Sectional type parameter self-adaptive control method, device and system for coal mine working face

Abstract

The invention provides a coal mine working face sectional type parameter self-adaptive control method, device and system, and relates to the technical field of coal mining equipment control. In some embodiments of the invention, the coal mine working face is equally divided into a plurality of independent control sections based on the physical distance, and each independent control section is provided with an edge controller, so that accurate control and quick response of equipment in each independent control section can be realized, and the response speed of the system is improved; each edge controller adjusts the operation parameters of the equipment in the independent control section according to the operation parameter self-adaptive adjustment amount, so that the universality of parameter configuration is improved; receiving an independent control section central adjustment instruction issued by the central control computer, and executing the independent control section central adjustment instruction; it is more efficient to determine collaborative operation of different control sections, resource waste and conflicts are reduced, and the system fault occurrence probability is reduced.

Description

Technical Field

[0001] The present disclosure relates to the technical field of coal mining equipment control, and in particular to a method, device, system, equipment and storage medium for segmented parameter adaptive control of a coal mine working face. Background Art

[0002] Currently, coal mine face control systems primarily include the following: Electro-hydraulic control systems: These utilize electro-hydraulic proportional valves to precisely control equipment such as hydraulic supports and shearers. Variable frequency control systems: These utilize frequency converters to adjust the operating speed of equipment such as shearers and conveyors, enabling efficient and energy-efficient production. Centralized control systems: These utilize computer, communications, and automation technologies to centrally monitor, dispatch, and manage coal mine production processes. Intelligent control systems: These utilize artificial intelligence, big data, and other technologies to automate and intelligentize coal mine production processes.

[0003] At present, in the application scenario of ultra-long working faces in coal mines, there are many devices on the ultra-long working faces, and the control signal transmission distance is long, resulting in slow system response speed; the geological conditions of the ultra-long working faces are complex, and the parameter settings of the existing control system are difficult to adapt to different working conditions, and the universality of the parameter configuration is low; there are many devices on the ultra-long working faces, so the probability of failure increases, and the existing control system is difficult to achieve rapid diagnosis and processing, resulting in a higher probability of system failure. Summary of the Invention

[0004] The present disclosure provides a method, device, system, equipment and storage medium for segmented parameter adaptive control of a coal mine working face, so as to at least solve the problems of slow response speed of the existing system, low universality of parameter configuration and high probability of system failure.

[0005] The technical solutions disclosed in this disclosure are as follows:

[0006] The present disclosure provides a segmented parameter adaptive control method for a coal mine working face, which is applied to a target edge controller and includes:

[0007] Collecting operating parameters of equipment within a target independent control segment corresponding to the target edge controller; wherein the coal mine working face is evenly divided into multiple independent control segments based on physical distance, each independent control segment is provided with an edge controller, and the target edge controller is any one of the multiple edge controllers;

[0008] Evaluate the device status according to the operating parameters to obtain a device status evaluation result, and report the device status evaluation result and the operating parameters to a central control computer;

[0009] generating an adaptive adjustment amount of an operating parameter according to the equipment status evaluation result;

[0010] Adjusting the operating parameters of the device and evaluating the device status according to the adaptive adjustment amount of the operating parameters to obtain adjusted operating parameters and an evaluation result of the adjusted device status, and reporting the adjusted operating parameters and the evaluation result of the adjusted device status to the central control computer;

[0011] Receive the independent control segment central adjustment instruction issued by the central control computer, and execute the independent control segment central adjustment instruction; wherein, the independent control segment central adjustment instruction is a cross-segment collaborative optimization adjustment parameter generated by the central control computer based on the adjusted operating parameters of multiple edge controllers and the adjusted device status evaluation results, and is an instruction generated and issued based on the cross-segment collaborative optimization adjustment parameter.

[0012] Optionally, the operating parameters include: support pressure, cutting motor current, conveyor vibration frequency, ambient temperature gradient and conveyor speed value.

[0013] Optionally, the operating parameters include: support pressure, cutting motor current, conveyor vibration frequency, and equipment rated vibration frequency; the equipment status assessment result is a segmented health index; and the equipment status is assessed based on the operating parameters to obtain the equipment status assessment result, including:

[0014] Calculating the segment health index according to the support pressure, the cutting motor current, the conveyor vibration frequency, and the rated vibration frequency of the equipment;

[0015] The segmental health index SHI j The calculation formula is:

[0016]

[0017] Among them, k is the dynamic adjustment coefficient, which is 0.5; e is the Euler number; w1 is the support pressure weight parameter; P j is the support pressure; w2 is the cutting motor current weight parameter; I j is the cutting motor current; w3 is the conveyor vibration frequency weight parameter; f j is the conveyor vibration frequency; f nom is the rated vibration frequency of the equipment.

[0018] Optionally, the device status assessment result is a segmented health index; and generating an adaptive adjustment amount of an operating parameter according to the device status assessment result includes:

[0019] Calculating the adaptive adjustment amount of the operating parameter according to the segmented health index and the basic proportional coefficient;

[0020] The operating parameter adaptive adjustment amount ΔK pThe calculation formula is:

[0021]

[0022] Where ΔK p0 is the basic scale factor, SHI j It is the segmented health index.

[0023] Optionally, the method further includes:

[0024] The central control computer constructs a dynamic coupling model based on the adjusted operating parameters and adjusted device status evaluation results of the plurality of edge controllers; and generates a global coordination instruction based on the collaborative optimization objective function; wherein the global coordination instruction includes an independent control segment central adjustment instruction corresponding to each independent control segment;

[0025] The coupling strength C between adjacent independent control segments in the dynamic coupling model j，j+1 The calculation formula is:

[0026]

[0027] Where δ is the coupling attenuation coefficient, SHI j and SHI j+1 are the segment health indices of the j-th and j+1-th independent control segments, respectively, and e is the Euler number;

[0028] The formula of the collaborative optimization objective function is:

[0029]

[0030] Among them, v j and v j+1 are the speed values ​​of the jth and j+1th conveyors, respectively, v ref is the global reference velocity, v tol is the speed tracking tolerance, which is set to 0.1, λ is the energy consumption weight coefficient, γ is the coordination weight coefficient between independent control segments, and n is the number of independent control segments; P j is the support pressure.

[0031] Optionally, the method further includes:

[0032] fusing the independent control segment central adjustment instruction and the local instruction to generate an execution instruction;

[0033] The execution instruction The calculation formula is:

[0034]

[0035] Among them, α jis the central adjustment instruction weight, (1-α j ) is the local instruction weight, It is the central adjustment instruction of the independent control segment. It is a local instruction;

[0036] The central adjustment instruction weight α j The calculation formula is:

[0037]

[0038] Among them, k is the weight steepness coefficient, which controls the sensitivity of mode switching, e is the Euler number, SHI j is the segment health index of the current independent control segment.

[0039] The present disclosure also provides a segmented parameter adaptive control device for a coal mine working face, which is applied to a target edge controller and includes:

[0040] an acquisition module configured to acquire operating parameters of equipment within a target independent control segment corresponding to the target edge controller; wherein the coal mine working face is evenly divided into a plurality of independent control segments based on physical distance, each of the independent control segments is provided with an edge controller, and the target edge controller is any one of the plurality of edge controllers;

[0041] a first evaluation module, configured to evaluate the device state according to the operating parameters, obtain a device state evaluation result, and report the device state evaluation result and the operating parameters to a central control computer;

[0042] A generating module, configured to generate an adaptive adjustment amount of an operating parameter according to the device status evaluation result;

[0043] a second evaluation module, configured to adjust the operating parameters of the device and evaluate the device status according to the adaptive adjustment amount of the operating parameters, obtain the adjusted operating parameters and the evaluation results of the device status after the adjustment, and report the adjusted operating parameters and the evaluation results of the device status after the adjustment to the central control computer;

[0044] A receiving module is used to receive the independent control segment central adjustment instruction issued by the central control computer and execute the independent control segment central adjustment instruction; wherein, the independent control segment central adjustment instruction is a cross-segment collaborative optimization adjustment parameter generated by the central control computer based on the adjusted operating parameters of multiple edge controllers and the adjusted device status evaluation results, and the instruction is generated and issued based on the cross-segment collaborative optimization adjustment parameter.

[0045] The disclosed embodiments further provide a segmented parameter adaptive control system for a coal mine working face, comprising: a plurality of edge controllers, a central control computer in communication with the plurality of edge controllers, and a plurality of devices in independent control segments in communication with each of the edge controllers;

[0046] a target edge controller, collecting operating parameters of equipment within a target independent control segment corresponding to the target edge controller; wherein the coal mine working face is evenly divided into a plurality of independent control segments based on physical distance, an edge controller is provided for each of the independent control segments, and the target edge controller is any one of the plurality of edge controllers; evaluating the equipment status according to the operating parameters to obtain an equipment status evaluation result, and reporting the equipment status evaluation result and the operating parameters to a central control computer; generating an adaptive adjustment amount of the operating parameters according to the equipment status evaluation result; adjusting the operating parameters of the equipment and evaluating the equipment status according to the adaptive adjustment amount of the operating parameters to obtain adjusted operating parameters and an evaluation result of the adjusted equipment status, and reporting the adjusted operating parameters and the evaluation result of the adjusted equipment status to the central control computer; receiving a central adjustment instruction of the independent control segment issued by the central control computer, and executing the central adjustment instruction of the independent control segment;

[0047] The central control computer generates cross-segment collaborative optimization adjustment parameters based on the adjusted operating parameters of multiple edge controllers and the adjusted device status evaluation results, generates independent control segment central adjustment instructions based on the cross-segment collaborative optimization adjustment parameters, and sends the independent control segment central adjustment instructions to the target edge controller.

[0048] The present disclosure also provides an electronic device, including:

[0049] processor;

[0050] a memory for storing processor-executable instructions;

[0051] The processor is configured to execute instructions to implement each step in the above method.

[0052] The embodiment of the present disclosure further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, each step in the above method is implemented.

[0053] The technical solutions provided by the embodiments of the present disclosure bring at least the following beneficial effects:

[0054] In some embodiments of the present disclosure, the operating parameters of the equipment in the target independent control section corresponding to the target edge controller are collected; wherein, the coal mine working face is evenly divided into multiple independent control sections based on physical distance, and an edge controller is set for each independent control section, which can achieve precise control and rapid response of the equipment in each independent control section, thereby improving the system response speed; the target edge controller is any one of the multiple edge controllers; the equipment state is evaluated according to the operating parameters, and the equipment state evaluation result is obtained, and the equipment state evaluation result and the operating parameters are reported to the central control computer; according to the equipment state evaluation result, an operating parameter adaptive adjustment amount is generated; according to the operating parameter adaptive adjustment amount, the equipment operating parameters are adjusted and the equipment state evaluation result and the operating parameters are adjusted. The standby status is evaluated to obtain the adjusted operating parameters and the evaluation results of the adjusted equipment status, and the adjusted operating parameters and the evaluation results of the adjusted equipment status are reported to the central control computer. Each edge controller adjusts the operating parameters of the equipment in the independent control segment according to the adaptive adjustment amount of the operating parameters, thereby improving the universality of the parameter configuration; the independent control segment central adjustment instruction issued by the central control computer is received, and the independent control segment central adjustment instruction is executed; wherein, the independent control segment central adjustment instruction is a cross-segment collaborative optimization adjustment parameter generated by the central control computer based on the adjusted operating parameters and the adjusted equipment status evaluation results of multiple edge controllers, so as to ensure that the collaborative operation of different control segments is more efficient, reduce resource waste and conflicts, and reduce the probability of system failure.

[0055] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The accompanying drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the description are used to explain the principles of the present disclosure, and do not constitute an improper limitation of the present disclosure.

[0057] Figure 1 A schematic flow chart of a method for adaptively controlling section-wise parameters of a coal mine working face provided by an exemplary embodiment of the present disclosure;

[0058] Figure 2 A schematic structural diagram of a segmented parameter adaptive control device for a coal mine working face provided by an exemplary embodiment of the present disclosure;

[0059] Figure 3 An exemplary embodiment of the present disclosure provides a schematic structural diagram of an electronic device. DETAILED DESCRIPTION

[0060] In order to enable ordinary persons in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings.

[0061] It should be noted that the terms "first," "second," and the like in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or precedence. It should be understood that the numbers used in this manner are interchangeable where appropriate so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure.

[0062] It should be noted that the user information involved in this disclosure includes but is not limited to: user device information and user personal information; the collection, storage, use, processing, transmission, provision and disclosure of user information in this disclosure comply with the relevant laws and regulations and do not violate public order and good morals.

[0063] In response to the above technical problems, in some embodiments of the present disclosure, the operating parameters of the equipment in the target independent control section corresponding to the target edge controller are collected; wherein, the coal mine working face is evenly divided into multiple independent control sections based on physical distance, and each independent control section is provided with an edge controller, which can achieve precise control and rapid response of the equipment in each independent control section, thereby improving the response speed of the system; the target edge controller is any one of the multiple edge controllers; the equipment status is evaluated according to the operating parameters to obtain the equipment status evaluation result, and the equipment status evaluation result and the operating parameters are reported to the central control computer; according to the equipment status evaluation result, an operating parameter adaptive adjustment amount is generated; according to the operating parameter adaptive adjustment amount, the equipment operating parameters are adjusted. The system adjusts and evaluates the equipment status to obtain the adjusted operating parameters and the evaluation results of the adjusted equipment status, and reports the adjusted operating parameters and the evaluation results of the adjusted equipment status to the central control computer. Each edge controller adjusts the operating parameters of the equipment in the independent control segment according to the adaptive adjustment amount of the operating parameters, thereby improving the universality of the parameter configuration; receives the independent control segment central adjustment instruction issued by the central control computer, and executes the independent control segment central adjustment instruction; wherein, the independent control segment central adjustment instruction is a cross-segment collaborative optimization adjustment parameter generated by the central control computer based on the adjusted operating parameters and the adjusted equipment status evaluation results of multiple edge controllers, thereby ensuring that the collaborative operation of different control segments is more efficient, reducing resource waste and conflicts, and reducing the probability of system failure.

[0064] The technical solutions provided by various embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

[0065] Figure 1 The following is a flow chart of a method for adaptive control of segmented parameters of a coal mine working face provided by an exemplary embodiment of the present disclosure. Figure 1 As shown, the method includes:

[0066] S101: Collect operating parameters of equipment in a target independent control segment corresponding to a target edge controller; wherein the coal mine working face is evenly divided into multiple independent control segments based on physical distance, each independent control segment is configured with an edge controller, and the target edge controller is any one of the multiple edge controllers;

[0067] S102: Evaluate the device status according to the operating parameters to obtain a device status evaluation result, and report the device status evaluation result and the operating parameters to the central control computer;

[0068] S103: generating an adaptive adjustment amount of an operating parameter according to the equipment status evaluation result;

[0069] S104: Adjusting the operating parameters of the equipment and evaluating the equipment status according to the adaptive adjustment amount of the operating parameters, obtaining the adjusted operating parameters and the evaluation results of the adjusted equipment status, and reporting the adjusted operating parameters and the evaluation results of the adjusted equipment status to the central control computer;

[0070] S105: Receive the independent control segment central adjustment instruction issued by the central control computer, and execute the independent control segment central adjustment instruction; wherein, the independent control segment central adjustment instruction is a cross-segment collaborative optimization adjustment parameter generated by the central control computer based on the adjusted operating parameters of multiple edge controllers and the adjusted device status evaluation results, and the instruction is generated and issued based on the cross-segment collaborative optimization adjustment parameter.

[0071] In this embodiment, the method is performed by an edge controller, a computing device located at the edge of the network that performs real-time data processing, analysis, and decision-making near the data source. It is a key component in the edge computing architecture.

[0072] By dividing the working face into several independent control segments and assigning an edge controller to each control segment, this system achieves precise control and rapid response for equipment within each segment, thereby improving overall workface control accuracy and efficiency. The edge controller can collect and analyze equipment operating parameters in real time, promptly identifying and addressing potential issues, reducing equipment failures and downtime, and thus enhancing the stability and reliability of the entire system. Adaptive parameter adjustment is achieved: Based on equipment status assessment results, the edge controller generates adaptive adjustment values ​​for operating parameters, allowing equipment to automatically adjust to optimal operating conditions based on actual operating conditions, improving production efficiency. A central control computer generates cross-segment collaborative optimization adjustment parameters based on data from all edge controllers, ensuring more efficient collaboration between different control segments and reducing resource waste and conflicts. Real-time monitoring and adaptive adjustment can reduce equipment wear and damage, extend equipment life, and reduce maintenance costs. This method effectively monitors equipment status, promptly identifies safety hazards, and prevents accidents by adjusting parameters, thereby improving coal mine production safety. The segmented control method facilitates system expansion and maintenance, allowing newly added control segments to be easily integrated into the existing system, enhancing system flexibility and scalability. A control system with a high degree of automation can reduce dependence on manual operations, lower the demand for human resources, and reduce the possibility of human error.

[0073] In some embodiments of the present disclosure, the operating parameters include at least one of the following: support pressure, cutting motor current, conveyor vibration frequency, ambient temperature gradient, conveyor speed value, and equipment rated vibration frequency. The equipment status assessment result may be a segmented health index.

[0074] In some embodiments of the present disclosure, the equipment status is evaluated based on the operating parameters to obtain an equipment status evaluation result. One possible implementation is to calculate a segmented health index based on the support pressure, the cutting motor current, the conveyor vibration frequency, and the rated vibration frequency of the equipment.

[0075] Segmental Health Index (SHI) j The calculation formula is:

[0076]

[0077] Among them, k is the dynamic adjustment coefficient, which is 0.5; e is the Euler number; w1 is the support pressure weight parameter; P j is the support pressure; w2 is the cutting motor current weight parameter; I j is the cutting motor current; w3 is the conveyor vibration frequency weight parameter; f j is the conveyor vibration frequency; f nom is the rated vibration frequency of the equipment.

[0078] The above-mentioned embodiments of the present disclosure can timely detect potential safety risks, such as support instability or conveyor overload, by real-time monitoring and evaluation of the operating parameters of the equipment, and real-time monitoring of key parameters such as support pressure and conveyor vibration frequency, so as to take measures to prevent accidents. Potential failures or performance degradation can be predicted, thereby achieving predictive maintenance and reducing sudden downtime. The calculation of the segmented health index helps to identify the performance differences between different sections of the working face, and optimize the equipment operating status by adjusting parameters, thereby improving overall production efficiency. By adjusting parameters such as the cutting motor current and conveyor speed, the energy consumption of the equipment can be optimized and unnecessary energy waste can be reduced. By avoiding the equipment from running for a long time in a bad state, wear can be reduced and the service life of the equipment can be extended. The introduction of the concept of health index makes the control system more intelligent and can automatically adjust the control strategy according to the actual operating status of the equipment. By collecting and analyzing a large amount of equipment operation data, data support can be provided to management and data-based decision-making capabilities can be enhanced.

[0079] In some embodiments of the present disclosure, an adaptive adjustment amount of an operating parameter is generated based on the device status evaluation result. One possible implementation method is to calculate the adaptive adjustment amount of the operating parameter based on the segmented health index and the basic proportional coefficient. Dynamically adjust the proportional coefficient K in the PID parameter based on the fuzzy rule base p .

[0080] Adaptive adjustment of operating parameters ΔK p The calculation formula is:

[0081]

[0082] Where ΔK p0 is the basic scale factor, SHI j It is the segmented health index.

[0083] The above-mentioned embodiments of the present disclosure can reduce the impact of external interference and model uncertainty on the control system through fuzzy PID control, improve the robustness of the system, and ensure stable control effects even in changing working environments; the use of a fuzzy rule base simplifies the design process of complex control strategies, making the control logic more intuitive and easy to understand. By adjusting the PID parameters in real time, the operating status of the equipment can be optimized, energy consumption and equipment wear can be reduced, thereby reducing operating costs. The parameter adaptive adjustment amount is calculated based on the health index, which can more accurately match the actual needs of the equipment and improve control accuracy. Automated parameter adjustment reduces the need for manual parameter adjustment, reduces the possibility of manual errors, and improves the level of automation. By adjusting the PID parameters in real time, equipment downtime caused by parameter mismatch can be reduced, and the continuity and efficiency of production can be improved.

[0084] In some embodiments of the present disclosure, the central control computer constructs a dynamic coupling model based on the adjusted operating parameters and adjusted equipment status evaluation results of multiple edge controllers; and generates global collaborative instructions based on the collaborative optimization objective function; wherein the global collaborative instructions include independent control segment central adjustment instructions corresponding to each independent control segment. By constructing a dynamic coupling model, the present disclosure enables the central control computer to take into account the interactions and influences between the control segments, thereby achieving global optimization control of the entire working surface. The dynamic coupling model can identify and compensate for mutual interference between the segments, reduce system oscillations and unstable factors, and enhance the stability of the overall system. Global collaborative instructions ensure the coordinated work between the independent control segments and improve the coordination and consistency of the entire working surface. The setting of the collaborative optimization objective function helps to optimize the production process and improve production efficiency and output. Global optimization control can reduce excessive wear and unnecessary maintenance of equipment, thereby reducing maintenance costs.

[0085] Optionally, the coupling strength C between adjacent independent control segments in the dynamic coupling model j，j+1 The calculation formula is:

[0086]

[0087] Where δ is the coupling attenuation coefficient, SHI j and SHI j+1 are the segment health indices of the j-th and j+1-th independent control segments, respectively, and e is the Euler number.

[0088] The formula of the collaborative optimization objective function is:

[0089]

[0090] Among them, v j and v j+1 are the speed values ​​of the jth and j+1th conveyors, respectively, v ref is the global reference velocity, v tol is the speed tracking tolerance, which is set to 0.1, λ is the energy consumption weight coefficient, γ is the coordination weight coefficient between independent control segments, and n is the number of independent control segments; P j is the support pressure.

[0091] In the above-mentioned embodiment of the present disclosure, by defining the coupling strength formula, the model can accurately represent the interaction between adjacent control segments, thereby better coordinating the operations between the segments. The coupling attenuation coefficient allows the system to adaptively adjust the coupling strength according to the actual operating conditions, making the model more flexible and able to adapt to different working conditions. The collaborative optimization objective function takes into account the speed value of each section of the conveyor, which helps to maintain the balance of production speed of the entire working surface and avoid inefficiency caused by speed mismatch. The introduction of the global reference speed enables each section of the conveyor to track a unified standard, improving production consistency and product quality. The setting of the energy consumption weight coefficient allows the optimization objective function to consider the optimization of energy consumption while pursuing production efficiency, which helps to reduce overall energy consumption.

[0092] In some embodiments of the present disclosure, the edge controller fuses the central adjustment instructions and local instructions of the independent control segment to generate execution instructions.

[0093] Execute instructions The calculation formula is:

[0094]

[0095] Among them, α j is the central adjustment instruction weight, (1-α j ) is the local instruction weight, It is the central adjustment instruction of the independent control segment. It is a local instruction.

[0096] Central adjustment command weight α j The calculation formula is:

[0097]

[0098] Among them, k is the weight steepness coefficient, which controls the sensitivity of mode switching, e is the Euler number, SHI j is the segment health index of the current independent control segment.

[0099] The above embodiment of the present disclosure effectively combines central adjustment instructions and local instructions through the fusion formula, enhances the synergy between central control and edge control, and improves the overall performance of the control system. The introduction of weight coefficients enables the control system to flexibly adjust the control strategy according to the current working segment status and better adapt to the dynamic changes of the working surface. Segment Health Index SHI jThe larger it is, the greater the proportion of global instructions. The weight steepness coefficient allows the system to automatically adjust the weight of the central adjustment instruction according to the segmented health index, so that the system can maintain stable operation when facing different health states. The segmented parameter adaptive control system of the super-long working face of the coal mine is used to implement the segmented parameter adaptive control method of the super-long working face of the coal mine. The adaptive control system includes multiple edge controllers, communication modules and a central control computer. The multiple edge controllers are respectively communicated with the central control computer through the communication modules, and the multiple edge controllers are respectively communicated with the multiple devices in the corresponding independent control segments. By adopting the above technical solution, the communication module can be based on wired communication, and can also realize wireless communication based on a locally constructed wireless network, such as Lora wireless technology.

[0100] In conjunction with the descriptions of the above embodiments, the present disclosure further provides a segmented parameter adaptive control system for a coal mine working face, comprising: multiple edge controllers, a central control computer communicatively coupled to the multiple edge controllers, and multiple devices within independent control segments communicatively coupled to each edge controller. The multiple edge controllers are each communicatively coupled to the central control computer via a communication module. The communication module can be based on wired communication or wireless communication using a locally constructed wireless network, such as LoRa wireless technology.

[0101] Among them, the target edge controller collects the operating parameters of the equipment in the target independent control segment corresponding to the target edge controller; wherein the coal mine working face is evenly divided into multiple independent control segments based on physical distance, each independent control segment is provided with an edge controller, and the target edge controller is any edge controller among the multiple edge controllers; the equipment status is evaluated according to the operating parameters to obtain the equipment status evaluation result, and the equipment status evaluation result and the operating parameters are reported to the central control computer; according to the equipment status evaluation result, the operating parameter adaptive adjustment amount is generated; according to the operating parameter adaptive adjustment amount, the equipment operating parameters are adjusted and the equipment status is evaluated to obtain the adjusted operating parameters and the adjusted equipment status evaluation result, and the adjusted operating parameters and the adjusted equipment status evaluation result are reported to the central control computer; the independent control segment central adjustment instruction issued by the central control computer is received, and the independent control segment central adjustment instruction is executed;

[0102] The central control computer generates cross-segment collaborative optimization adjustment parameters based on the adjusted operating parameters of multiple edge controllers and the adjusted device status evaluation results, generates independent control segment central adjustment instructions based on the cross-segment collaborative optimization adjustment parameters, and sends the independent control segment central adjustment instructions to the target edge controller.

[0103] The following specific embodiments are used to illustrate the implementation principles of the disclosed coal mine working face segmented parameter adaptive control method and system:

[0104] A 400-meter-long working face at a coal mine was divided into eight independently controlled sections, each 50 meters long. Sections 1-4 were geologically stable, with an initial support pressure of 28 MPa, a cutting motor current of 90 A, a conveyor vibration frequency of 48 Hz, and a temperature gradient of 5°C / m. Sections 5-8 were geologically fragmented, with a support pressure of 35 MPa, a current of 130 A, a vibration frequency of 55 Hz, and a temperature gradient of 12°C / m.

[0105] Condition Assessment: Calculated using the Segment Health Index (SHI) formula: The SHI value for Segment 1 is 0.32 (good condition), and the SHI value for Segment 5 reaches 0.81 (abnormal condition). The calculation uses a dynamic adjustment coefficient k = 0.5, and weighting parameters w1 = 0.4 (pressure), w2 = 0.3 (current), and w3 = 0.3 (rated vibration frequency fnom = 50 Hz).

[0106] Parameter adjustment: Adaptive adjustment based on SHI value: The first section enters energy-saving mode, the proportional coefficient Kp is adjusted from the basic value of 2.5 to 2.1, and the cutting speed is reduced by 10%; the fifth section enters protection mode, Kp increases to 3.3, and the support pressure increases by 15%.

[0107] Collaborative Optimization: The central control computer calculated that the combined coefficient between the fourth (stable) and fifth (crushing) segments was 0.35, significantly lower than the 0.92 between the stable segments. The optimized instructions required the speed of the fourth segment to be adjusted from 2.4m / s to 2.45m / s, and the speed of the fifth segment to be increased from 2.1m / s to 2.25m / s. The target synchronous speed was 2.5m / s, with an allowable deviation of 0.1m / s.

[0108] Instruction execution: The fourth section uses a 70% central instruction weight (a=0.7), with a final execution speed of 2.45m / s, an inverter PWM duty cycle of 65%, and a pressure stable at 29MPa; the fifth section uses a 95% central instruction weight (a=0.95), an execution speed of 2.25m / s, the hydraulic valve opening increases to 85%, and the vibration frequency drops to 52Hz.

[0109] Implementation results: The speed synchronization error across the entire working face was reduced from ±0.15 m / s to +0.03 m / s, energy consumption per ton of coal was reduced from 3.2 kW h / t to 2.4 kW h / t, and fault response time was shortened from 10 minutes to 1.2 minutes. The pressure in the high-risk fifth section was reduced from 35 MPa to 32 MPa, preventing roof collapse accidents. The current in the stable first section was reduced from 90 A to 82 A, extending equipment life. The entire conveying system operated smoothly, with no coal accumulation.

[0110] After implementation at a 430-meter working face in a coal mine, this solution reduced the failure rate by 70% and increased production capacity by 18%, achieving safe and efficient production. Through dynamic weight allocation and precise coordinated control, it effectively addressed the control challenges associated with uneven geological conditions in the ultra-long working face.

[0111] Figure 2 Schematic diagram of a coal mine working face segmented parameter adaptive control device 20 provided by an exemplary embodiment of the present disclosure. Figure 2 As shown, the coal mine working face segmented parameter adaptive control device 20 includes: an acquisition module 21, a first evaluation module 22, a generation module 23, a second evaluation module 24 and a receiving module 25.

[0112] The acquisition module 21 is configured to acquire operating parameters of equipment within a target independent control segment corresponding to a target edge controller; wherein the coal mine working face is evenly divided into multiple independent control segments based on physical distance, each independent control segment is provided with an edge controller, and the target edge controller is any one of the multiple edge controllers;

[0113] The first evaluation module 22 is used to evaluate the equipment status according to the operating parameters, obtain the equipment status evaluation result, and report the equipment status evaluation result and the operating parameters to the central control computer;

[0114] A generating module 23 is used to generate an adaptive adjustment amount of an operating parameter according to the equipment status evaluation result;

[0115] The second evaluation module 24 is configured to adjust the operating parameters of the equipment and evaluate the equipment status according to the adaptive adjustment amount of the operating parameters, obtain the adjusted operating parameters and the evaluation results of the adjusted equipment status, and report the adjusted operating parameters and the evaluation results of the adjusted equipment status to the central control computer;

[0116] The receiving module 25 is used to receive the independent control segment central adjustment instruction issued by the central control computer and execute the independent control segment central adjustment instruction; wherein, the independent control segment central adjustment instruction is a cross-segment collaborative optimization adjustment parameter generated by the central control computer based on the adjusted operating parameters of multiple edge controllers and the adjusted device status evaluation results, and is an instruction generated and issued based on the cross-segment collaborative optimization adjustment parameter.

[0117] Regarding the apparatus in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0118] Figure 3 FIG. 1 is a structural diagram of an electronic device provided by an exemplary embodiment of the present disclosure. Figure 3As shown, the electronic device includes: a memory 31 and a processor 32. In addition, the electronic device also includes a power supply component 33 and a communication component 34.

[0119] The memory 31 is used to store computer programs and can be configured to store various other data to support operations on the electronic device. Examples of such data include instructions for any application or method operating on the electronic device.

[0120] The memory 31 can be implemented by any type of volatile or non-volatile memory device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0121] The communication component 34 is used for data transmission with other devices.

[0122] The processor 32 is configured to execute computer instructions stored in the memory 31 to: collect operating parameters of equipment within a target independent control segment corresponding to a target edge controller; wherein the coal mine working face is evenly divided into multiple independent control segments based on physical distance, each independent control segment is provided with an edge controller, and the target edge controller is any one of the multiple edge controllers; evaluate the equipment status based on the operating parameters to obtain an equipment status evaluation result, and report the equipment status evaluation result and the operating parameters to a central control computer; generate an adaptive adjustment amount for the operating parameters based on the equipment status evaluation result; adjust the equipment operating parameters and evaluate the equipment status based on the adaptive adjustment amount for the operating parameters to obtain adjusted operating parameters and an adjusted equipment status evaluation result, and report the adjusted operating parameters and the adjusted equipment status evaluation result to the central control computer; receive an independent control segment central adjustment instruction issued by the central control computer and execute the independent control segment central adjustment instruction; wherein the independent control segment central adjustment instruction is a cross-segment collaborative optimization adjustment parameter generated by the central control computer based on the adjusted operating parameters and the adjusted equipment status evaluation results of multiple edge controllers, and is an instruction generated and issued based on the cross-segment collaborative optimization adjustment parameter.

[0123] Accordingly, the embodiment of the present disclosure further provides a computer-readable storage medium storing a computer program. When the computer-readable storage medium stores the computer program and the computer program is executed by one or more processors, the one or more processors are caused to execute Figure 1 Each step in the embodiment of the method.

[0124] Accordingly, the present disclosure also provides a computer program product, which includes a computer program / instruction, and the computer program / instruction is executed by a processor. Figure 1 Each step in the method embodiment.

[0125] above Figure 3 The communication component is configured to facilitate wired or wireless communication between the device where the communication component is located and other devices. The device where the communication component is located can access a wireless network based on a communication standard, such as WiFi, 2G, 3G, 4G / LTE, 5G and other mobile communication networks, or a combination thereof. In an exemplary embodiment, the communication component receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0126] above Figure 3 The power supply component in a device provides power to various components of the device in which the power supply component is located. The power supply component may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the device in which the power supply component is located.

[0127] The electronic device also includes a display screen and an audio component.

[0128] The display screen includes a screen, which may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from a user. The touch panel includes one or more touch sensors to sense touches, slides, and gestures on the touch panel. The touch sensor can not only sense the boundaries of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation.

[0129] The audio component can be configured to output and / or input audio signals. For example, the audio component includes a microphone (MIC), and when the device where the audio component is located is in an operating mode, such as call mode, recording mode, and voice recognition mode, the microphone is configured to receive external audio signals. The received audio signal can be further stored in a memory or sent via a communication component. In some embodiments, the audio component also includes a speaker for outputting audio signals.

[0130] Those skilled in the art will appreciate that the embodiments of the present disclosure may be provided as methods, systems, or computer program products. Therefore, the present disclosure may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present disclosure may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0131] The present disclosure is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present disclosure. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0132] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0133] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0134] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0135] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0136] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory media such as modulated data signals and carrier waves.

[0137] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or device that includes the element.

[0138] The above are merely specific embodiments of the present disclosure, intended to enable those skilled in the art to understand and implement the present disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure is not limited to these embodiments, but is to be construed in the broadest manner consistent with the principles and novel features disclosed herein.

Claims

1. A segmented parameter adaptive control method for coal mine working face, characterized in that: Applicable to target edge controllers, including: Collecting operating parameters of equipment within a target independent control segment corresponding to the target edge controller; wherein the coal mine working face is evenly divided into multiple independent control segments based on physical distance, each independent control segment is provided with an edge controller, and the target edge controller is any one of the multiple edge controllers; Evaluate the device status according to the operating parameters to obtain a device status evaluation result, and report the device status evaluation result and the operating parameters to a central control computer; generating an adaptive adjustment amount of an operating parameter according to the equipment status evaluation result; Adjusting the operating parameters of the device and evaluating the device status according to the adaptive adjustment amount of the operating parameters to obtain adjusted operating parameters and an evaluation result of the adjusted device status, and reporting the adjusted operating parameters and the evaluation result of the adjusted device status to the central control computer; Receive the independent control segment central adjustment instruction issued by the central control computer, and execute the independent control segment central adjustment instruction; wherein, the independent control segment central adjustment instruction is a cross-segment collaborative optimization adjustment parameter generated by the central control computer based on the adjusted operating parameters of multiple edge controllers and the adjusted device status evaluation results, and is an instruction generated and issued based on the cross-segment collaborative optimization adjustment parameter.

2. The method according to claim 1, characterized in that The operating parameters include: support pressure, cutting motor current, conveyor vibration frequency, ambient temperature gradient and conveyor speed value.

3. The method according to claim 1, characterized in that The operating parameters include: support pressure, cutting motor current, conveyor vibration frequency and equipment rated vibration frequency; the equipment status assessment result is a segmented health index; the equipment status is assessed based on the operating parameters to obtain the equipment status assessment result, including: Calculating the segment health index according to the support pressure, the cutting motor current, the conveyor vibration frequency, and the rated vibration frequency of the equipment; The segmental health index SHI j The calculation formula is: Among them, k is the dynamic adjustment coefficient, which is 0.5; e is the Euler number; w1 is the support pressure weight parameter; P j is the support pressure; w2 is the cutting motor current weight parameter; I j is the cutting motor current; w3 is the conveyor vibration frequency weight parameter; f j is the conveyor vibration frequency; f nom is the rated vibration frequency of the equipment.

4. The method according to claim 1, wherein The device status evaluation result is a segmented health index; and generating an adaptive adjustment amount of an operating parameter according to the device status evaluation result includes: Calculating the adaptive adjustment amount of the operating parameter according to the segmented health index and the basic proportional coefficient; The operating parameter adaptive adjustment amount ΔK p The calculation formula is: Where ΔK p0 is the basic scale factor, SHI j It is the segmented health index.

5. The method according to claim 1, wherein The method further comprises: The central control computer constructs a dynamic coupling model based on the adjusted operating parameters and adjusted device status evaluation results of the plurality of edge controllers; and generates a global coordination instruction based on the collaborative optimization objective function; wherein the global coordination instruction includes an independent control segment central adjustment instruction corresponding to each independent control segment; The coupling strength C between adjacent independent control segments in the dynamic coupling model j，j+1 The calculation formula is: Where δ is the coupling attenuation coefficient, SHI j and SHI j+1 are the segment health indices of the j-th and j+1-th independent control segments, respectively, and e is the Euler number; The formula of the collaborative optimization objective function is: Among them, v j and v j+1 are the speed values ​​of the jth and j+1th conveyors, respectively, v ref is the global reference velocity, v tol is the speed tracking tolerance, which is set to 0.1, λ is the energy consumption weight coefficient, γ is the coordination weight coefficient between independent control segments, and n is the number of independent control segments; P j is the support pressure.

6. The method according to claim 1, wherein The method further comprises: fusing the independent control segment central adjustment instruction and the local instruction to generate an execution instruction; The execution instruction The calculation formula is: Among them, α j is the central adjustment instruction weight, (1-α j ) is the local instruction weight, It is the central adjustment instruction of the independent control segment. It is a local instruction; The central adjustment instruction weight α j The calculation formula is: Among them, k is the weight steepness coefficient, which controls the sensitivity of mode switching, e is the Euler number, SHI j is the segment health index of the current independent control segment.

7. A segmented parameter adaptive control device for coal mine working face, characterized in that: Applicable to target edge controllers, including: an acquisition module configured to acquire operating parameters of equipment within a target independent control segment corresponding to the target edge controller; wherein the coal mine working face is evenly divided into a plurality of independent control segments based on physical distance, each of the independent control segments is provided with an edge controller, and the target edge controller is any one of the plurality of edge controllers; a first evaluation module, configured to evaluate the device state according to the operating parameters, obtain a device state evaluation result, and report the device state evaluation result and the operating parameters to a central control computer; A generating module, configured to generate an adaptive adjustment amount of an operating parameter according to the device status evaluation result; a second evaluation module, configured to adjust the operating parameters of the device and evaluate the device status according to the adaptive adjustment amount of the operating parameters, obtain the adjusted operating parameters and the evaluation results of the device status after the adjustment, and report the adjusted operating parameters and the evaluation results of the device status after the adjustment to the central control computer; A receiving module is used to receive the independent control segment central adjustment instruction issued by the central control computer and execute the independent control segment central adjustment instruction; wherein, the independent control segment central adjustment instruction is a cross-segment collaborative optimization adjustment parameter generated by the central control computer based on the adjusted operating parameters of multiple edge controllers and the adjusted device status evaluation results, and the instruction is generated and issued based on the cross-segment collaborative optimization adjustment parameter.

8. A segmented parameter adaptive control system for coal mine working face, characterized in that: include: a plurality of edge controllers, a central control computer communicatively coupled to the plurality of edge controllers, and a plurality of devices within an independent control segment communicatively coupled to each of the edge controllers; a target edge controller, configured to collect operating parameters of equipment within a target independent control segment corresponding to the target edge controller; wherein the coal mine working face is evenly divided into a plurality of independent control segments based on physical distance, each of the independent control segments is provided with an edge controller, and the target edge controller is any one of the plurality of edge controllers; evaluate the equipment status according to the operating parameters to obtain an equipment status evaluation result, and report the equipment status evaluation result and the operating parameters to a central control computer; and generate an adaptive adjustment amount for the operating parameters according to the equipment status evaluation result; Adjusting the operating parameters of the device and evaluating the device status according to the adaptive adjustment amount of the operating parameters to obtain adjusted operating parameters and an evaluation result of the adjusted device status, and reporting the adjusted operating parameters and the evaluation result of the adjusted device status to the central control computer; receiving an independent control segment central adjustment instruction issued by the central control computer, and executing the independent control segment central adjustment instruction; The central control computer generates cross-segment collaborative optimization adjustment parameters based on the adjusted operating parameters of multiple edge controllers and the adjusted device status evaluation results, generates independent control segment central adjustment instructions based on the cross-segment collaborative optimization adjustment parameters, and sends the independent control segment central adjustment instructions to the target edge controller.

9. An electronic device, characterized in that: include: processor; a memory for storing processor-executable instructions; The processor is configured to execute instructions to implement each step in the method according to 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 by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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