation of a scientific and reasonable three-machine coordination strategy. Driving the three machines based on this strategy can enable the three machines to achieve a high degree of coordination during operation, effectively improving the overall operating efficiency of the fully mechanized mining face, enhancing system stability, reducing the risk of failures caused by equipment incoordination, and improving the reliability of the three-machine collaborative operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a flow chart of a three-machine driving method for a fully mechanized mining face provided in an embodiment of the present application; Figure 2 This is a block diagram of a three-machine drive device for a fully mechanized mining face provided by an embodiment of the present application; Figure 3 This is a schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0019] The following is combined with Figure 1 -Attached Figure 3 This application is described in further detail.

[0020] To make the purpose, technical solutions, and advantages of the embodiments of this application more clear, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0021] In order to facilitate understanding of the technical solutions proposed in this application, several elements that will be introduced in the description of this application are first introduced here. It should be understood that the following introduction is only for the convenience of understanding these elements, so as to understand the content of the embodiments of this application, and does not necessarily cover all possible situations.

[0022] The "three machines" of a fully mechanized mining face refer to the shearer, face conveyor, and hydraulic supports. These three types of equipment work together to form the core production system of a fully mechanized mining face. Specifically, the shearer is responsible for cutting and dropping coal from the coal seam, stripping it from the coal wall using rollers or planers. The shearer rides on the face conveyor and travels back and forth along guide rails. The face conveyor (face conveyor) transports the coal dropped by the shearer to the end of the face (transfer machine or belt conveyor), serves as the shearer's travel track, and provides a support for the hydraulic supports. The hydraulic supports support the roof, preventing it from collapsing and ensuring a safe working space. The support equipment uses jacks to propel the face conveyor and itself forward (a "push-and-slide support"). Automation: An electro-hydraulic control system enables automated follow-up (linked to the shearer).

[0023] The synergistic effect of the "three machines" in the comprehensive mining working face: the coal mining machine is responsible for breaking and loading coal, the scraper conveyor is responsible for transporting coal, and the hydraulic support is responsible for supporting the roof. The three work closely together to realize the mechanized operations of coal mining, coal transportation and support, greatly improving the production efficiency and safety of the coal mine.

[0024] In the intelligent fully mechanized mining face, the three machines work together under the unified control of an underground centralized control center. This center collects, processes, and analyzes data from various sensors, centrally controlling and monitoring the fully mechanized mining equipment and ensuring efficient and stable operation of the entire face.

[0025] The embodiment of the present application provides a three-machine driving method for a fully mechanized mining face, such as Figure 1As shown, the method provided in the embodiment of the present application is performed by an electronic device, which can be a server or a terminal device, wherein the server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smartphone, a tablet computer, a laptop computer, a desktop computer, etc., but is not limited thereto. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, which is not limited in the embodiment of the present application. The method includes steps S101 to S103, wherein: Step S101: obtain the initial models of the three machines in the current fully mechanized mining face, and collect the corresponding operating data of the three machines in the current fully mechanized mining face in real time.

[0026] Among them, operation data refers to the various parameter data reflecting the working status and performance of the equipment collected in real time by various sensors installed on the equipment during the actual operation of the three machines in the comprehensive mining working face. These data can intuitively reflect the equipment's operating conditions, workload and other information.

[0027] Specifically, the electronic device is connected to the three machines in the current fully mechanized mining face via wired or wireless communication. The electronic device stores a database corresponding to the three machines in the current fully mechanized mining face, which contains 3D geometric models of the three machines. From this database, the electronic device retrieves the 3D geometric models of the three machines (coal shearer, scraper conveyor, and hydraulic support) and physical models containing information such as the equipment's operating principles and mechanical properties, and combines them to form an initial model. Simultaneously, the electronic device establishes communication with various sensors installed on the three machines (such as temperature sensors, pressure sensors, displacement sensors, and speed sensors). The electronic device collects real-time operating parameters of the equipment at a set sampling frequency (e.g., collecting data once per second). These data include the shearer's cutting motor current, traction speed, and drum speed; the scraper conveyor's chain speed, motor power, and coal flow weight; and the hydraulic support's travel displacement.

[0028] Step S102: Synchronize the operating data to the initial model to obtain the dynamically updated virtual three-machine state.

[0029] Real-time collected operational data is input into the corresponding parameter nodes of the initial model according to pre-defined data mapping rules. For example, the current data of the shearer's cutting motor is input into the parameter variable representing the cutting motor current in the model. By updating the relevant parameters in real time, the model can reflect the current actual operating status of the equipment. Through calculation and simulation, the model generates a dynamically updated virtual three-machine status, such as the equipment's real-time position, posture, workload, and other status information, and displays it visually on the electronic device screen.

[0030] Step S103: Generate a three-machine coordination strategy based on the virtual three-machine status, and drive the three machines in the current fully mechanized mining face based on the three-machine coordination strategy.

[0031] Among them, the three-machine collaborative strategy includes equipment operating parameter adjustment, action sequence planning, and mutual coordination and cooperation.

[0032] Specifically, the dynamically updated virtual states of the three machines are analyzed and processed. Using pre-defined algorithms and rules (such as those based on optimizing equipment operating efficiency and ensuring safety), the system comprehensively considers the interrelationships and workflows among the three machines to generate a three-machine coordination strategy. For example, the optimal operating speed of the scraper conveyor is determined based on the shearer's coal cutting speed and position, as well as the scraper conveyor's coal flow and transport capacity. The hydraulic support's movement sequence and step size are planned based on the hydraulic support's current support status and the shearer's forward direction. The electronic equipment then transmits the generated three-machine coordination strategy to the control systems of the three machines in the fully mechanized mining face via an industrial network or other communication method, driving the three machines to operate according to the coordination strategy, achieving efficient collaborative operation among the equipment.

[0033] Specifically, in this embodiment, when the operating data includes motor current, vibration spectrum, traction force, coal flow weight, and travel displacement, a three-machine coordination strategy is generated based on the virtual three-machine states, including: Obtain the first and second operating sub-data corresponding to the current cycle of the three machines in the current fully mechanized mining face. The first operating sub-data includes the motor current and vibration spectrum, and the second operating sub-data includes the motor current and traction force. Integrate the first operating sub-data based on Kalman filtering to obtain multi-source operating sub-data; Based on multi-source operation sub-data, the coal seam area corresponding to the three machines in the current fully mechanized mining face is determined, and the corresponding coal cutting mode is determined. The coal seam area is a stable area or other area, and the coal cutting mode is a two-way coal cutting model or a one-way coal cutting model. Based on the second operation sub-data, determine the current coal and rock hardness corresponding to the three machines in the current fully mechanized mining face, and determine the traction speed of the three machines in the current fully mechanized mining face based on the current coal and rock hardness; Obtain the current coal quantity distribution of the coal mine and determine the chain speed of the three machines in the current fully mechanized mining face based on the coal quantity distribution and coal flow weight; Determine the support moving step distances corresponding to the three machines in the current fully mechanized mining face based on the walking displacement; A three-machine coordination strategy is generated based on the coal cutting mode, traction speed, chain speed, and support movement step.

[0034] Among them, the current cycle is the period from the start of work of the three machines in the current fully mechanized mining face to the current moment.

[0035] Through real-time communication with various sensors installed on the three machines in the fully mechanized mining face, the system reads relevant data from the sensor data acquisition system within a set period (e.g., every minute). For the first sub-data segment, motor current data is obtained from the current sensor, and vibration spectrum data is obtained from the vibration sensor. These data are then categorized and stored. For the second sub-data segment, motor current data is obtained from the current sensor, and traction force data is obtained from the traction force detection device. These data are also categorized and stored for subsequent processing and analysis.

[0036] The Kalman filter algorithm is then used to process the collected first operating sub-data (motor current and vibration spectrum). First, a state prediction model is established based on historical motor current and vibration spectrum data and current measurement data to predict the motor current and vibration spectrum states at the next moment. The currently measured motor current and vibration spectrum data are then compared with the predicted values. The Kalman gain is then used to adjust the predicted values to more closely approximate the actual measured values. After multiple iterative calculations, the motor current and vibration spectrum data are fused to remove noise interference, resulting in more accurate and reliable multi-source operating sub-data.

[0037] Analyze multi-source operating sub-data (data fused from motor current and vibration spectrum). Based on a pre-established relationship model between motor current, vibration spectrum, and coal seam characteristics (for example, stable motor current and a vibration spectrum within a certain range indicate a relatively stable coal seam; large motor current fluctuations and an abnormal vibration spectrum, i.e., outside the corresponding range, indicate potential changes or instability in the coal seam), determine whether the coal seam region currently occupied by the three machines in the fully mechanized mining face is stable or in another region (such as a fault region or an area with significant variations in coal seam thickness). Then, based on the determined coal seam region, determine the corresponding coal cutting mode. Specifically, if the region is stable, a bidirectional coal cutting mode is selected to improve mining efficiency; if the region is otherwise, a unidirectional coal cutting mode is selected to better adapt to coal seam variations, ensuring equipment safety and mining quality.

[0038] Furthermore, the second operating sub-data (motor current and traction force data) is analyzed. Based on a pre-established relationship model between motor current, traction force, and coal rock hardness (for example, the harder the coal rock, the higher the motor current and the greater the traction force required during shearer cutting), the preset standard motor current and traction force corresponding to the three machines in the current fully mechanized mining face are obtained. The current coal rock hardness is inferred by calculating the average of the first ratio of the current motor current to the preset standard motor current and the second ratio of the traction force to the preset standard traction force. Based on the determined coal rock hardness and the preset hardness-to-traction speed conversion rule, the traction speed appropriate for the current coal rock hardness is determined. If the coal rock hardness is high, the traction speed is appropriately reduced to ensure cutting quality and equipment safety. If the coal rock hardness is low, the traction speed can be appropriately increased to improve coal mining efficiency.

[0039] The current coal distribution information for the mine is obtained from the database corresponding to the three machines in the current fully mechanized mining face, and coal flow weight data is obtained from the coal flow weight sensors installed on the scraper conveyors. Analysis is then performed based on the coal distribution and coal flow weight data. Specifically, the difference in coal distribution between the current position of the three machines in the fully mechanized mining face and their expected positions at the next moment (which can be positive or negative) is calculated. The coal distribution corresponding to the current position is added to the difference in coal distribution to obtain the coal distribution corresponding to the next moment. The ratio of the coal distribution corresponding to the next moment to the coal distribution corresponding to the current position is calculated to obtain the coal ratio. The product of this coal ratio and the coal flow weight is calculated to obtain the estimated coal flow weight corresponding to the next moment. The chain speed of the three machines in the current fully mechanized mining face is determined using the preset relationship between coal flow weight and chain speed and the estimated coal flow weight.

[0040] Furthermore, the support movement pitches for the three machines in the current fully mechanized mining face are determined based on their travel displacements. A three-machine coordination strategy is generated based on the coal cutting mode, hauling speed, chain speed, and support movement pitches.

[0041] Specifically, in this embodiment, the operation data also includes the current traction speed and the current cutting time. The support moving step distance corresponding to the three machines in the current fully mechanized mining face is determined based on the walking displacement, including: Get the drum inclination angles corresponding to the three machines in the current fully mechanized mining face; Based on the current cutting time, drum inclination, and travel displacement, the theoretical cutting depth corresponding to the three machines in the current fully mechanized mining face is calculated; Based on the theoretical cutting depth, determine the support moving step distance corresponding to the three machines in the current fully mechanized mining face.

[0042] The drum inclination angle refers to the tilt of the shearer drum relative to a reference plane (such as the horizontal plane). This angle affects the shearer's cutting performance. Different drum inclination angles are suitable for different coal seam conditions and are a key parameter for calculating theoretical cutting depth.

[0043] The system establishes a communication link with the angle sensor installed on the shearer drum to read drum inclination data in real time. The angle sensor accurately measures the drum's tilt relative to the horizontal or other reference plane and transmits this data as an electrical signal to the electronic device. The electronic device receives and interprets this signal, converting it into actual angle values and storing it in the device's database for subsequent calculations.

[0044] The current cutting duration data (i.e., the duration of the shearer's current cutting operation), drum inclination data, and travel displacement data (the distance the shearer has moved along the face during the current cutting period) are retrieved from the database corresponding to the three machines in the current fully mechanized mining face. Calculations are performed based on a pre-established mathematical model and formula (which comprehensively considers the shearer's operating principle and the relationship between drum inclination, travel displacement, and cutting duration). For example, considering that drum inclination affects the vertical depth of cutting and travel displacement reflects the horizontal distance traveled, the actual cutting depth achieved by the shearer during this period can be calculated in combination with the cutting duration, thereby calculating the theoretical cutting depth.

[0045] Furthermore, based on the calculated theoretical cutting depth data, combined with pre-set coal mining process rules and support movement principles (for example, to ensure that the hydraulic supports can promptly and effectively support the newly exposed roof, the support movement step distance is usually matched with or proportional to the theoretical cutting depth of the coal mining machine), the support movement step distance corresponding to the three machines in the current fully mechanized mining face is determined. The electronic equipment performs analysis and decision-making within its internal logic judgment module. If the theoretical cutting depth is small, a smaller support movement step distance may be selected according to the rules; if the theoretical cutting depth is large, a larger support movement step distance is determined accordingly. After the support movement step distance is determined, this parameter information is transmitted to the hydraulic support control system, so that the hydraulic support can move according to the determined step distance.

[0046] An embodiment of the present application provides a three-machine driving method for a comprehensive mining working face. By obtaining the initial model of the three machines of the current comprehensive mining working face and collecting operating data in real time, the data is synchronized to the model for dynamic updating, thereby accurately simulating the virtual three-machine state. This provides a solid foundation for the subsequent generation of a scientific and reasonable three-machine coordination strategy. Driving the three machines based on this strategy can enable the three machines to achieve high coordination and cooperation during operation, effectively improving the overall operating efficiency of the comprehensive mining working face, enhancing system stability, reducing the risk of failure due to equipment incoordination, and improving the reliability of the three-machine collaborative operation.

[0047] A possible implementation of the embodiment of the present application further includes, before the above step S101 of obtaining the initial models of the three machines of the current fully mechanized mining face: Get the equipment models of the three machines in the current fully mechanized mining face, and get the component sub-models corresponding to the equipment models; Assemble the component sub-models to obtain the equipment model; Based on the equipment model, the physical model and behavior model of the three machines in the current fully mechanized mining face are established; Based on the physical model and behavioral model, the initial model of the three machines in the current fully mechanized mining face is obtained.

[0048] Among them, the component sub-models include coal mining machine model, scraper conveyor model and hydraulic support model.

[0049] The device model information for each of the three machines in the fully mechanized mining face (coal shearer, scraper conveyor, and hydraulic support) is retrieved from the corresponding database. Based on these equipment models, the device then accesses a database containing submodels for each type of equipment component. This database is categorized by equipment model, and the electronic device accurately matches and extracts the submodels corresponding to the current equipment model, namely the shearer model, scraper conveyor model, and hydraulic support model.

[0050] Furthermore, using 3D modeling software, the acquired component sub-models are combined according to the actual structure and assembly relationships of the equipment to form an equipment model. Based on the geometric and physical parameters of each component in the equipment model, combined with relevant principles such as mechanics and kinematics, mathematical modeling methods are used to describe the physical behavior of the equipment under different operating conditions. Specifically, for coal mining machines, a cutting force model is established based on the structure and parameters of the cutting unit, and a traction force model is established based on the transmission method of the traction unit. For scraper conveyors, a tension model is established based on the mechanical properties of the scraper chain, and a coal flow transportation model is established based on the movement laws of the coal flow. For hydraulic supports, a support force model is established based on the hydraulic principles of the columns and jacks.

[0051] To build the behavioral model, we capture the equipment's operational procedures and control logic, simulating its various behaviors during actual operation. For example, we define control strategies for different shearing methods (unidirectional and bidirectional), the operational logic for starting, stopping, and regulating the speed of a scraper conveyor, and the sequence and conditions for hydraulic support movements, such as moving, lowering, and raising the support. Through these analyses and settings, we construct a behavioral model that accurately reflects the equipment's actual operating behavior.

[0052] A possible implementation of the embodiment of the present application is to establish a physical model of the three machines of the current fully mechanized mining face based on the equipment model in the above embodiment, including: Based on the operation data, the physical models of the shearer, scraper conveyor and hydraulic support of the three machines in the current fully mechanized mining face are established; Based on the physical model of the coal mining machine, the physical model of the scraper conveyor and the physical model of the hydraulic support, the physical model of the three machines in the current fully mechanized mining face is obtained.

[0053] Specifically, the physical model of the coal mining machine is established by classifying and organizing the operating data of the coal mining machine. These data include the current, voltage, and power of the cutting motor, the speed and torque of the traction motor, the cutting force and load of the drum, etc. Based on this data, a cutting dynamics model is established using mechanical principles and mathematical methods to analyze the interaction between the pick and the coal rock, and determine the magnitude and direction of the cutting force. At the same time, based on the operating data of the traction system, a traction dynamics model is established to describe the movement characteristics of the coal mining machine on the working face. Taking into account the structural parameters of the coal mining machine, such as the body mass and the center of gravity position, a complete physical model of the coal mining machine is constructed. This model can simulate the operating status of the coal mining machine under different working conditions.

[0054] Establishing a physical model of the scraper conveyor: Based on the acquired scraper conveyor operating data, such as motor power and current, scraper chain tension and speed, coal flow rate, and stacking height, a coal flow model is established by analyzing the operating data and applying the principles of fluid mechanics and mechanical dynamics to describe the flow characteristics and resistance distribution of the coal flow on the scraper conveyor. Simultaneously, based on the mechanical properties of the scraper chain, a scraper chain tension model is established to calculate the tension changes in the scraper chain at different positions and operating conditions. Combined with the scraper conveyor's structural parameters, such as chute size and chain pitch, a physical model of the scraper conveyor is constructed to simulate the scraper conveyor's operation and performance.

[0055] Establishing a physical model of the hydraulic support: Based on the acquired operating data of the hydraulic support, including the pressure and expansion of the columns, the thrust and displacement of the jacks, and the load-bearing capacity of the support. Based on the operating data, applying the principles of hydraulic transmission and structural mechanics, a mechanical model of the columns is established to analyze the stress conditions of the columns under different support states. At the same time, based on the working characteristics of the jacks, a dynamic model of the jacks is established to describe the jacks' movement process and response characteristics. Taking into account the structural parameters of the hydraulic support, such as the length and width of the top beam and the angle of the shield beam, a physical model of the hydraulic support is constructed to simulate the support performance and stability of the hydraulic support.

[0056] Furthermore, the established physical models of the shearer, scraper conveyor, and hydraulic support were integrated. By establishing corresponding coupling relationships and constraints, the three models were organically combined to form a holistic physical model. This model can fully simulate the coordinated operation of the three machines in a fully mechanized mining face, including aspects such as mechanical transmission and motion coordination between the devices.

[0057] One possible implementation of the embodiment of the present application is to establish a behavior model of the three machines in the current fully mechanized mining face based on the equipment model in the above embodiment, including: Obtain the current driving strategy of the three machines in the current fully mechanized mining face. The current driving strategy includes the driving sub-strategies corresponding to each component. Based on the current driving strategy, the behavioral model of the three machines in the current fully mechanized mining face is established.

[0058] The current drive strategy refers to the combination of strategies currently used by the three machines in the fully mechanized mining face to control their operation and motion. Drive sub-strategies are components of the current drive strategy. These sub-strategies are specific drive control strategies developed for different components or functional modules of each of the three machines in the fully mechanized mining face, such as the shearer drum lift control strategy and the scraper conveyor speed regulation strategy. These strategies are independent yet interrelated, forming the overall drive strategy for each device.

[0059] The electronic device establishes a connection with the control system or operating terminal of the fully mechanized mining face and reads the current drive strategy information for the three machines in the fully mechanized mining face from the system's control parameter setting module or operation record database. For the shearer, the electronic device obtains driver sub-strategies such as its cutting mode (e.g., one-way cutting, two-way cutting), traction speed control strategy (automatically adjusted based on coal seam thickness and hardness or manually set), and drum lifting control strategy. For the scraper conveyor, the electronic device obtains driver sub-strategies such as its start and stop control logic, speed regulation strategy (automatically adjusted based on coal flow or operating at a fixed speed), and overload protection strategy. For the hydraulic support, the electronic device obtains driver sub-strategies such as its frame movement sequence strategy (e.g., sequential frame movement, grouped frame movement), pressure control strategy for lowering and raising the frame, and guard plate movement strategy. The electronic device integrates and categorizes these driver sub-strategies for future use.

[0060] Based on the current drive strategy, the behavior of the three machines in the fully mechanized mining face is modeled using logic modeling and state machine methods. For the shearer, a state transition model is established based on the cutting mode and traction speed control strategy, describing the behavior logic and state changes during different operating phases (such as starting, cutting, pausing, and reversing). For the scraper conveyor, an operating state model is established based on its start, stop, and speed regulation strategies, simulating its operation under different coal flow rates and operating conditions. For the hydraulic support, an action state model is established based on strategies such as the frame movement sequence and pressure control, demonstrating the state changes and time series during the hydraulic support lowering, moving, and raising operations. Furthermore, the electronic device links and integrates the behavioral models of these three devices to construct a complete behavioral model of the three machines in the current fully mechanized mining face. This model can simulate the coordinated behavior and responses of the three machines in actual operation by inputting different operating parameters and control commands.

[0061] The above embodiment introduces a three-machine driving method for a fully mechanized mining face from the perspective of a method flow. The following embodiment introduces a three-machine driving device for a fully mechanized mining face from the perspective of a virtual module or a virtual unit. For details, please refer to the following embodiment.

[0062] See also Figure 2 The three-machine driving device 20 of the fully mechanized mining face may specifically include: a model acquisition module 201, a synchronization module 202 and a generation module 203, wherein: A three-machine driving device 20 for a fully mechanized mining face includes: The model acquisition module 201 is used to obtain the initial model of the three machines in the current fully mechanized mining face and collect the corresponding operating data of the three machines in the current fully mechanized mining face in real time; Synchronization module 202, used to synchronize the operation data to the initial model to obtain the dynamically updated virtual three-machine state; The generation module 203 is used to generate a three-machine coordination strategy based on the virtual three-machine status, and drive the three machines in the current fully mechanized mining face based on the three-machine coordination strategy.

[0063] In a possible implementation of the embodiment of the present application, the apparatus further includes: The model acquisition module is used to obtain the equipment models of the three machines in the current fully mechanized mining face and obtain the component sub-models corresponding to the equipment models; The assembly module is used to assemble the component sub-models to obtain the equipment model; Establish a module for building the physical model and behavior model of the three machines in the current fully mechanized mining face based on the equipment model; The module is used to obtain the initial model of the three machines in the current fully mechanized mining face based on the physical model and the behavioral model.

[0064] In a possible implementation of the embodiment of the present application, when the establishment module establishes the physical model of the three machines of the current fully mechanized mining face based on the equipment model, it is specifically used to: Based on the operation data, the physical models of the shearer, scraper conveyor and hydraulic support of the three machines in the current fully mechanized mining face are established; Based on the physical model of the coal mining machine, the physical model of the scraper conveyor and the physical model of the hydraulic support, the physical model of the three machines in the current fully mechanized mining face is obtained.

[0065] In one possible implementation of the embodiment of the present application, when establishing a behavior model of the three machines in the current fully mechanized mining face based on the equipment model, the module is specifically used to: Obtain the current driving strategy of the three machines in the current fully mechanized mining face. The current driving strategy includes the driving sub-strategies corresponding to each component. Based on the current driving strategy, the behavioral model of the three machines in the current fully mechanized mining face is established.

[0066] In one possible implementation of the embodiment of the present application, the operating data includes motor current, vibration spectrum, traction force, coal flow weight, and travel displacement. When generating the three-machine coordination strategy based on the virtual three-machine states, the generation module 203 is specifically configured to: Obtain the first and second operating sub-data corresponding to the current cycle of the three machines in the current fully mechanized mining face. The first operating sub-data includes the motor current and vibration spectrum, and the second operating sub-data includes the motor current and traction force. Integrate the first operating sub-data based on Kalman filtering to obtain multi-source operating sub-data; Based on multi-source operation sub-data, the coal seam area corresponding to the three machines in the current fully mechanized mining face is determined, and the corresponding coal cutting mode is determined. The coal seam area is a stable area or other area, and the coal cutting mode is a two-way coal cutting model or a one-way coal cutting model. Based on the second operation sub-data, determine the current coal and rock hardness corresponding to the three machines in the current fully mechanized mining face, and determine the traction speed of the three machines in the current fully mechanized mining face based on the current coal and rock hardness; Obtain the current coal quantity distribution of the coal mine and determine the chain speed of the three machines in the current fully mechanized mining face based on the coal quantity distribution and coal flow weight; Determine the support moving step distances corresponding to the three machines in the current fully mechanized mining face based on the walking displacement; A three-machine coordination strategy is generated based on the coal cutting mode, traction speed, chain speed, and support movement step.

[0067] In one possible implementation of the embodiment of the present application, the operation data further includes the current traction speed and the current cutting time. When the generation module 203 determines the support moving step distance corresponding to the three machines of the current fully mechanized mining face based on the walking displacement, it is specifically used to: Get the drum inclination angles corresponding to the three machines in the current fully mechanized mining face; Based on the current cutting time, drum inclination, and travel displacement, the theoretical cutting depth corresponding to the three machines in the current fully mechanized mining face is calculated; Based on the theoretical cutting depth, determine the support moving step distance corresponding to the three machines in the current fully mechanized mining face.

[0068] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0069] See also Figure 3 , the embodiment of the present application also introduces an electronic device from the perspective of a physical device, such as Figure 3 As shown, Figure 3 The electronic device 300 shown includes a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, for example, via a bus 302. Optionally, the electronic device 300 may further include a transceiver 304. It should be noted that in actual applications, the number of transceivers 304 is not limited to one, and the structure of the electronic device 300 does not constitute a limitation on the embodiments of the present application.

[0070] Processor 301 can be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic device, transistor logic device, hardware component, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 301 can also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0071] Bus 302 may include a path for transmitting information between the above components. Bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. Bus 302 may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, Figure 3Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0072] The memory 303 may be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0073] The memory 303 is used to store application code for executing the solution of the present application, and the execution is controlled by the processor 301. The processor 301 is used to execute the application code stored in the memory 303 to implement the content shown in the above method embodiment.

[0074] Among them, electronic devices include but are not limited to: mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc., and can also be servers, etc. Figure 3 The electronic device shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0075] An embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding contents of the aforementioned method embodiment.

[0076] It should be understood that although the steps in the flowcharts of the accompanying drawings are shown in sequence as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some of the steps in the flowcharts of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0077] The above are only some of the implementation methods of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A three-machine driving method for a fully mechanized mining face, characterized in that: include: Obtaining the initial models of the three machines in the current fully mechanized mining face, and collecting the operating data corresponding to the three machines in the current fully mechanized mining face in real time; Synchronizing the operating data into the initial model to obtain a dynamically updated virtual three-machine state; A three-machine coordination strategy is generated based on the virtual three-machine state, and the three machines in the current fully mechanized mining face are driven based on the three-machine coordination strategy.

2. The three-machine driving method for fully mechanized mining working face according to claim 1 is characterized in that: Before obtaining the initial model of the three machines in the current fully mechanized mining face, the following steps are also required: Obtain the equipment models of the three machines of the current fully mechanized mining face, and obtain the component sub-models corresponding to the equipment models; Assembling the component sub-models to obtain a device model; Based on the equipment model, a physical model and a behavioral model of the three machines of the current fully mechanized mining face are established; Based on the physical model and the behavioral model, an initial model of the three machines in the current fully mechanized mining face is obtained.

3. The three-machine driving method for fully mechanized mining working face according to claim 2 is characterized in that: The physical model of the three machines of the current fully mechanized mining face is established based on the equipment model, including: Based on the operating data, a physical model of the shearer, a physical model of the scraper conveyor, and a physical model of the hydraulic support of the three machines of the current fully mechanized mining face is established; Based on the physical model of the coal mining machine, the physical model of the scraper conveyor and the physical model of the hydraulic support, the physical models of the three machines of the current fully mechanized mining working face are obtained.

4. The three-machine driving method for fully mechanized mining working face according to claim 2 is characterized in that: Based on the equipment model, a behavior model of the three machines in the current fully mechanized mining face is established, including: Obtaining a current driving strategy for the three machines of the current fully mechanized mining face, wherein the current driving strategy includes a driving sub-strategy corresponding to each component; Based on the current driving strategy, a behavior model of the three machines in the current fully mechanized mining face is established.

5. The three-machine driving method for fully mechanized mining working face according to claim 1 is characterized in that: The operation data includes motor current, vibration spectrum, traction force, coal flow weight, and walking displacement. The three-machine coordination strategy generated based on the virtual three-machine state includes: Obtaining first operating sub-data and second operating sub-data corresponding to the three machines of the current fully mechanized mining face in a current cycle, wherein the first operating sub-data includes motor current and vibration spectrum, and the second operating sub-data includes motor current and traction force; Integrating the first operation sub-data based on Kalman filtering to obtain multi-source operation sub-data; Determine, based on the multi-source operation sub-data, a coal seam region corresponding to the three machines of the current fully mechanized mining face, and determine a coal cutting mode corresponding to the coal seam region, wherein the coal seam region is a stable region or other region, and the coal cutting mode is a bidirectional coal cutting model or a unidirectional coal cutting mode; Determining the current coal and rock hardness corresponding to the three machines of the current fully mechanized mining face based on the second operation sub-data, and determining the traction speed of the three machines of the current fully mechanized mining face based on the current coal and rock hardness; Obtaining the coal quantity distribution of the current coal mine, and determining the chain speeds of the three machines of the current fully mechanized mining face based on the coal quantity distribution and the coal flow weight; Determine the support moving step distances corresponding to the three machines in the current fully mechanized mining face based on the walking displacement; A three-machine coordination strategy is generated based on the coal cutting mode, the traction speed, the chain speed, and the support moving step.

6. The three-machine driving method for fully mechanized mining working face according to claim 5, characterized in that: The operation data also includes the current traction speed and the current cutting time. The determination of the support moving step distance corresponding to the three machines of the current fully mechanized mining face based on the walking displacement includes: Obtain the drum inclination angles corresponding to the three machines in the current fully mechanized mining face; Based on the current cutting time, the drum inclination angle, and the travel displacement, the theoretical cutting depth corresponding to the three machines of the current fully mechanized mining working face is calculated; Based on the theoretical cutting depth, the support moving step distances corresponding to the three machines in the current comprehensive mining working face are determined.

7. A three-machine driving device for a fully mechanized mining face, characterized in that: include: The model acquisition module is used to obtain the initial model of the three machines in the current fully mechanized mining face and collect the operating data corresponding to the three machines in the current fully mechanized mining face in real time; A synchronization module, configured to synchronize the operating data with the initial model to obtain a dynamically updated virtual three-machine state; A generation module is used to generate a three-machine coordination strategy based on the virtual three-machine state, and drive the three machines of the current fully mechanized mining face based on the three-machine coordination strategy.

8. The three-machine driving device for fully mechanized mining working face according to claim 7 is characterized in that: The device further comprises: A model acquisition module is used to obtain the equipment models of the three machines in the current fully mechanized mining face and obtain the component sub-models corresponding to the equipment models; An assembly module, used for assembling the component sub-models to obtain a device model; An establishment module is used to establish a physical model and a behavior model of the three machines of the current fully mechanized mining face based on the equipment model; An obtaining module is used to obtain the initial model of the three machines of the current fully mechanized mining face based on the physical model and the behavioral model.

9. An electronic device, characterized in that: The electronic device includes: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the three-machine driving method for a comprehensive mining working face as described in any one of claims 1 to 6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed in a computer, the computer is caused to execute the three-machine driving method for a fully mechanized mining face according to any one of claims 1 to 6.

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