Fully-mechanized coal mining diagnosis system

Abstract

The invention discloses a fully-mechanized coal mining diagnosis system, and relates to the technical field of mining engineering intelligent control, and the system comprises a diagnosis controller, a front-end configuration system, and a 10-gigabit looped network. The diagnosis controller is used for acquiring fully-mechanized coal mining equipment parameters of fully-mechanized coal mining equipment through the 10-gigabit looped network, diagnosing the fully-mechanized coal mining equipment and a fully-mechanized coal mining process of the fully-mechanized coal mining equipment according to the fully-mechanized coal mining equipment parameters, acquiring a diagnosis result of the fully-mechanized coal mining equipment, and feeding back the diagnosis result to the front-end configuration system; the front-end configuration system is used for receiving the diagnosis result sent by the diagnosis controller, generating alarm information of the fully-mechanized coal mining equipment according to the diagnosis result, carrying out technological parameter configuration, control instruction issuing, equipment technological state information display and diagnosis result submission of the fully-mechanized coal mining technology, and sending the alarm information of the fully-mechanized coal mining equipment to the diagnosis controller in the diagnosis process of the diagnosis controller; storing diagnosis parameters, control instructions and alarm information corresponding to the fully-mechanized coal mining equipment; the 10-gigabit looped network is used for sending parameters of the fully-mechanized mining equipment to the diagnosis controller.

Description

Technical Field

[0001] This application relates to the field of intelligent control technology for mining engineering, and in particular to a fully mechanized mining diagnostic system. Background Technology

[0002] Coal mining has undergone continuous transformation since the realization of mechanization. After experiencing the development of automation, informatization, and digitalization technologies, it has now entered a period of accelerated construction of smart mines. The fully mechanized mining face is one of the work sites with a large concentration of personnel underground. It has a large number of fully mechanized coal mining equipment (fully mechanized mining equipment) and the fully mechanized coal mining process (fully mechanized mining process) is complex. It bears the heavy responsibility of unmanned and minimally manned operations and is a key focus of intelligent construction.

[0003] The relevant technologies have been tested in multiple fully mechanized mining faces to achieve automated coal cutting. Through field trials, the automated functions such as coal cutting with memory function, automatic support following and pulling, random video imaging of the working face, and remote intervention have been gradually improved, realizing automated coal cutting in fully mechanized mining faces.

[0004] However, due to the complex environment, technology, and equipment conditions in underground coal mines, unplanned shutdowns and safety accidents are prone to occur during the operation of fully mechanized mining equipment, which seriously affect production safety and efficiency. Summary of the Invention

[0005] In view of this, this application provides a fully mechanized mining diagnostic system and method, the main purpose of which is to solve the technical problem that current related technologies are limited by the complex environment, technology and equipment conditions in coal mines, which easily lead to unplanned shutdowns and safety accidents during the operation of fully mechanized mining equipment, seriously affecting production safety and efficiency.

[0006] According to a first aspect of this application, a fully mechanized mining diagnostic system is provided, comprising: a diagnostic controller, a front-end configuration system, and a 10 Gigabit ring network; The diagnostic controller is used to acquire the parameters of the fully mechanized mining equipment at different diagnostic stages through the 10 Gigabit ring network, diagnose the fully mechanized mining equipment and the fully mechanized mining process of the fully mechanized mining equipment according to the parameters, acquire the diagnostic results of the fully mechanized mining equipment at different diagnostic stages, and feed the diagnostic results back to the front-end configuration system. The front-end configuration system is used to receive the diagnostic results sent by the diagnostic controller at different diagnostic stages, generate alarm information of the fully mechanized mining equipment based on the diagnostic results, configure process parameters of the fully mechanized mining process, issue control commands, display equipment process status information and report diagnostic results, and store the diagnostic parameters, control commands and alarm information corresponding to the fully mechanized mining equipment during the diagnostic process of the diagnostic controller. The 10 Gigabit ring network is used to provide communication links and data channels with the fully mechanized mining equipment, obtain the fully mechanized mining equipment parameters at different diagnostic stages based on the communication links and data channels, and send the fully mechanized mining equipment parameters at different diagnostic stages to the diagnostic controller.

[0007] By employing the above technical solution, this application provides a fully mechanized mining diagnostic system. This system uses a 10-gigabit ring network to collect parameters of the fully mechanized mining equipment in real time at different diagnostic stages. A diagnostic controller diagnoses the fully mechanized mining equipment and its mining process based on these parameters, obtaining diagnostic results at different stages. These results are then fed back to the front-end configuration system in real time. The front-end configuration system generates alarm information for the fully mechanized mining equipment based on these results, providing timely alerts when abnormalities occur. This system constructs an intelligent safety management system integrating multiple diagnostic stages of the fully mechanized mining equipment and its processes. It provides timely and effective early warnings for the safety of the fully mechanized mining equipment and system, achieving safety monitoring throughout the entire fully mechanized mining operation. This reduces unplanned downtime and safety accidents, ensures production safety, and ultimately improves the intelligence level and efficiency of fully mechanized mining operations.

[0008] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0009] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This diagram illustrates the structure of a comprehensive mining diagnostic system provided in an embodiment of the present invention. Figure 2 A schematic diagram of the structure of a diagnostic controller provided in an embodiment of the present invention is shown; Figure 3 This invention provides a flowchart of a device calibration and diagnostic process according to an embodiment of the present invention. Figure 4 This invention provides a flowchart of a device self-test diagnostic process according to an embodiment of the present invention. Figure 5 This invention provides a process self-inspection and diagnostic flowchart. Figure 6 A flowchart of a pose diagnosis method provided by an embodiment of the present invention is shown; Figure 7A flowchart of a comprehensive mining diagnostic system provided by an embodiment of the present invention is shown; In the picture: 1-Diagnostic controller, 11-Equipment calibration module, 12-Equipment self-test module, 13-Process self-test module, 14-Position diagnosis module, 15-Pre-inspection module; 2-Front-end configuration system; 3-10 Gigabit Ring Network. Detailed Implementation

[0010] The present application will be described in detail below with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in the embodiments of the present application can be combined with each other.

[0011] Currently, due to the complex environment, technology, and equipment limitations in underground coal mines, existing fully mechanized mining control systems struggle to provide timely and effective early warnings and circuit breakers for equipment and system safety, leading to unplanned shutdowns and safety accidents that severely impact production safety and efficiency. With the development of IoT, big data, and AI technologies, developing an intelligent management system suitable for fully mechanized mining operations and integrating self-calibration, self-inspection, and self-diagnosis functions for equipment and processes is of great significance for improving the intelligence and adaptability of coal mines, enhancing production efficiency, and ensuring production safety.

[0012] To address the aforementioned problems, embodiments of the present invention provide a comprehensive mining diagnostic system, such as... Figure 1 As shown, the system includes: a diagnostic controller 1, a front-end configuration system 2, and a 10 Gigabit ring network 3. The diagnostic controller 1 is used to acquire the parameters of the fully mechanized mining equipment at different diagnostic stages through the 10 Gigabit ring network 3, diagnose the fully mechanized mining equipment and its fully mechanized mining process based on the parameters, acquire the diagnostic results of the fully mechanized mining equipment at different diagnostic stages, and feed the diagnostic results back to the front-end configuration system 2. The front-end configuration system 2 is used to receive the diagnostic results sent by the diagnostic controller 1 at different diagnostic stages, generate alarm information for the fully mechanized mining equipment based on the diagnostic results, configure the process parameters of the fully mechanized mining process, issue control commands, display equipment process status information, and report diagnostic results. During the diagnostic process of the diagnostic controller 1, it also stores the diagnostic parameters, control commands, and alarm information corresponding to the fully mechanized mining equipment. The 10 Gigabit ring network 3 is used to provide a communication link and data channel with the fully mechanized mining equipment, acquire the parameters of the fully mechanized mining equipment at different diagnostic stages based on the communication link and data channel, and send the parameters of the fully mechanized mining equipment at different diagnostic stages to the diagnostic controller 1.

[0013] Among them, the diagnostic controller 1 is the control center of the entire system. It completes the functions of calibration, self-inspection, position diagnosis, and pre-inspection of the fully mechanized mining equipment and process, coordinates the safe operation of each fully mechanized mining equipment (operating equipment), and feeds back the diagnostic results to the front-end configuration system 2 for user decision-making. For example, the diagnostic controller 1 can be an industrial controller with fault self-diagnosis function. It can obtain and analyze the parameters of the fully mechanized mining equipment in real time through the 10 Gigabit ring network 3, identify whether the fully mechanized mining equipment is abnormal at different operating stages based on different diagnostic stages, locate the faults of the fully mechanized mining equipment, and perform intelligent diagnosis of the health of the fully mechanized mining equipment and process execution. The diagnostic results are fed back to the front-end configuration system 2 to realize the intelligent and safe operation of the fully mechanized mining face.

[0014] Specifically, fully mechanized mining equipment may include coal mining machines, scraper conveyors, hydraulic supports, transfer conveyors, crushers, emulsion pump stations, belt conveyors (conveyor belt conveyors), power supply systems, automated control systems, cooling spray systems, etc.; fully mechanized mining technology may include the technical methods and operational procedures for completing the entire coal mining process using fully mechanized mining equipment; fully mechanized mining equipment parameters may refer to the operating data of equipment such as coal mining machines, hydraulic supports, and scraper conveyors, such as current, voltage, temperature, pressure, position, speed, etc. Correspondingly, different diagnostic stages can be defined as stages with different diagnostic functions based on the operation process of the fully mechanized mining equipment, such as: the equipment verification stage before the fully mechanized mining equipment starts, the equipment self-inspection stage after the fully mechanized mining equipment starts, the process self-inspection stage after the fully mechanized mining process starts, the posture diagnosis stage after the fully mechanized mining process starts, and the pre-inspection stage after the fully mechanized mining equipment has been running for a period of time. Correspondingly, the diagnostic results include the diagnostic results of different diagnostic stages, such as the equipment verification results corresponding to the equipment verification stage, the equipment self-inspection results corresponding to the equipment self-inspection stage, the process self-inspection results corresponding to the process self-inspection stage, the posture diagnosis results corresponding to the posture diagnosis stage, and the pre-inspection results corresponding to the pre-inspection stage. Based on the diagnostic results of these stages, safety monitoring of the entire fully mechanized mining operation process can be realized, the level of intelligence in fully mechanized mining operations can be improved, production efficiency can be increased, and production safety can be guaranteed.

[0015] In some embodiments, the front-end configuration system 2 serves as a human-machine interface, providing a human-machine collaboration interface to configure equipment process parameters, issue diagnostic system commands, display equipment process status information, and report diagnostic results; it also stores important parameters such as parameters, control commands, and alarms during the fully mechanized mining diagnosis process. The front-end configuration system 2 may include host computer monitoring software (such as WinCC or KingSCADA) to display a visual interface for information such as the status of fully mechanized mining equipment, alarm information, process flow, equipment process status information, and diagnostic results. This graphical interface enables monitoring, control, and data management of the fully mechanized mining equipment, allowing staff to promptly view equipment status and take corresponding measures to ensure production safety.

[0016] For example, after receiving the diagnostic results sent by the diagnostic controller 1, the front-end configuration system 2 can analyze the diagnostic results. If it is determined that there is an abnormality in the fully mechanized mining equipment, it can generate an alarm message corresponding to the abnormality to remind the staff to perform equipment maintenance and ensure production safety. Accordingly, the alarm message notification methods may include audible and visual alarms, pop-up notifications, SMS notifications, etc., and the alarm messages can also be classified into levels, such as "notification", "warning", "serious fault", etc.

[0017] Correspondingly, the front-end configuration system 2 can also be used to configure fully mechanized mining process parameters, such as: coal mining machine traction speed, hydraulic support shifting distance, scraper conveyor start / stop logic, etc.; it can also be used to send control commands from the front-end system to the diagnostic controller 1 or fully mechanized mining equipment, such as: starting the coal mining machine, emergency shutdown, automatic support shifting, etc.; and upload the diagnostic results to the upper-level system, such as: mine dispatch center, equipment health management system (PHM), cloud big data platform, etc.; and during the diagnostic process of the diagnostic controller 1, it can store the corresponding diagnostic parameters, control commands, alarm information, etc. of the fully mechanized mining equipment in real time, specifically to a local database (such as SQL Server, MySQL) or a distributed database, so as to persistently save the key data generated during system operation, which is convenient for fault tracing and big data analysis, equipment pre-inspection, etc.

[0018] In some embodiments, the 10 Gigabit ring network 3 serves as a bridge for the entire fully mechanized mining diagnostic system, providing communication links and data channels between the system and the fully mechanized mining equipment. The communication link can refer to a physical connection path, such as a fiber optic cable, used for signal transmission between the fully mechanized mining equipment. The data channel can be a logical transmission channel established on the communication link, used for transmitting parameters of the fully mechanized mining equipment, enabling the diagnostic controller 1 to monitor the parameters of the fully mechanized mining equipment at different operating stages in real time through the 10 Gigabit ring network 3.

[0019] For example, a large coal mine adopts an intelligent fully mechanized mining face, which can be equipped with fully mechanized mining equipment such as coal mining machines, hydraulic supports, and scraper conveyors, and deploys a 10-gigabit ring network 3. The fully mechanized mining equipment parameters of each fully mechanized mining equipment are collected in real time through the 10-gigabit ring network 3 and sent to the corresponding diagnostic controller 1 in real time.

[0020] Compared with existing technologies, the fully mechanized mining diagnostic system provided in this application collects the parameters of the fully mechanized mining equipment in real time at different diagnostic stages through a 10-gigabit ring network 3. The diagnostic controller 1 diagnoses the fully mechanized mining equipment and its mining process based on these parameters, obtaining diagnostic results at different diagnostic stages. These results are then fed back to the front-end configuration system 2 in real time. The front-end configuration system 2 generates alarm information for the fully mechanized mining equipment based on the diagnostic results, providing timely alerts when abnormalities occur. This constructs an intelligent safety management system integrating multiple diagnostic stages of fully mechanized mining equipment and processes, providing timely and effective early warnings for the safety of the equipment and system. This achieves safety monitoring throughout the entire fully mechanized mining operation, thereby reducing unplanned downtime and safety accidents, ensuring production safety, and ultimately improving the intelligence level and efficiency of fully mechanized mining operations.

[0021] Furthermore, exemplary, such as Figure 2 The diagram shows the composition of the diagnostic controller 1. As the control center of this system, the diagnostic controller 1 can include modules such as equipment verification module 11, equipment self-test module 12, process self-test module 13, posture diagnosis module 14, and pre-inspection module 15. These modules are used to perform functions such as equipment verification, equipment self-test, process self-test, self-test, posture diagnosis, and pre-inspection, respectively. The modules work together and support each other to form a unified operating system. The diagnostic controller 1 is also used to coordinate the safe operation of each piece of equipment and to feed back the diagnostic results to the front-end configuration system 2 for user decision-making.

[0022] Optionally, the diagnostic controller 1 may include an equipment verification module 11; the equipment verification module 11 is used to verify whether the parameters of the fully mechanized mining equipment meet the equipment start-up conditions before the fully mechanized mining equipment is started, obtain the equipment verification results of the fully mechanized mining equipment, and feed the equipment verification results back to the front-end configuration system 2; the equipment start-up conditions may include, but are not limited to, emergency stop closing, normal communication, normal frequency converter, no overcurrent, overvoltage or overtemperature of the motor, normal pressure sensor, normal position sensor, etc.

[0023] Optionally, the equipment verification module 11 includes a verification diagnostic result library; the verification diagnostic result library is used to integrate diagnostic prompt codes and display codes, and match the diagnostic prompt codes and display codes corresponding to the equipment verification results; the equipment verification module 11 is used to determine the equipment verification flag bit of the fully mechanized mining equipment according to the parameters of the fully mechanized mining equipment before the fully mechanized mining equipment is started; the equipment verification result of the fully mechanized mining equipment is determined according to the equipment verification flag bit, and the diagnostic prompt code and display code corresponding to the equipment verification result are output to the front-end configuration system 2. The equipment verification flag bit is used to mark whether the equipment start-up status of the fully mechanized mining equipment is normal; the front-end configuration system 2 is used to generate equipment verification alarm information corresponding to the fully mechanized mining equipment according to the diagnostic prompt code and display code corresponding to the equipment verification result before the fully mechanized mining equipment is started. The equipment verification alarm information includes the abnormal location and abnormal solution of the equipment corresponding to the fully mechanized mining equipment.

[0024] The verification and diagnostic result library can be used to configure the diagnostic prompt codes and display codes corresponding to each fully mechanized mining equipment during the verification stage, as well as the abnormal information corresponding to each diagnostic prompt code and display code. It can be built into the equipment verification module 11 and intelligently match the equipment verification results during the equipment verification process. The equipment verification results can include abnormally started equipment detected in the fully mechanized mining equipment before the equipment is started, as well as the diagnostic prompt codes and display codes corresponding to the abnormally started equipment. The equipment verification alarm information can be the equipment verification alarm information corresponding to the equipment verification results generated based on the intelligent matching results between the verification and diagnostic result library and the equipment verification results, which is used to provide early warning of whether the equipment is starting normally before the fully mechanized mining equipment is started.

[0025] In some embodiments, the equipment verification module 11 can be used to perform equipment verification and diagnosis before the fully mechanized mining equipment is started, to diagnose whether the fully mechanized mining equipment meets the conditions for equipment start-up. The equipment verification function has a built-in verification and diagnosis result library, which integrates the diagnostic prompt codes ErrorCode and display codes ErrorShow corresponding to the equipment verification and diagnosis stages. It intelligently matches the equipment verification results and outputs the equipment verification results to the front-end configuration system 2 through the display code ErrorShow, so that users can take corresponding countermeasures.

[0026] For example, such as Figure 3The diagram illustrates the equipment calibration and diagnostic flowchart. First, the ProofreadingFlag flag can be defined. Specifically, after system startup, the diagnostic controller 1 reads the parameters of the fully mechanized mining equipment via the 10 Gigabit ring network 3 and begins equipment calibration. The calibration checks whether the equipment parameters meet the equipment startup conditions, such as whether the emergency stop is closed, whether communication is normal, whether the frequency converter is normal, whether the motor is experiencing overcurrent, overvoltage, or overtemperature, whether the pressure sensor is normal, and whether the position sensor is normal. If the equipment calibration result is normal, ProofreadingFlag=0 is returned; if the equipment calibration result is abnormal, ProofreadingFlag=1 is returned, and the diagnostic prompt code ErrorCode and display code ErrorShow corresponding to the abnormally started equipment are fed back to the front-end configuration system 2. The front-end configuration system 2 then provides the location and solution for the abnormal equipment. After the abnormality is resolved, the system can calibrate again until the equipment calibration result is normal, returning ProofreadingFlag=0, and the equipment calibration ends.

[0027] For example, during the calibration and diagnosis of a coal mining machine, when ProofreadingFlag=1, ErrorCode=42, and ErrorShow=50, the front-end configuration system 2 can analyze the abnormal information corresponding to diagnostic prompt code 42 and display code 50 of the coal mining machine's calibration result based on the abnormal information corresponding to each diagnostic prompt code and display code in the calibration and diagnosis result database, and display it, such as "The coal mining machine cannot operate normally; the right inverter IGBT has an over-temperature fault. Please check the right traction inverter to ensure safe operation of the equipment." As another example, when calibrating and diagnosing an emulsion pump, when ProofreadingFlag=1, ErrorCode=5001, and ErrorShow=5010, the abnormal information corresponding to these values ​​is analyzed, and the front-end configuration system 2 displays "The emulsion pump cannot operate normally; the pump station communication is abnormal. Please check the communication."

[0028] Optionally, the diagnostic controller 1 may also include a device self-test module 12; the device self-test module 12 is used to detect the fully mechanized mining equipment using the device verification module 11, determine that the fully mechanized mining equipment meets the equipment start-up conditions, and after starting the fully mechanized mining equipment, obtain the fully mechanized mining equipment parameters after starting the fully mechanized mining equipment through the 10 Gigabit ring network 3; based on the fully mechanized mining equipment parameters after starting the fully mechanized mining equipment, perform safety diagnosis on the equipment operation process of the fully mechanized mining equipment, and obtain the device self-test results of the fully mechanized mining equipment.

[0029] Optionally, the equipment self-test module 12 may include a self-test diagnostic result library; the self-test diagnostic result library is used to integrate diagnostic prompt codes and display codes, and match the diagnostic prompt codes and display codes corresponding to the equipment self-test results; the equipment verification module 11 is used to determine the equipment self-test flag bit of the fully mechanized mining equipment according to the parameters of the fully mechanized mining equipment after startup during the operation of the fully mechanized mining equipment; determine the equipment self-test result of the fully mechanized mining equipment according to the equipment self-test flag bit, and output the diagnostic prompt codes and display codes corresponding to the equipment self-test result to the front-end configuration system 2; the equipment self-test flag bit is used to mark whether the equipment operation status of the fully mechanized mining equipment is normal; the front-end configuration system 2 is used to generate equipment self-test alarm information corresponding to the fully mechanized mining equipment according to the diagnostic prompt codes and display codes corresponding to the equipment self-test results during the operation of the fully mechanized mining equipment.

[0030] The self-test diagnostic result library can be used to configure the diagnostic prompt codes and display codes corresponding to each fully mechanized mining equipment during the self-test phase (such as the equipment self-test phase and the process self-test phase), as well as the abnormal information corresponding to each diagnostic prompt code and display code. It can be built into the equipment self-test module 12 or the process self-test module 13, and intelligently match the equipment self-test results during the equipment self-test or process self-test process. The equipment self-test results can include abnormal operating equipment detected in the fully mechanized mining equipment after the fully mechanized mining equipment is started, as well as the diagnostic prompt codes and display codes corresponding to the abnormal operating equipment. It can also include abnormal processes detected in the fully mechanized mining process after the fully mechanized mining process is started, as well as the diagnostic prompt codes and display codes corresponding to the abnormal processes. The equipment self-test alarm information can be the equipment self-test alarm information corresponding to the equipment self-test results generated according to the intelligent matching results between the self-test diagnostic result library and the equipment self-test results. It is used to provide early warning of whether the equipment or process is operating normally after the fully mechanized mining equipment or fully mechanized mining process is started.

[0031] In some embodiments, the device self-test module 12 can be used to perform device self-test diagnosis after the device is started, to perform safety diagnosis of the device operation process, and to ensure that the device operates safely and reliably. The device self-test diagnosis function has a built-in self-test diagnosis result library, which integrates diagnostic prompt codes ErrorCode and display codes ErrorShow. It intelligently matches the device self-test results and outputs the results to the front-end configuration system 2 through the display code ErrorShow, so that users can take corresponding countermeasures.

[0032] For example, such as Figure 4The diagram shows the equipment self-check diagnostic flowchart. To better illustrate this function, the equipment self-check flag (Self-checkFlag) is defined first. Specifically, in response to the startup of the fully mechanized mining diagnostic system, the diagnostic controller 1 reads the fully mechanized mining equipment parameters through the 10 Gigabit ring network 3 and begins the equipment self-check. First, the equipment verification module 11 performs the equipment verification and diagnostic function to ensure that the functions are complete before the equipment starts running. After the fully mechanized mining equipment starts running, the diagnostic controller 1 reads the fully mechanized mining equipment parameters after startup and checks whether the parameters meet the normal operating conditions of the equipment. The normal operating conditions may include, but are not limited to: whether the emergency stop is closed, whether the communication is normal, whether the frequency converter is normal, whether the motor is overcurrent, overvoltage, or overtemperature, whether the pressure sensor is normal, and whether the position sensor is normal, etc. If the equipment self-test result is normal, it returns Self-checkFlag=0, indicating that fully mechanized mining equipment in the start-up state starts normally and fully mechanized mining equipment in the working state works normally. If the equipment self-test result is abnormal, it returns Self-checkFlag=1, indicating that fully mechanized mining equipment in the start-up state cannot start and fully mechanized mining equipment in the working state stops working. The system also feeds back the diagnostic error code ErrorCode and display code ErrorShow corresponding to the abnormal equipment self-test result to the front-end configuration system 2, providing the location of the equipment abnormality and a solution. After the abnormality is resolved, the system performs a self-test again until the diagnostic result is normal, then returns Self-checkFlag=0, and the fully mechanized mining equipment self-test ends.

[0033] For example, when the coal mining machine is in operation, the equipment self-check module 12 performs a self-check diagnosis. When Self-checkFla=1, ErrorCode=1, and ErrorShow=1, the front-end configuration system 2 displays "The coal mining machine has stopped working; the main body emergency stop has been triggered. Please check the emergency stop to ensure normal equipment operation." As another example, during the scraper conveyor self-check diagnosis, when Self-checkFla=1, ErrorCode=1002, and ErrorShow=1025, the front-end configuration system 2 displays "The scraper conveyor has stopped working; the main power supply circuit of the tail unit is faulty. Please check the tail unit." Similarly, during the emulsion pump 1 self-check diagnosis, when Self-checkFla=1, ErrorCode=5030, and ErrorShow=5041, the front-end configuration system 2 displays "The emulsion pump has stopped working; the oil temperature sensor is disconnected. Please check the oil temperature sensor."

[0034] Optionally, the diagnostic controller 1 further includes a process self-test module 13; the process self-test module 13 is used to determine whether the fully mechanized mining process meets the process operating conditions based on the equipment self-test flag and the equipment verification flag; when it is determined that the fully mechanized mining process meets the process operating conditions, the fully mechanized mining process corresponding to the fully mechanized mining equipment is started, and the process self-test result corresponding to the fully mechanized mining process is represented by the process self-test flag of the fully mechanized mining process based on the process safety conditions and the parameters of the fully mechanized mining equipment after the fully mechanized mining process is started; the parameters of the fully mechanized mining equipment after the fully mechanized mining process is started include at least the fully mechanized mining equipment parameters, process parameters, and environmental parameters; the process safety conditions may include, but are not limited to, correct process logic, correct process parameters, correct environmental parameters, and personnel not entering the work area.

[0035] Optionally, the process self-inspection module 13 is also used to match the diagnostic prompt code and display code corresponding to the process self-inspection result according to the self-inspection diagnostic result library, and output the diagnostic prompt code and display code corresponding to the process self-inspection result to the front-end configuration system 2; the front-end configuration system 2 is used to generate process self-inspection alarm information corresponding to the fully mechanized mining process according to the diagnostic prompt code and display code corresponding to the process self-inspection result after the fully mechanized mining process is started.

[0036] Specifically, the process self-inspection and diagnosis involves using the process self-inspection module 13 to perform safety diagnoses on the fully mechanized mining process after its startup, ensuring the safety and reliability of the mining operation. The process self-inspection module 13 can have a built-in self-inspection and diagnosis result library, integrating the corresponding diagnostic prompt codes ErrorCode and display codes ErrorShow for each process self-inspection stage. It intelligently matches the process self-inspection results and outputs them to the front-end configuration system 2 via the display code ErrorShow, facilitating the user to implement appropriate countermeasures.

[0037] Among them, the process operating conditions can be that the equipment self-inspection result is normal and the equipment verification result is normal, which can be expressed as: ProofreadingFlag=0 and Self-checkFla=0.

[0038] For example, such as Figure 5The diagram shows the process self-check diagnostic flowchart. To better illustrate this function, the process self-check flag, ProcessFlag, can be defined first. Upon system startup, diagnostic controller 1 reads the parameters of the fully mechanized mining equipment, process parameters, and environmental parameters through the 10 Gigabit ring network 3 to perform a process self-check. Normal operation of the fully mechanized mining process requires that all equipment meet the operating conditions and can operate normally. ProofreadingFlag=0 and Self-checkFla=0 are necessary conditions for normal process operation. If the fully mechanized mining process is in progress, when Self-checkFla=1, the process execution terminates, and the equipment self-check diagnostic will report the corresponding diagnostic prompt code ErrorCode and display code ErrorShow. The relevant self-check process has already been described and will not be repeated here.

[0039] After the fully mechanized mining operation begins, the process self-check and diagnostic function starts working. Based on process safety conditions, it checks factors affecting the safety of the operation, excluding equipment self-checks. Specifically, it can determine whether the process logic is correct, whether the process parameters are correct, whether the environmental parameters are correct, and whether personnel have entered the work area, etc., and obtains the process self-check results. If the process self-check result is normal, it returns ProcessFlag=0, and the process operates normally. If the process self-check result is abnormal, it returns ProcessFlag=1, the process stops running, and the diagnostic prompt code ErrorCode and display code ErrorShow of the abnormal result are fed back to the front-end configuration system 2, along with the process abnormality situation and solution. After the abnormality is resolved, the system performs the process self-check again until the process self-check diagnostic result is normal, then returns ProcessFlag=0, and the process operates normally.

[0040] For example, during fully mechanized mining operations, in the self-diagnosis process, when ProcessFlag=1, ErrorCode=9000, and ErrorShow=9000, the front-end configuration system 2 displays "Planning and cutting stopped, manual intervention required for the planning curve; please confirm whether to accept manual intervention." As another example, when ProcessFlag=1, ErrorCode=9001, and ErrorShow=9001, the front-end configuration system 2 displays "Fully mechanized mining stopped, methane exceeding limit alarm; please check relevant sensors and confirm environmental parameters, and take preventative measures." And as yet another example, when ProcessFlag=1, ErrorCode=9010, and ErrorShow=9010, the front-end configuration system 2 displays "Planning and cutting stopped, someone has entered the work area at the machine head; AI electronic fence warning."

[0041] Optionally, the diagnostic controller 1 also includes a pose diagnosis module 14; the pose diagnosis module 14 is used to diagnose the mutual position between the fully mechanized mining equipment and the equipment posture of the fully mechanized mining equipment in real time after the fully mechanized mining process is started, and to determine the pose diagnosis result of the fully mechanized mining equipment based on the comparison results between the mutual position between the fully mechanized mining equipment, the equipment posture of the fully mechanized mining equipment and the preset operating rating value of the fully mechanized mining equipment.

[0042] The preset operation ratings may include the pose safety threshold configured through the front-end configuration system 2.

[0043] The front-end configuration system 2 is also used to configure the pose safety threshold of the fully mechanized mining equipment; the position diagnosis module is also used to obtain the pose parameters corresponding to the fully mechanized mining equipment through the 10 Gigabit ring network 3; based on the comparison result between the pose parameters of the fully mechanized mining equipment and the pose safety threshold, the corresponding pose diagnosis flag bit of the fully mechanized mining equipment is generated; and the pose diagnosis flag bit and the diagnosis prompt code and display code corresponding to the pose diagnosis result are output to the front-end configuration system 2.

[0044] In specific application scenarios, the positional relationships between various mining equipment and between different equipment all affect the operation. Real-time diagnosis of the relative positions of multiple devices and the posture of individual devices allows for judgment of abnormal situations, ensuring the normal operation of equipment and processes. The posture diagnosis function has a built-in diagnostic result library, integrating diagnostic prompt codes ErrorCode and display codes ErrorShow. It intelligently matches posture diagnosis results and outputs the results to the front-end configuration system 2 via the display code ErrorShow, facilitating users to implement appropriate countermeasures.

[0045] For example, such as Figure 6 The diagram shows the pose diagnosis flowchart. To better illustrate this function, a pose diagnosis flag, PoseFlag, can be defined first. Upon system startup, the diagnostic controller 1 reads the pose parameters of the fully mechanized mining equipment via the 10 Gigabit ring network 3 and begins pose diagnosis. It diagnoses in real-time whether the equipment position and relative positions between equipment exceed the rated values ​​required for operation. If the pose diagnosis result is normal, it returns PoseFlag=0, and the equipment process operates normally. If the pose diagnosis result is abnormal, it returns PoseFlag=1, the working equipment and executed process stop working, and the diagnostic prompt code ErrorCode and display code ErrorShow of the abnormal result are fed back to the front-end configuration system 2, along with the location of the equipment abnormality and a solution. After the abnormality is resolved, the system performs a self-check again until the pose diagnosis result is normal, then returns PoseFlag=0, and the equipment calibration ends.

[0046] For example, coal mining machine posture: coal mining machine pitch angle X, coal mining machine yaw angle Y, x1, x2, x3, x4, y1, y2, y3, y4 are safety thresholds configured in front-end configuration system 2.

[0047] When x1 < X ≤ x2, the coal mining machine operates normally; PoseFlag = 0.

[0048] When x2<X≤x3 or x4<X≤x1, PoseFlag=0 and ErrorCode=8020 and ErrorShow=8022. At this time, the front-end configuration system 2 displays "Adjust the mining height of the front and rear drums of the coal mining machine to ensure the levelness of the top and bottom".

[0049] When x3 < X or X ≤ x4, PoseFlag = 1, ErrorCode = 8021, ErrorShow = 8023. At this time, the front-end configuration system 2 displays "Stop operation, check project quality, and formulate rectification measures".

[0050] The self-checking method for pitch attitude angle X of the coal mining machine is used to self-check the yaw attitude angle Y.

[0051] For example, the coal machine position sensor collects the coal machine position as L1, and the support position sensor collects the position as L2. After the coal machine has been running for a period of time T1, if L1 remains unchanged, but L2 becomes L21, then the coal machine position L will be L21.

[0052] Optionally, the diagnostic controller 1 also includes a pre-inspection module 15, and the fully mechanized mining diagnostic system also includes an AI edge inference server 4; the front-end configuration system 2 is also used to configure the maintenance information corresponding to the fully mechanized mining equipment, including maintenance time, which is adjusted according to the operating pressure of the fully mechanized mining equipment; the pre-inspection module 15 is used to use the AI ​​edge inference server 4 to predict the equipment operation status of the fully mechanized mining equipment based on the maintenance time and the historical maintenance time and historical maintenance content of the fully mechanized mining equipment; and generate an equipment maintenance plan for the fully mechanized mining equipment based on the equipment operation status.

[0053] For example, after a period of operation, fully mechanized mining equipment needs to be inspected and maintained in order to maintain its stability, reliability, and operational efficiency. The pre-inspection function uses big data analysis and AI decision-making capabilities to make plans for the maintenance of the equipment and the status of the required components in advance, thereby improving the service life of the equipment, increasing operational efficiency, and reducing the impact on production.

[0054] The AI ​​edge inference server 4 can be a dedicated computing device deployed underground or near the fully mechanized mining equipment. It runs trained AI models (such as LSTM, random forest, Prophet, and other time-series prediction models) to perform real-time predictions of equipment operation. Based on the prediction results, it generates dynamic and personalized equipment maintenance plans (repair strategies). These plans may include suggested maintenance times, maintenance levels (routine maintenance, minor repairs, major repairs), and a list of spare parts to be replaced, reducing unplanned downtime and other anomalies. Correspondingly, maintenance information can include structured data related to equipment maintenance, such as maintenance time (start and end times of planned or actual maintenance), maintenance content (component replacement, lubrication, calibration, software upgrades, etc.), and can also be used as historical data for AI model training and prediction. In this way, based on the historical maintenance times and content of the fully mechanized mining equipment, as well as real-time monitoring information such as current equipment parameters and status, the health trend of the fully mechanized mining equipment over a future period can be predicted, including failure probability, remaining useful life (RUL), and performance degradation curves.

[0055] The operating pressure of fully mechanized mining equipment can be defined as the comprehensive load that the equipment bears during operation. It is usually evaluated by the following parameters: load rate (such as motor current / rated current), running time, start-stop frequency, environmental conditions (temperature, humidity, dust), etc. The greater the operating pressure of the fully mechanized mining equipment, the faster its wear and tear. Maintenance needs to be arranged in advance to shorten the maintenance time of the equipment.

[0056] Specifically, equipment information parameters such as the first maintenance time and maintenance content can be configured in the front-end configuration system 2. Based on this configuration information and parameters such as the operating time, pressure, current, and load of each device, the diagnostic controller 1, in conjunction with the maintenance strategy, periodically pushes maintenance information and provides maintenance strategies.

[0057] Assume the equipment's rated maintenance interval is Te months. The rated operating pressure is Fe (rated power Pe, rated voltage Ve, rated current Ie). When the equipment operates under rated conditions, the maintenance time is T = Te. Assuming maintenance is performed according to Te under rated conditions, and considering the previous maintenance time of t1 and the maintenance content, propose the following maintenance strategy: When the working time is 0.8Te < t ≤ 0.9Te, prepare the necessary repair parts and tools based on the provided repair tips.

[0058] When T=nTe, provide a major overhaul reference, including the availability of spare parts.

[0059] When the equipment is operating under non-rated conditions, the maintenance time is T = βTe.

[0060] When equipment is operating under overload, the maintenance time will be shortened, T = βTe, where 0 < β < 1, and the value of β is determined based on on-site usage. Based on the previous maintenance time t1 and the maintenance content, a maintenance strategy is proposed.

[0061] For example, such as Figure 7 The diagram shows the flowchart of the fully mechanized mining diagnostic system. This system may include a diagnostic controller 1, a front-end configuration system 2, a 10 Gigabit ring network 3, and an AI edge inference server 4. The diagnostic controller 1 includes functions such as equipment verification diagnostics, equipment self-test diagnostics, process self-test diagnostics, pose diagnostics, and pre-inspection. The various functional modules work together to ensure the stable, safe, and reliable execution of equipment and processes, improving equipment utilization efficiency. For example, during the diagnostic process, if PoseFlag is detected as 0, other diagnostics continue; if PoseFlag = 1, the working equipment and executing process stop working. The fully mechanized mining diagnostic system can have a built-in diagnostic result library, integrating diagnostic prompt codes ErrorCode and display codes ErrorShow. It intelligently matches equipment verification results and outputs the results to the front-end configuration system 2 via the display code ErrorShow, facilitating users to implement corresponding measures. Specifically, the equipment verification and diagnostic function is used to diagnose whether the equipment meets the working conditions before startup; the equipment self-diagnostic function is used to perform safety diagnoses on the equipment's working process after startup to ensure safe and reliable operation; the process self-diagnostic function is used to perform safety diagnoses on the fully mechanized mining process to ensure safe and reliable operation; the position and posture diagnostic function is used to diagnose the relative positions of multiple devices and the posture of individual devices in real time, make judgments on abnormal situations, and ensure the normal operation of equipment and processes; and the pre-inspection function is used to plan for the maintenance and upkeep of equipment and the status of required components in advance, thereby improving equipment lifespan, increasing operational efficiency, and reducing the impact on production.

[0062] In this way, the fully mechanized mining diagnostic system provided in this embodiment is an intelligent safety management system that integrates self-calibration, self-inspection, and self-diagnosis functions of fully mechanized mining equipment and processes. It utilizes the equipment verification module 11 to diagnose whether the equipment meets the working conditions before startup; the equipment self-inspection module 12 to perform safety diagnosis of the equipment's working process after startup, ensuring safe and reliable operation; the process self-inspection module 13 to perform safety diagnosis of the fully mechanized mining process, ensuring safe and reliable operation; and the posture diagnosis module 14 to diagnose the relative positions of multiple devices and the posture of individual devices in real time, making judgments on any abnormal situations. The system ensures the normal operation of equipment and processes. The pre-inspection module 15 proactively plans for equipment requiring maintenance and identifies necessary components, extending equipment lifespan, improving operational efficiency, and reducing the impact on production. All related modules work collaboratively to ensure stable, safe, and reliable execution of equipment and processes, improving equipment utilization efficiency, achieving the goal of reducing manpower, increasing efficiency, and ensuring safety. It also addresses issues such as missing equipment and process self-inspection, self-correction, system self-maintenance, and position control in the fully mechanized mining process, enabling safety monitoring of the entire fully mechanized mining operation, enhancing the intelligence level of fully mechanized mining operations, improving production efficiency, and ensuring production safety.

[0063] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of a preferred embodiment, and the modules or processes shown in the drawings are not necessarily essential for implementing this application. Those skilled in the art will understand that the modules in the apparatus of the embodiment can be distributed within the apparatus of the embodiment as described, or can be modified to be located in one or more apparatuses different from this embodiment. The modules of the above-described embodiment can be combined into one module, or further divided into multiple sub-modules.

[0064] The serial numbers in this application are for descriptive purposes only and do not represent the superiority or inferiority of any particular implementation scenario. The above disclosures are merely a few specific implementation scenarios of this application; however, this application is not limited thereto, and any variations conceived by those skilled in the art should fall within the protection scope of this application.

Claims

1. A fully mechanized diagnosis system, characterized in that, The application relates to a system for diagnosing a fully-mechanized coal mining device. The system comprises a diagnostic controller, a front-end configuration system and a gigabit ring network. The diagnostic controller is used for acquiring fully-mechanized coal mining device parameters of the fully-mechanized coal mining device in different diagnostic stages through the gigabit ring network, diagnosing the fully-mechanized coal mining device and a fully-mechanized coal mining process of the fully-mechanized coal mining device according to the fully-mechanized coal mining device parameters, acquiring diagnostic results of the fully-mechanized coal mining device in the different diagnostic stages, and feeding back the diagnostic results to the front-end configuration system. The front-end configuration system is used for receiving the diagnostic results sent by the diagnostic controller in the different diagnostic stages, generating alarm information of the fully-mechanized coal mining device according to the diagnostic results, and performing process parameter configuration, control instruction issuing, device process state information display and diagnostic result reporting of the fully-mechanized coal mining process, and storing diagnostic parameters, control instructions and alarm information corresponding to the fully-mechanized coal mining device during the diagnostic process of the diagnostic controller. The gigabit ring network is used for providing a communication link and a data channel with the fully-mechanized coal mining device, acquiring the fully-mechanized coal mining device parameters of the fully-mechanized coal mining device in the different diagnostic stages based on the communication link and the data channel, and sending the fully-mechanized coal mining device parameters in the different diagnostic stages to the diagnostic controller.

2. The fully mechanized diagnosis system according to claim 1, characterized in that, The diagnostic controller comprises a device verification module. The device verification module is used for verifying whether the fully-mechanized coal mining device parameters of the fully-mechanized coal mining device meet device starting conditions of the fully-mechanized coal mining device before the fully-mechanized coal mining device starts, acquiring a device verification result of the fully-mechanized coal mining device, and feeding back the device verification result to the front-end configuration system. The device starting conditions at least include emergency stop closure, normal communication, normal frequency converter, no overcurrent, overvoltage and overtemperature of the motor, normal pressure sensor and normal position sensor.

3. The fully mechanized diagnosis system according to claim 2, characterized in that, The device verification module comprises a verification diagnostic result database. The verification diagnostic result database is used for integrating diagnostic prompt codes and display codes, and matching the diagnostic prompt codes and the display codes corresponding to the device verification result. The device verification module is used for determining a device verification flag of the fully-mechanized coal mining device according to the fully-mechanized coal mining device parameters before the fully-mechanized coal mining device starts, determining the device verification result of the fully-mechanized coal mining device according to the device verification flag, and outputting the diagnostic prompt codes and the display codes corresponding to the device verification result to the front-end configuration system, wherein the device verification flag is used for marking whether the device starting state of the fully-mechanized coal mining device is normal. The front-end configuration system is used for generating device verification alarm information corresponding to the fully-mechanized coal mining device according to the diagnostic prompt codes and the display codes corresponding to the device verification result before the fully-mechanized coal mining device starts, wherein the alarm information comprises an abnormal position and an abnormal solution corresponding to the fully-mechanized coal mining device.

4. The fully mechanized diagnosis system according to claim 3, characterized in that, The diagnostic controller further comprises a device self-checking module. The device self-checking module is used for acquiring fully-mechanized coal mining device parameters of the fully-mechanized coal mining device after the fully-mechanized coal mining device starts through the gigabit ring network after detecting the fully-mechanized coal mining device by using the device verification module, determining that the fully-mechanized coal mining device meets the device starting conditions, and starting the fully-mechanized coal mining device, performing safety diagnosis on a device operation process of the fully-mechanized coal mining device according to the fully-mechanized coal mining device parameters after the fully-mechanized coal mining device starts, and acquiring a device self-checking result of the fully-mechanized coal mining device.

5. The fully mechanized diagnosis system according to claim 4, characterized in that, The device self-checking module comprises a self-checking diagnosis result library; The self-checking diagnosis result library is used for matching the diagnosis prompt code and the display code corresponding to the device self-checking result; The device checking module is used for determining the device self-checking flag of the fully-mechanized mining device according to the parameters of the started fully-mechanized mining device during the operation of the fully-mechanized mining device; The device self-checking result of the fully-mechanized mining device is determined according to the device self-checking flag, and the diagnosis prompt code and the display code corresponding to the device self-checking result are output to the front-end configuration system, wherein the device self-checking flag is used for marking whether the device operation state of the fully-mechanized mining device is normal; The front-end configuration system is used for generating the device self-checking alarm information corresponding to the fully-mechanized mining device according to the diagnosis prompt code and the display code corresponding to the device self-checking result during the operation of the fully-mechanized mining device.

6. The fully mechanized diagnosis system according to claim 5, characterized in that, The diagnosis controller further comprises a process self-checking module; The process self-checking module is used for judging whether the fully-mechanized mining process meets the process operation condition according to the device self-checking flag and the device checking flag; When it is determined that the fully-mechanized mining process meets the process operation condition, the fully-mechanized mining process corresponding to the fully-mechanized mining device is started, the process self-checking result corresponding to the fully-mechanized mining process is represented by using the process self-checking flag of the fully-mechanized mining process according to the process safety condition and the parameters of the fully-mechanized mining device after the fully-mechanized mining process is started; The parameters of the fully-mechanized mining device after the fully-mechanized mining process is started at least comprise the fully-mechanized mining device parameters, the process parameters and the environment parameters; The process safety condition at least comprises the process logic being correct, the process parameters being correct, the environment parameters being correct and personnel not intruding into the operation area.

7. The fully mechanized diagnosis system according to claim 6, characterized in that, The process self-checking module is further used for matching the diagnosis prompt code and the display code corresponding to the process self-checking result according to the device self-checking result library, and outputting the diagnosis prompt code and the display code corresponding to the process self-checking result to the front-end configuration system; The front-end configuration system is used for generating the process self-checking alarm information corresponding to the fully-mechanized mining process according to the diagnosis prompt code and the display code corresponding to the process self-checking result after the fully-mechanized mining process is started.

8. The fully mechanized diagnosis system according to claim 7, characterized in that, The diagnosis controller further comprises a position and posture diagnosis module; The position and posture diagnosis module is used for diagnosing the mutual positions between the fully-mechanized mining devices and the device postures of the fully-mechanized mining devices in real time after the fully-mechanized mining process is started, and determining the position and posture diagnosis result of the fully-mechanized mining devices according to the comparison result of the mutual positions between the fully-mechanized mining devices, the device postures of the fully-mechanized mining devices and the preset operation rated values of the fully-mechanized mining devices.

9. The fully mechanized diagnosis system according to claim 8, characterized in that, The front-end configuration system is further used for configuring the position and posture safety threshold of the fully-mechanized mining device; The position diagnosis module is further used for acquiring the position and posture parameters corresponding to the fully-mechanized mining device through the gigabit ring network, generating the position and posture diagnosis flag corresponding to the fully-mechanized mining device according to the comparison result of the position and posture parameters of the fully-mechanized mining device and the position and posture safety threshold, and outputting the diagnosis prompt code and the display code corresponding to the position and posture diagnosis flag and the position and posture diagnosis result to the front-end configuration system.

10. The fully mechanized diagnosis system according to claim 1, characterized in that, The diagnosis controller further comprises a pre-checking module, and the fully-mechanized mining diagnosis system further comprises an AI edge inference server; The front-end configuration system is also used for configuring maintenance information corresponding to the fully mechanized mining equipment, and the maintenance information includes a maintenance time, and the maintenance time is adjusted according to working pressure of the fully mechanized mining equipment. The pre-checking module is used for predicting, by using the AI edge inference server, equipment operation of the fully mechanized mining equipment according to the maintenance time and historical maintenance time and historical maintenance content of the fully mechanized mining equipment, and generating an equipment maintenance plan of the fully mechanized mining equipment according to the equipment operation.

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