Oversized mining height working face control method, device and equipment based on closed-loop feedback

Abstract

The invention provides an ultra-large mining height working face control method, device and equipment based on closed-loop feedback, and relates to the technical field of data processing. The method comprises the following steps: acquiring a first multi-source control parameter of the working face with the super-large mining height; calculating an equipment risk assessment value based on the first multi-source control parameter; generating control instructions of a plurality of devices of the super-large mining height working face based on the device risk assessment value, and transmitting the control instructions to the plurality of devices respectively, so that each device executes the control instruction; after each piece of equipment executes the control instruction, collecting a second multi-source control parameter of each piece of equipment after the control instruction is executed; and on the basis of the second multi-source control parameter, whether the equipment operation condition of the super-large mining height working face meets the preset performance requirement or not is determined. By adopting the method provided by the embodiment of the invention, the energy efficiency and the safety of the whole super-large mining height working face can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of data processing, and in particular, to a control method, device, and equipment for an extra-high mining height working face based on closed-loop feedback. Background Art

[0002] In the related art, hydraulic supports and shearers are important equipment for extra-high mining height working faces. At present, pressure compensation control is usually adopted for hydraulic support control, such as the Bang-Bang control strategy. When the column pressure is lower than the set value, full-flow liquid supply is provided, and it is cut off after reaching the threshold value, which may cause pressure oscillation and may cause frequent failure of seals. The height control of the shearer usually adopts cubic spline interpolation combined with PID, but it will fail when geological mutations occur. Moreover, the sampling period of the hydraulic support pressure data is not synchronized with the shearer positioning data, which will cause a large alignment error in the collaborative control time, resulting in a relatively high proportion of reactive power consumption in the hydraulic system. This will affect the energy efficiency and safety of the extra-high mining height working face. Summary of the Invention

[0003] The present application provides a control method, device, and equipment for an extra-high mining height working face based on closed-loop feedback. The technical solution of the present application is as follows: In a first aspect, the present application provides a control method for an extra-high mining height working face based on closed-loop feedback, including: Collecting first multi-source control parameters of the extra-high mining height working face; Calculating an equipment risk assessment value based on the first multi-source control parameters; Generating control instructions for multiple devices of the extra-high mining height working face based on the equipment risk assessment value, and respectively transmitting the control instructions to the multiple devices so that each device executes the control instructions; After each device executes the control instructions, collecting second multi-source control parameters of each device after executing the control instructions; Based on the second multi-source control parameters, determining whether the equipment operation condition of the extra-high mining height working face meets the preset performance requirements.

[0004] In a second aspect, the present application provides a control device for an extra-high mining height working face based on closed-loop feedback, including: A first data acquisition module for collecting first multi-source control parameters of the extra-high mining height working face; A data calculation module for calculating an equipment risk assessment value based on the first multi-source control parameters; An instruction control module for generating control instructions for multiple devices of the extra-high mining height working face based on the equipment risk assessment value, and respectively transmitting the control instructions to the multiple devices so that each device executes the control instructions; A second data acquisition module, configured to collect second multi-source control parameters of each device after each device executes the control instruction; A control module, configured to determine, based on the second multi-source control parameters, whether the operation of the devices in the ultra-high cutting height working face meets the preset performance requirements.

[0005] In a third aspect, the present application provides an electronic device, including: A processor; A memory for storing executable instructions of the processor; Wherein, the processor is configured to execute the instructions to implement the method described in the first aspect.

[0006] In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the method described in the first aspect is implemented.

[0007] In a fifth aspect, the present application provides a computer program product, including computer programs / instructions, and when the computer programs / instructions are executed by a processor, the method described in the first aspect is implemented.

[0008] The technical solutions disclosed in the present application at least bring the following beneficial effects: In the embodiments of the present application, by collecting the first multi-source control parameters of the ultra-high cutting height working face; calculating the equipment risk assessment value based on the first multi-source control parameters; generating control instructions for multiple devices in the ultra-high cutting height working face based on the equipment risk assessment value, and transmitting the control instructions to the multiple devices respectively, so that each device executes the control instruction; after each device executes the control instruction, collecting the second multi-source control parameters of each device after executing the control instruction; and determining, based on the second multi-source control parameters, whether the operation of the devices in the ultra-high cutting height working face meets the preset performance requirements. In this way, by collecting the multi-source control parameters of the ultra-high cutting height working face, calculating the equipment risk assessment value, and generating control instructions based on this, precise control and closed-loop verification of devices such as hydraulic supports and shearers can be achieved. In this way, the pressure oscillation of the hydraulic support can be effectively reduced, the service life of the sealing parts can be extended, and the height control stability of the shearer can be maintained during geological mutations; moreover, by synchronously collecting and processing multi-source data, the time alignment error of cooperative control can also be reduced, the reactive power consumption of the hydraulic system can be reduced, thereby improving the energy efficiency and safety of the entire ultra-high cutting height working face.

[0009] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The accompanying drawings here are incorporated into the specification and form a part of this specification, showing embodiments consistent with the present disclosure, and are used together with the specification to explain the principles of the present disclosure, and do not constitute an undue limitation on the present disclosure.

[0011] Figure 1 It is a schematic flow chart of a control method for an extra-large mining height working face based on closed-loop feedback provided by an embodiment of the present application; Figure 2 It is a schematic flow chart of a control method for an extra-large mining height working face based on closed-loop feedback provided by an embodiment of the present application; Figure 3 It is a schematic structural diagram of a control device for an extra-large mining height working face based on closed-loop feedback provided by an embodiment of the present application; Figure 4 It is a schematic structural diagram of an electronic device provided by an embodiment of the present application. Specific embodiments

[0012] In order to enable those of ordinary skill in the art to better understand the technical solutions of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0013] It should be noted that the terms "first", "second", etc. in the present application are used to distinguish similar objects and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such used data can be interchanged under appropriate circumstances so that the embodiments of the present application described here can be implemented in an order other than those illustrated or described here. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application.

[0014] It should be noted that in the embodiments of the present application, there may be existing solutions in the industry for certain software, components, models, etc. They should be considered exemplary, and their purpose is only to illustrate the feasibility in the implementation of the technical solutions of the present application, but it does not mean that the applicant has already or necessarily used this solution.

[0015] In the related art, the control technology of hydraulic supports is usually achieved through pressure compensation. The pressure compensation control usually adopts the Bang-Bang control strategy. When the pressure of the upright cylinder is lower than the set value (such as 28 MPa), the full flow of liquid is supplied. After reaching the threshold, the supply will be cut off. The inclination anti-toppling control usually detects the inclination of the support through a biaxial inclination sensor. When the lateral inclination angle is greater than 3°, the unilateral upright cylinder will be triggered to supplement pressure. This method is prone to pressure oscillation phenomena. For example, when the mining height is above 7.5 m, if the overshoot of pressure adjustment reaches 35%, it will cause the seals to fail frequently. Moreover, when adjacent hydraulic supports are lifted and lowered synchronously, hydraulic shock waves are also likely to be generated. When the propagation speed of pressure fluctuations reaches 150 m / s, system resonance will also be triggered. For the electro-hydraulic control of hydraulic supports, pressure sensors and inclination sensors are usually used to achieve the automatic following of the hydraulic supports. However, after the mining height increases, the pressure distribution of the roof will show a non-linear enhancement phenomenon, and the PID (Proportional-Integral-Derivative) control in the related technology is difficult to adapt to this situation. For the height control of the shearer, the cubic spline interpolation method is usually used to construct the roof and floor curves, and the PID is combined to control the drum height. The limitation of this method is that it will fail during geological mutations. For example, when encountering a fault (such as a hardness change > 15%), the cutting resistance will surge, resulting in the saturation of the PID integral term, and the trajectory deviation can reach 200 mm. In addition, the sampling period of the support pressure data (such as 500 ms) and the shearer positioning data period (such as 100 ms) in the ultra-large mining height working face are not synchronized, resulting in a large alignment error in the collaborative control time (such as up to 0.4 s at most). And when the mining height is 8 m, the proportion of reactive power consumption of the hydraulic system may increase from the conventional 18% to 34%.

[0016] Based on this, a control method for an ultra-large mining height working face based on closed-loop feedback provided by an embodiment of the present application can collect real-time data of the ultra-large mining height working face (such as multi-source control parameters), providing a basis for subsequent analysis and decision-making; it can collect key parameters such as the pressure of the hydraulic support, the position of the shearer, and the roof separation amount, integrate data from different sources, and obtain the overall state of the working face; it can perform fusion calculations on the collected multi-source control parameters to obtain more comprehensive working face state information, evaluate the risks of equipment operation, and provide a basis for control decisions; it can also perform equipment risk assessment values according to the fused equipment state information, identify possible safety hazards, and based on the equipment risk assessment values, use a distributed decision algorithm to generate control quantities for multiple devices in the ultra-large mining height working face; and, through the contract net protocol, achieve efficient task allocation; at the same time, it can adjust the working state of the equipment according to the control instructions. Each device can perform corresponding operations according to the received control instructions, and verify the control effect of the ultra-large mining height working face through closed-loop feedback to ensure the stability and safety of system operation.

[0017] In this way, through multi-source data fusion and distributed decision-making, the device can be controlled more precisely, improving production efficiency. The device risk assessment value helps to identify potential risks in advance, take preventive measures, and reduce the accident rate; the improved contract net protocol and bid response mechanism can allocate tasks more effectively, improving resource utilization; the closed-loop verification can ensure the effectiveness of control instructions, and through feedback adjustment, the stability and reliability of the entire system can be improved; moreover, the automatic execution of the control of the extra-large mining height working face based on closed-loop feedback can improve the degree of automation, reduce manual operations and decisions, reduce labor intensity and human errors, thereby improving the applicability of the method provided by the embodiments of the present application and enhancing the continuity, efficiency, and stability in system production.

[0018] The following will, with reference to the accompanying drawings, elaborate on the technical solutions provided by the embodiments of the present application.

[0019] Figure 1 The following is a flowchart of a method for controlling an extra-large mining height working face based on closed-loop feedback provided by an embodiment of the present application. This method can be applied to a control center computer. As Figure 1 shown, the method for controlling an extra-large mining height working face based on closed-loop feedback may include the following steps: S101, collect the first multi-source control parameters of the extra-large mining height working face. In the embodiments of the present application, the multi-source control parameters of the extra-large mining height working face, that is, the first multi-source control parameters, can be collected. Exemplarily, data such as the pressure change rate of the extra-large mining height working face, the roof separation amount, the current mining height of the working face, the stiffness matrix of the hydraulic support, etc. can be collected. Alternatively, parameters such as the pressure vector of the hydraulic support, the three-dimensional position of the shearer, and the scalar of the roof separation amount can also be collected. An extra-large mining height working face refers to a working face in an extra-thick coal seam where the full-seam mining process is used for coal mining. The mining height (i.e., the height at which the shearer cuts the coal seam) of the extra-large mining height working face is relatively high (usually greater than 6 meters, and even up to 8.8 meters, 10 meters or more). Such a working face can achieve the one-time mining of relatively thick coal seams through advanced coal mining technologies and equipment, with high efficiency, high resource recovery rate, and intelligence. As an example, the first multi-source control parameters of the extra-large mining height working face can be collected through sensors, monitoring systems, etc.

[0020] It can be understood that the method for controlling an extra-large mining height working face based on closed-loop feedback provided by the embodiments of the present application can be executed periodically. Thus, when collecting the first multi-source control parameters of the extra-large mining height working face, the first multi-source control parameters of the extra-large mining height working face within a set period can be collected.

[0021] S102, calculate the device risk assessment value based on the first multi-source control parameters.

[0022] In the embodiments of the present application, after collecting the first multi-source control parameters of an extra-high mining height working face, the risk assessment value of the equipment, that is, the equipment risk assessment value, can be calculated based on the first multi-source control parameters. By evaluating the equipment risk assessment value of the equipment, it can provide a data basis for subsequent processing. As a quantified risk indicator, it can make the decision-making process faster and more accurate. Moreover, by evaluating the equipment risk assessment value, it can also provide a data basis for risk prevention of the equipment.

[0023] In a possible implementation manner, the first multi-source control parameters include the pressure change rate, the roof separation amount, the current mining height of the working face, and the stiffness matrix of the hydraulic support; The formula for calculating the equipment risk assessment value Risklevel based on the first multi-source control parameters is as follows:

[0024] Wherein, f 1 (x) is the pressure change rate risk item, P is the pressure change rate; f 2 (x) is the roof separation amount risk item, △L is the roof separation amount, H is the current mining height of the working face; f 3 (x) is the hydraulic support stiffness variation risk item, K is the real-time stiffness matrix, K 0 is the initial stiffness matrix, is the measure of the overall matrix difference, a is the normalization coefficient, w 1, w 2, w 3 are the weight coefficients.

[0025] In this way, by evaluating the pressure change rate, the roof separation amount, and the hydraulic support stiffness variation, potential safety risks can be discovered in a timely manner, preventive measures can be taken to avoid accidents; by monitoring the stiffness change of the hydraulic support, maintenance and repair activities can be planned more effectively to ensure the normal operation of the equipment; the relationship between the roof separation amount and the mining height is also considered, which helps to maintain the stability of the working face and prevent accidents such as roof collapse; at the same time, the equipment risk assessment value takes into account multiple factors, enabling the system to automatically adjust the control strategy according to different working conditions and enhancing the system's adaptive ability.

[0026] S103. Generate control instructions for multiple devices of the extra-high mining height working face based on the equipment risk assessment value, and transmit the control instructions to the multiple devices respectively, so that each device executes the control instructions.

[0027] In an embodiment of the present application, after calculating the device risk assessment value, control instructions for each device can be generated based on the device risk assessment value. Exemplarily, the control amount for each device can be determined first based on the device risk assessment value. Then, control instructions for each device can be generated based on the control amount of each device, and the control instructions can be transmitted to each device respectively. In this way, after each device receives the corresponding control instruction, it can perform corresponding operations based on the control instruction.

[0028] S104. After each device executes the control instruction, collect the second multi-source control parameters of each device after executing the control instruction.

[0029] In an embodiment of the present application, after each device executes the control instruction, the parameters of the device will also change. At this time, the multi-source control parameters of each device, that is, the second multi-source control parameters, can be collected again. Exemplarily, the second multi-source control parameters can include, for example, the control instruction of the device and the PID controller parameters. It can be understood that the second multi-source control parameters can also include, for example, the hydraulic support pressure vector, the roof separation scalar, the decision function, etc.

[0030] S105. Based on the second multi-source control parameters, determine whether the operation of the equipment in the ultra-high cutting height working face meets the preset performance requirements.

[0031] In an embodiment of the present application, after collecting the second multi-source control parameters of each device after executing the control instruction, the operation of the ultra-high cutting height working face can be verified based on the second multi-source control parameters to achieve the closed-loop feedback of the control method for the ultra-high cutting height working face. Exemplarily, by defining the preset performance requirements and calculating the actual performance indicators, comparing the two to determine whether the operation of the equipment in the ultra-high cutting height working face meets the preset performance requirements, and realizing the closed-loop feedback of the operation of the equipment in the ultra-high cutting height working face.

[0032] In an embodiment of the present application, by collecting the first multi-source control parameters of an extra-high mining height working face; calculating the equipment risk assessment value based on the first multi-source control parameters; generating control instructions for multiple devices on the extra-high mining height working face based on the equipment risk assessment value, and transmitting the control instructions to the multiple devices respectively, so that each device executes the control instructions; after each device executes the control instructions, collecting the second multi-source control parameters of each device after executing the control instructions; and determining whether the equipment operation condition of the extra-high mining height working face meets the preset performance requirements based on the second multi-source control parameters. In this way, by collecting the multi-source control parameters of the extra-high mining height working face, calculating the equipment risk assessment value, and generating control instructions based on this, precise control and closed-loop verification of devices such as hydraulic supports and shearers can be achieved. Thus, the pressure oscillation of the hydraulic support can be effectively reduced, the service life of the sealing parts can be increased, and the height control stability of the shearer can be maintained during geological mutations; moreover, by synchronously collecting and processing multi-source data, the time alignment error of cooperative control can also be reduced, and the reactive power consumption of the hydraulic system can be reduced, thereby improving the energy efficiency and safety of the entire extra-high mining height working face.

[0033] In some possible implementation manners, generating control instructions for multiple devices on the extra-high mining height working face based on the equipment risk assessment value includes: Adopting distributed decision-making to generate control quantities for multiple devices on the extra-high mining height working face based on the equipment risk assessment value; Using a preset contract net protocol to pre-distribute the control instructions for multiple devices; When receiving the bid response feedback results of multiple devices, generating control instructions for multiple devices based on the bid response feedback results; Transmitting the control instructions for multiple devices to the multiple devices respectively.

[0034] In an embodiment of the present application, when generating control instructions for multiple devices on the extra-high mining height working face based on the equipment risk assessment value, the control quantities for multiple devices on the extra-high mining height working face can be generated first based on the calculated equipment risk assessment value. For example, the control quantities of each device in the extra-high mining height working face can be generated by means of distributed decision-making. Then, based on the control quantities of each device, control instructions for each device can be generated through a preset contract net protocol, and the control instructions for each device can be pre-distributed. After each device receives the pre-distributed control instructions, a response result, that is, a bid response feedback result, can be fed back, so that the central computer can generate control instructions for each device based on the bid response feedback results of each device. After that, the control instructions for each device can be sent to the corresponding device.

[0035] In a further possible implementation manner, adopting distributed decision-making to generate control quantities for multiple devices on the extra-high mining height working face based on the equipment risk assessment value includes: Adopt a multi-agent distributed decision-making method, and generate control quantities of multiple devices based on a multi-objective optimization function and device risk assessment values.

[0036] In an embodiment of the present application, a multi-agent distributed decision-making method can be used to calculate a multi-objective optimization function and device risk assessment values to generate control quantities of respective devices.

[0037] Among them, the multi-objective optimization function can be preset as follows:

[0038] Among them, u is a control quantity vector, u i is the i th control quantity of the device, u n is a nominal control quantity, r i is the i th risk assessment value of the device, u safe is a device safety control threshold, R is an energy consumption weight matrix, J 1 (u) is a control quantity tracking nominal value objective function, J 2 (u) is a risk aversion objective function, J 3 (u) is an energy consumption minimization objective function, u T is a row vector of the control quantity vector (used to multiply the control quantity vector u by the energy consumption weight matrix R ).

[0039] The calculation method for generating control quantities of multiple devices by adopting a multi-agent distributed decision-making method based on a multi-objective optimization function and device risk assessment values is as follows:

[0040] Among them, G d is the control quantity of the device, R a is the risk assessment value corresponding to the device (that is, the risk assessment result corresponding to the device), β is a decision algorithm parameter, and D is a decision function.

[0041] In a further possible implementation, the preset contract net protocol includes a tendering stage, a bidding stage, and a winning bid decision-making stage. Among them, the tendering stage refers to sending control quantity task tuples to multiple devices respectively; the bidding stage refers to multiple devices feeding back bidding vectors; the winning bid decision-making stage refers to generating control instructions for multiple devices based on the bidding vectors. In this way, through the tendering and bidding processes, tasks can be allocated according to the actual situations and capabilities of each device, thereby achieving the optimal allocation of resources; the improved contract net protocol allows devices to quickly respond to task requirements, which can reduce the decision-making time and improve the overall response speed of the system; devices can feedback their own states and preferences through the bidding vectors, enabling the control center computer to flexibly adjust the control strategy according to real-time information; the generation of control instructions in the winning bid decision-making stage can ensure that the generated control instructions maximize the satisfaction of the system performance requirements and improve the control effect. In this way, through the structured tendering and bidding processes, unnecessary communication overhead can be reduced and communication efficiency can be improved.

[0042] In a further possible implementation, based on the second multi-source control parameters, determining whether the operation of the equipment in the ultra-high cutting height working face meets the preset performance requirements includes: Based on the second multi-source control parameters, calculating the equipment operation performance indicators of the ultra-high cutting height working face: Based on the equipment operation performance indicators, determining whether the operation of the equipment in the ultra-high cutting height working face meets the preset performance requirements.

[0043] In the embodiments of the present application, when determining whether the operation of the equipment in the ultra-high cutting height working face meets the preset performance requirements based on the second multi-source control parameters, that is, performing closed-loop verification, the equipment operation performance indicators of the ultra-high cutting height working face can be calculated first based on the second multi-source control parameters, and the calculation formula can be as follows: ; where, V c is the closed-loop verification result, P s , L m , D1 is the second multi-source control parameter after executing the control instruction; C i is the control instruction, and K is the PID controller parameter.

[0044] Then, based on the equipment operation performance indicators, it can be determined whether the operation of the equipment in the ultra-high cutting height working face meets the preset performance requirements, and the closed-loop verification of the ultra-high cutting height working face control method can be realized. Exemplarily, the verification can be carried out by comparing with a threshold. For example, the equipment operation performance indicators are compared with the preset performance requirement indicators. If the equipment operation performance indicators are greater than the preset performance requirements, it can be considered that the control effect meets the expectations, the system is stable, the control instruction is effective, the system performance is optimized, etc.; on the contrary, if the equipment operation performance indicators are less than or equal to the preset performance requirements, it can be considered that the control effect does not meet the expectations.

[0045] In some possible implementation manners, the first multi-source control parameter may further include a pressure change rate, a roof separation amount, a current mining height of the working face, and a hydraulic support stiffness matrix. An equipment risk assessment value Risklevel is calculated based on the pressure change rate, the roof separation amount, the current mining height of the working face, and the hydraulic support stiffness matrix. In this way, by evaluating the pressure change rate, the roof separation amount, and the variation of the hydraulic support stiffness, potential safety risks can be detected in a timely manner, preventive measures can be taken to avoid accidents; a quantitative risk index can also be provided for the control center, making the decision-making process faster and more accurate; the maintenance and repair activities can also be planned more effectively by monitoring the stiffness change of the hydraulic support to ensure the normal operation of the equipment; moreover, the relationship between the roof separation amount and the mining height is also considered, which helps to maintain the stability of the working face, prevent accidents such as roof collapse, and calculating the equipment risk assessment value by integrating multiple factors can enable the system to automatically adjust the control strategy according to different working conditions and enhance the adaptive ability.

[0046] Correspondingly, at this time, the method for calculating the equipment risk assessment value may be as follows:

[0047] Among them, f 1 (x) is the pressure change rate risk item, P is the pressure change rate; f 2 (x) is the roof separation amount risk item, △L is the roof separation amount, H is the current mining height of the working face; f 3 (x) is the hydraulic support stiffness variation risk item, K is the real-time stiffness matrix, K 0 is the initial stiffness matrix, is the measure of the overall matrix difference, a is the normalization coefficient, w 1, w 2, w 3 are the weight coefficients.

[0048] In some possible implementation manners, the first multi-source control parameter may further include a hydraulic support pressure vector, a three-dimensional position of a shearer, and a roof separation amount scalar; The above-mentioned control method for an extra-large mining height working face based on closed-loop feedback may further include: Calculating an equipment state fusion based on the hydraulic support pressure vector, the three-dimensional position of the shearer, and the roof separation amount scalar.

[0049] In the embodiments of the present application, device state fusion can also be calculated. For example, based on the hydraulic support pressure vector, the three-dimensional position of the shearer, and the roof separation scalar in the first multi-source control parameters, device state fusion can be calculated, and the calculation method can be as follows:

[0050] Wherein, P k is the hydraulic support pressure vector, S k is the three-dimensional position of the shearer, L k is the roof separation scalar, △u p is the flow rate adjustment of the hydraulic support pump station, V s is the shearer speed command, α is the pressure transfer coefficient (e.g., it can take a value of 0.15), β is the displacement dynamic coefficient (e.g., it can take a value of 0.8), I 3 represents a third-order identity matrix, W k is the process noise, △t is the sampling time interval.

[0051] In this way, by fusing multi-source data such as the hydraulic support pressure, the shearer position, and the roof separation amount, a more accurate device state fusion estimate can be obtained, thereby improving the response speed and accuracy of the control system; the dynamic coefficient in the state equation can also be used to predict the future device state of the system, which helps to make decisions in advance and reduce control errors caused by reaction lag; by considering the flow rate adjustment of the hydraulic support pump station and the shearer speed command, resources can be allocated more effectively, improving energy utilization and production efficiency; accurate state estimation helps to prevent equipment overload and improper operation, reduce equipment wear, extend service life, and thus reduce maintenance costs; at the same time, by real-time monitoring and predicting the roof separation amount, measures can be taken in time to prevent roof accidents and improve the safety of the working face; moreover, the state equation takes into account the process noise, enabling the algorithm to adapt to uncertainties under different working conditions and improving the robustness of the system.

[0052] To make the control method for an extra-large mining height working face provided by the embodiments of the present disclosure clearer, the following will be described in combination with specific examples. Referring to Figure 2 , the control method for an extra-large mining height working face provided by the embodiments of the present application may include the following steps: Step 1, the control center computer respectively collects the multi-source control parameters of the extra-large mining height working face, and the multi-source control parameters include hydraulic support pressure parameters, shearer position parameters, and roof separation amount parameters; Step 2, the control center computer performs equipment status fusion calculation at a set period; Step 3, the control center computer performs equipment risk assessment at a set period; Step 4, the control center computer adopts distributed decision-making and generates control quantities for multiple devices in an extra-high cutting height working face based on the equipment risk assessment; Step 5, the control center computer uses an improved contract net protocol for pre-distribution of task instructions. Multiple devices bid and respond to the instruction distribution of the control center computer respectively. The control center computer generates control instructions for multiple devices based on the feedback results of the bid responses and transmits them to multiple devices respectively; Step 6, multiple devices execute the control instructions; Step 7, the control center computer performs closed-loop verification of the control effect based on multi-source control parameters after the control instructions.

[0053] In this way, real-time data (such as multi-source control parameters) of the extra-high cutting height working face can be collected, providing a basis for subsequent analysis and decision-making; key parameters such as hydraulic support pressure, shearer position, and roof separation amount can be collected, different sources of data can be integrated, and the overall state of the working face can be obtained; the collected multi-source control parameters can be fused and calculated to obtain more comprehensive working face state information, evaluate the risks of equipment operation, and provide a basis for control decisions; also, according to the fused equipment state information, equipment risk assessment values can be carried out, potential safety hazards can be identified, and based on the equipment risk assessment values, a distributed decision-making algorithm can be used to generate control quantities for multiple devices in the extra-high cutting height working face; moreover, through the contract net protocol, efficient allocation of tasks can be achieved; at the same time, the working state of the equipment can be adjusted according to the control instructions, each device can perform corresponding operations according to the received control instructions, and the control effect of the extra-high cutting height working face can be verified through closed-loop feedback, ensuring the stability and safety of system operation.

[0054] In this way, through multi-source data fusion and distributed decision-making, equipment can be controlled more precisely, and production efficiency can be improved. The equipment risk assessment value helps to identify potential risks in advance, take preventive measures, and reduce the accident rate; the improved contract net protocol and bid response mechanism can allocate tasks more effectively and improve resource utilization; closed-loop verification can ensure the effectiveness of control instructions, and through feedback adjustment, the stability and reliability of the entire system can be improved; moreover, the automatic execution of the control of the extra-high cutting height working face based on closed-loop feedback can improve the degree of automation, reduce manual operations and decisions, reduce labor intensity and human errors, thereby improving the applicability of the method provided in the embodiments of the present application and enhancing the continuity, efficiency, and stability in system production.

[0055] In step 2, the state equation of the equipment status fusion calculation is:

[0056] Among them, P k is the pressure vector of the hydraulic support, S k is the three-dimensional position of the shearer, L k is the scalar of roof separation amount, △u p is the flow rate adjustment amount of the pump station of the hydraulic support, V s is the speed command of the shearer, α is the pressure transfer coefficient (e.g., it can take a value of 0.15), β is the displacement dynamic coefficient (e.g., it can take a value of 0.8), I 3 represents the third-order identity matrix, W k is the process noise, △t is the sampling time interval.

[0057] In step 3, the calculation formula for the equipment risk assessment value is:

[0058] Among them, f 1 (x) is the risk term of pressure change rate, P is the pressure change rate; f 2 (x) is the risk term of roof separation amount, △L is the roof separation amount, H is the current mining height of the working face; f 3 (x) is the risk term of the stiffness variation of the hydraulic support, K is the real-time stiffness matrix, K 0 is the initial stiffness matrix, is the measure of the overall difference of the matrix, a is the normalization coefficient, w 1, w 2, w 3 are the weight coefficients.

[0059] In step 4, when generating the control quantities of multiple devices in the ultra-high mining height working face, the multi-objective optimization function is:

[0060] Among them, u is the control quantity vector, u i is the i th control quantity of the device, u n is the nominal control quantity, ri is the risk assessment value of the i th device, u safe is the device safety control threshold, R is the energy consumption weight matrix, J 1 (u) is the control variable tracking nominal value objective function, J 2 (u) is the risk aversion objective function, J 3 (u) is the energy consumption minimization objective function, u T is the row vector of the control variable vector (used to multiply the control variable vector u by the energy consumption weight matrix R).

[0061] The control variables of multiple devices are generated using the following formula:

[0062] where, G d is the control variable of the device, R a is the risk assessment value corresponding to the device (i.e., the risk assessment result corresponding to the device), β is the decision algorithm parameter, and D is the decision function.

[0063] In step 5, the improved contract net protocol includes a tendering phase, a bidding phase, and a winning bid decision phase; in the tendering phase, the control center computer sends control variable task tuples to multiple devices respectively; in the bidding phase, multiple devices send bidding vectors to the control center computer respectively; in the winning bid decision phase, the control center computer generates control instructions for multiple devices based on the bidding vectors. Among them, the formula for generating control instructions in the winning bid decision phase is:

[0064] where, C i is the generated device control instruction, T P is the bidding vector, δ is the bidding response algorithm, and Bid is the winning bid decision function.

[0065] In step 7, the control center computer can use a multi-index fusion closed-loop verification algorithm to perform closed-loop verification on the control effect. The formula of the multi-index fusion closed-loop verification algorithm is as follows: ; where, V c is the closed-loop verification result, P s , L m , D1 is the second multi-source control parameter after executing the control instruction; C i is the control instruction, and K is the PID controller parameter.

[0066] Through multi-index fusion, the algorithm can more accurately evaluate the actual effect of control instructions, thereby adjusting and optimizing control parameters and improving control accuracy. Closed-loop verification ensures the stability of the control system during actual operation. By real-time monitoring and adjustment, it reduces the possibility of system oscillation and overshoot. Multi-index fusion considers multiple control parameters, which helps to comprehensively evaluate the control effect, thereby optimizing control performance and improving production efficiency. The algorithm can provide real-time feedback on the control effect, enabling the control center computer to quickly make adjustments to adapt to the dynamic changes in the working face environment.

[0067] The following uses specific examples to illustrate the control method for ultra-high mining height working faces based on closed-loop feedback of the present application, specifically as follows: Step 1, data acquisition: Hydraulic support pressure parameters: [24.5MPa, 23.8MPa, 25.2MPa]; Shearer position parameters: [10.2m, 3.5m, 1.8m]; Roof separation parameter: 0.6m; Step 2, equipment status fusion calculation; State equation parameters: Hydraulic support pressure vector: [24.5, 23.8, 25.2]; Shearer three-dimensional position: [10.2, 3.5, 1.8]; Roof separation scalar: 0.6; Flow rate adjustment of the hydraulic support pump station: 0.3m³ / min; Shearer speed command: 2.5m / min; Pressure transfer coefficient: 0.15; Displacement dynamic coefficient: 0.8; Process noise: [0.01, 0.02, 0.03]; Step 3, equipment risk assessment; Risk assessment parameters: Risk item of pressure change rate: 0.2; Risk item of roof separation: 0.15; Risk item of hydraulic support stiffness variation: 0.1; Weight coefficient: [0.5, 0.3, 0.2]; Step 4, distributed decision-making; Results of control quantity generation: Control quantity of equipment 1: 5kW; Control quantity of equipment 2: 3kW; Control quantity of equipment 3: 4kW; Step 5, contract net protocol; Bidding stage: The control center sends task tuples; Bidding stage: Equipment feedbacks bidding vectors; Bid-winning decision-making stage: Generate control instructions; Step 6, Execute the control instructions; The control amount executed by device 1: 5 kW; The control amount executed by device 2: 3 kW; The control amount executed by device 3: 4 kW; Step 7, Closed-loop verification; Closed-loop verification result: The control effect meets the expectation and the system is stable.

[0068] Closed-loop verification result: The control instructions are effective and the system performance is optimized.

[0069] The specific implementation and technical effects of each step in this embodiment are similar to those of the above method embodiment, and will not be elaborated here.

[0070] Based on the same inventive concept, the embodiment of the present application also provides a control device for an extra-high mining height working face based on closed-loop feedback. As Figure 3 shown, the control device 300 for an extra-high mining height working face based on closed-loop feedback includes: The first data acquisition module 310 is used to acquire the first multi-source control parameters of the extra-high mining height working face; The data calculation module 320 is used to calculate the equipment risk assessment value based on the first multi-source control parameters; The instruction control module 330 is used to generate control instructions for multiple devices of the extra-high mining height working face based on the equipment risk assessment value, and transmit the control instructions to the multiple devices respectively, so that each device executes the control instructions; The second data acquisition module 340 is used to acquire the second multi-source control parameters of each device after each device executes the control instructions; The control module 350 is used to determine whether the equipment operation condition of the extra-high mining height working face meets the preset performance requirements based on the second multi-source control parameters.

[0071] In a possible implementation manner, the instruction control module 330 is used for: Adopt distributed decision-making to generate the control amounts of multiple devices of the extra-high mining height working face based on the equipment risk assessment value; Adopt the preset contract net protocol to pre-distribute the control instructions of the multiple devices; In the case of receiving the bid response feedback results of the multiple devices, generate the control instructions of the multiple devices based on the bid response feedback results; Transmit the control instructions of the multiple devices to the multiple devices respectively.

[0072] In a possible implementation manner, the instruction control module 330 is used for: Adopt a multi-agent distributed decision-making method, and generate control quantities for multiple devices based on a multi-objective optimization function and the device risk assessment value.

[0073] In a possible implementation manner, the preset contract net protocol includes a tendering stage, a bidding stage, and a winning bid decision-making stage. Among them, in the tendering stage, a control quantity task tuple is sent to each of the multiple devices respectively; in the bidding stage, the multiple devices feedback bid vectors; and in the winning bid decision-making stage, control instructions for the multiple devices are generated based on the bid vectors.

[0074] In a possible implementation manner, the control module 350 is used for: Calculate the device operation performance index of the extra-high cutting height working face based on the second multi-source control parameter: Determine whether the operation condition of the devices in the extra-high cutting height working face meets the preset performance requirements based on the device operation performance index.

[0075] In a possible implementation manner, the first multi-source control parameter includes a pressure change rate, a roof separation amount, the current mining height of the working face, and a hydraulic support stiffness matrix; The data calculation module 320 is used for:

[0076] Among them, f 1 (x) is the pressure change rate risk item, P is the pressure change rate; f 2 (x) is the roof separation amount risk item, △L is the roof separation amount, H is the current mining height of the working face; f 3 (x) is the hydraulic support stiffness variation risk item, K is the real-time stiffness matrix, K 0 is the initial stiffness matrix, is the measure of the overall difference of the matrix, a is the normalization coefficient, w 1, w 2, w 3 are weight coefficients.

[0077] In a possible implementation manner, the first multi-source control parameter includes a hydraulic support pressure vector, the three-dimensional position of a shearer, and a roof separation amount scalar; The control device 300 for the extra-high cutting height working face based on closed-loop feedback further includes a state calculation module, which is used for: Calculate the device state fusion based on the hydraulic support pressure vector, the three-dimensional position of the shearer, and the roof separation amount scalar.

[0078] The specific implementation manners and technical effects of the device provided by the embodiments of the present application are similar to those of the above method embodiments, and will not be elaborated herein.

[0079] According to the embodiments of the present application, the present application also discloses an electronic device, a computer-readable storage medium, and a computer program product.

[0080] Figure 4 FIG. shows a schematic block diagram of an exemplary electronic device 400 that can be used to implement the embodiments of the present application. The electronic device 400 is intended to represent various forms of digital computers, such as, for example, a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as, for example, a personal digital processor, a cellular phone, a smart phone, a wearable device, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely exemplary and are not intended to limit the implementation of the present application described and / or claimed herein.

[0081] As Figure 4 shown, the electronic device 400 includes a computing unit 401, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 402 or a computer program loaded from a storage unit 408 into a random access memory (RAM) 403. In the RAM 403, various programs and data required for the operation of the electronic device 400 can also be stored. The computing unit 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0082] A plurality of components in the electronic device 400 are connected to the I / O interface 405, including: an input unit 406, such as a keyboard, a mouse, etc.; an output unit 407, such as various types of displays, speakers, etc.; a storage unit 408, such as a magnetic disk, an optical disk, etc.; and a communication unit 409, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 409 allows the electronic device 400 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0083] The computing unit 401 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 401 executes the various methods and processes described above, such as the fully mechanized caving face control method based on closed-loop feedback. For example, in some embodiments, the fully mechanized caving face control method based on closed-loop feedback can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 408. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 400 via the ROM 402 and / or the communication unit 409. When the computer program is loaded into the RAM 403 and executed by the computing unit 401, one or more steps of the fully mechanized caving face control method described above can be executed. Alternatively, in other embodiments, the computing unit 401 can be configured to execute the fully mechanized caving face control method by any other suitable means (e.g., by means of firmware).

[0084] The various embodiments of the systems and techniques described above in this document can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a dedicated or general-purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0085] The program code of the computer program product for implementing the methods of the present application can be written in any combination of one or more programming languages. These program codes can be provided to the processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing devices, such that when the program codes are executed by the processor or controller, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The program codes can be executed entirely on the machine, partially on the machine, as an independent software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0086] In the context of this application, a computer-readable storage medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A computer-readable storage medium can be a machine-readable signal medium or a machine-readable storage medium. A computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of a computer-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0087] To provide for interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can also be used to provide for interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic, speech, or tactile input).

[0088] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of a communication network include: a local area network (LAN), a wide area network (WAN), the Internet, and a blockchain network.

[0089] A computer system may include a client and a server. The client and the server are generally far away from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the respective computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system, and solves the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services ("Virtual Private Server", or simply "VPS"). The server may also be a server of a distributed system, or a server combined with a blockchain.

[0090] It should be understood that various forms of the processes shown above can be used, steps can be reordered, added or deleted. For example, the steps recited in this application can be executed in parallel, sequentially or in a different order, as long as the desired results of the technical solutions disclosed in this application can be achieved, and no limitation is made herein.

[0091] The above specific embodiments do not constitute a limitation on the protection scope of this application. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principle of this application shall be included within the protection scope of this application.

Claims

1. A control method for an extra-high mining face based on closed-loop feedback, characterized in that, Including: Collecting the first multi-source control parameters of an extra-large mining height working face; Calculating the equipment risk assessment value based on the first multi-source control parameters; Generating control instructions for multiple devices on the extra-large mining height working face based on the equipment risk assessment value, and transmitting the control instructions to the multiple devices respectively, so that each device executes the control instructions; After each device executes the control instructions, collecting the second multi-source control parameters of each device after executing the control instructions; Based on the second multi-source control parameters, determining whether the equipment operation condition of the extra-large mining height working face meets the preset performance requirements.

2. The control method for an extra-large mining height working face based on closed-loop feedback according to claim 1, characterized in that, The generating control instructions for multiple devices on the extra-large mining height working face based on the equipment risk assessment value includes: Adopting distributed decision-making to generate the control quantities of multiple devices on the extra-large mining height working face based on the equipment risk assessment value; Using a preset contract net protocol for pre-distributing the control instructions of the multiple devices; When receiving the bid response feedback results of the multiple devices, generating the control instructions for the multiple devices based on the bid response feedback results; Transmitting the control instructions of the multiple devices to the multiple devices respectively.

3. The control method for an extra-high cutting height working face based on closed-loop feedback according to claim 2, characterized in that, The adopting distributed decision-making to generate the control quantities of multiple devices on the extra-large mining height working face based on the equipment risk assessment value includes: Adopting a multi-agent distributed decision-making method to generate the control quantities of multiple devices based on a multi-objective optimization function and the equipment risk assessment value.

4. The control method for an extra-high mining face based on closed-loop feedback according to claim 2, characterized in that, The preset contract net protocol includes a tendering stage, a bidding stage, and a winning bid decision-making stage. Among them, the tendering stage refers to sending control quantity task tuples to the multiple devices respectively; the bidding stage refers to the multiple devices feeding back bid vectors; the winning bid decision-making stage refers to generating the control instructions for the multiple devices based on the bid vectors.

5. The control method for an extra-high mining height working face based on closed-loop feedback according to claim 1, characterized in that The determining whether the equipment operation condition of the extra-large mining height working face meets the preset performance requirements based on the second multi-source control parameters includes: Calculating the equipment operation performance index of the extra-large mining height working face based on the second multi-source control parameters; Based on the equipment operation performance index, determining whether the equipment operation condition of the extra-large mining height working face meets the preset performance requirements.

6. The control method for an extra-high cutting height working face based on closed-loop feedback according to claim 1, wherein The first multi-source control parameters include the pressure change rate, roof separation amount, current mining height of the working face, and hydraulic support stiffness matrix; The method for calculating the equipment risk assessment value Risklevel based on the first multi-source control parameters is as follows: Among them, f 1 (x) is the pressure change rate risk term, P is the pressure change rate; f 2 (x) is the roof separation amount risk term, △L is the roof separation amount, H is the current mining height of the working face; f 3 (x) is the hydraulic support stiffness variation risk term, K is the real-time stiffness matrix, K 0 is the initial stiffness matrix, is a measure of the overall matrix difference, a is the normalization coefficient, w 1, w 2, w 3 are the weight coefficients.

7. The control method for an extra-large mining height working face based on closed-loop feedback according to claim 1, wherein The first multi-source control parameters include the hydraulic support pressure vector, three-dimensional position of the shearer, and roof separation amount scalar; The method further includes: Calculating the equipment state fusion based on the hydraulic support pressure vector, three-dimensional position of the shearer, and roof separation amount scalar.

8. A control device for an extra-high cutting height working face based on closed-loop feedback, characterized in that, Including: A first data acquisition module for collecting the first multi-source control parameters of an extra-large mining height working face; A data calculation module for calculating the equipment risk assessment value based on the first multi-source control parameters; An instruction control module for generating control instructions for multiple devices on the extra-large mining height working face based on the equipment risk assessment value, and transmitting the control instructions to the multiple devices respectively, so that each device executes the control instructions; The second data acquisition module is used to collect the second multi-source control parameters of each device after each device executes the control instruction. The control module is used for the data acquisition module to determine whether the operation of the equipment in the ultra-high cutting height working face meets the preset performance requirements based on the second multi-source control parameters.

9. An electronic device, characterized in that, It includes: A processor; A memory for storing executable instructions of the processor; Wherein, the processor is configured to execute the instructions to implement the method according to any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, The computer program implements the method according to any one of claims 1-7 when executed by the processor.

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