Fully mechanized coal mining face intelligent control system based on Internet of Things

Abstract

The invention belongs to the technical field of coal mining intellectualization, and discloses a fully mechanized coal mining face intellectualization control system based on the Internet of Things, which comprises a service architecture module, a multi-level hardware interaction module, an intelligent control module, a data visualization and alarm module and a flexible deployment module. According to the invention, a horizontally extensible servitization architecture is adopted, multiple internet of things protocols and large-scale equipment access are supported, intelligent management and control of equipment are realized through multi-level hardware interaction, comprehensive intelligent management and control of a fully mechanized coal mining face are realized by combining data visualization and flexible deployment capabilities, the production efficiency and safety are improved, and the system is suitable for popularization and application. And the labor cost is reduced.

Description

Technical Field

[0001] This invention relates to the field of intelligent coal mining technology, specifically to an intelligent control system for fully mechanized mining faces based on the Internet of Things. Background Technology

[0002] The fully mechanized longwall face is the core area of ​​coal mine production, and its production efficiency and safety directly affect the overall production benefits of the coal mine. Traditional control methods for fully mechanized longwall faces mainly rely on manual operation and simple automated control, which suffers from problems such as poor equipment coordination, serious data silos, low control accuracy, and slow response speed.

[0003] With the development of technologies such as the Internet of Things, big data, and artificial intelligence, intelligent coal mining has become an inevitable trend in the industry. However, existing intelligent control systems for fully mechanized mining faces generally suffer from the following shortcomings: closed system architecture, poor scalability, and difficulty in adapting to fully mechanized mining faces of different scales and types; poor protocol compatibility, making it impossible to achieve unified access and management of equipment from different manufacturers and of different types; rigid control logic, making it difficult to flexibly adjust according to actual production needs; limited data processing capabilities, unable to achieve real-time processing and analysis of large-scale equipment data; and a single deployment method, unable to adapt to the network environment and hardware conditions of different coal mines. Therefore, developing an intelligent control system for fully mechanized mining faces with high scalability, strong compatibility, flexible control, efficient data processing, and diversified deployment capabilities is of great significance. Summary of the Invention

[0004] Therefore, the purpose of this invention is to provide an intelligent control system for fully mechanized mining faces based on the Internet of Things (IoT). This system adopts a service-oriented architecture, supports multiple IoT protocols, and realizes intelligent management and control of fully mechanized mining face equipment. It features high scalability, strong compatibility, and flexible deployment.

[0005] To achieve the aforementioned objectives, the technical solution adopted is as follows: The IoT-based intelligent control system for longwall mining faces includes a service-oriented architecture module, a multi-level hardware interaction module, an intelligent control module, a data visualization and alarm module, and a flexible deployment module.

[0006] The service-oriented architecture module is built using horizontally scalable open-source technology, supports clustered deployment, ensures that each node in the cluster has consistent functionality and no single point of failure, a single server node can handle tens of thousands of device connections, and the cluster can handle millions of device connections. It also has persistent data storage capabilities and customizable function expansion capabilities, and new functions can be added through customizable components and rule engine nodes.

[0007] The multi-level hardware interaction module comprises a communication layer, a kernel layer, and a rule engine layer. The communication layer supports multiple IoT protocols, including MQTT, HTTP, CoAP, LwM2M, Modbus, OPC-UA, and SNMP. The MQTT transmission component provides a gateway API to enable multi-device connections and sensor data acquisition. After receiving device messages, the communication layer parses and pushes them to a persistent message queue, only sending feedback to the device after the message queue confirms receipt. The kernel layer handles REST API calls and WebSocket subscriptions, stores active device session information, and monitors device connection status. It uses an Actor model to manage tenants and device entities, supports multi-node cluster deployment, and each node is responsible for processing incoming messages in a specific partition. The rule engine layer is the core data processing unit of the system. It uses an Actor model to manage rule chains and rule node entities, supports cluster deployment and message partitioning, subscribes to data from the message queue, and confirms messages after processing. It provides two operating modes: shared mode and isolated mode.

[0008] The intelligent control module includes an electro-hydraulic control submodule, a fluid supply submodule, a belt conveyor and three-machine submodule, a coal mining machine submodule, an underground control console submodule, and an operating console module. The electro-hydraulic control submodule defines equipment protocol parsing rules and RPC control command formats through a JSON configuration file, supporting independent control of a single support and group control of multiple supports. Single support control includes actions such as column pressure adjustment and push stroke control. Group control supports selection of the up-and-down channel and configuration of the number of supports. Control commands are parsed via a rule chain and then sent to the equipment via the Modbus protocol. The fluid supply submodule configures the server attributes and telemetry attributes of the emulsifying pump and spray pump, supporting two start-stop control modes: mode one assigns an independent start-stop address to each pump, and mode two allows all pumps to share a single start-stop address and distinguish different pumps using bits. Simultaneously, it uses a rule chain to parse pump operating status and construct control commands. In the belt conveyor and three-machine submodule, the belt conveyor submodule is configured with line-side interlocking, The monitoring attributes such as belt misalignment and smoke detection are analyzed using rule chains to determine the belt start / stop status and achieve centralized control of multiple belts. The three-machine sub-module assigns attributes to sub-equipment such as crushers and transfer conveyors through equipment profiles, supporting independent status monitoring and joint start / stop control of sub-equipment. The coal mining machine sub-module collects operating parameters such as traction motor temperature and cutting current through the Modbus protocol, supports both hold-type and non-hold-type button control, and implements cutting rate calculation and one-key start / stop logic through rule chains. The underground control console sub-module collects the operating console mode of each device through the Modbus protocol, sends control commands to associated devices, and receives device status feedback to determine the feasibility of one-key start / stop. The operating console module supports three control modes: centralized control, local control, and maintenance control. One-key start / stop is only allowed when both the operating console and the equipment are in centralized control mode. Control command sending permissions are controlled through the server attribute "rpckaiguan", and control permissions are automatically locked when no command is issued.

[0009] The data visualization and alarm module provides a WebUI interface, builds stateless static components based on the Express.js framework, obtains system data through REST API and WebSocket API, supports real-time data display, historical data playback, geolocation and map display, and provides custom dashboard and report generation functions; the alarm module triggers alarms based on a rule engine, supports multiple types of alarms such as communication failure, infrared failure, and stress over-limit, and sends notifications through multiple channels such as email, SMS and Webhook.

[0010] The flexible deployment module supports local deployment, cloud deployment, and edge deployment. It supports containerized deployment, can run in a dedicated network without internet access, and supports automatic discovery of new server nodes and load balancing.

[0011] Furthermore, the rule engine layer of the service-oriented architecture module includes a protocol parsing node and an RPC protocol parsing node. The protocol parsing node defines field parsing rules through JSON configuration, supporting the parsing of the fields dongzuoxinxi1, dongzuoxinxi2, zhuangtai, gongzuomianinfo1, and gongzuomianinfo2. The configuration includes the index range, data length, whether to convert, parsing method, and alarm triggering conditions. When "tongxinzhuangtai" is parsed as true, a communication failure alarm is triggered. The RPC protocol parsing node defines the RPC instruction format through JSON configuration, supporting the parsing of the setgenjimingling and setcaimeijifangxiang instructions. The configuration includes the instruction tag, data type, function code, address, and data length. It uses little-endian mode to store multi-byte data, with the least significant byte stored at the lowest address and the most significant byte stored at the highest address.

[0012] Furthermore, the JSON configuration file of the electro-hydraulic control submodule includes general configuration, working face protocol configuration, support telemetry information configuration, and support RPC control configuration; the general configuration defines general rules for data parsing; the working face protocol configuration defines function codes and addresses for fields such as startendno and shebeimoshi; the support telemetry information configuration defines fields such as lizhuyali and tuiyixingcheng, using the naming rule of "field name + device number"; the support RPC control configuration defines instructions such as setdongzuokongzhi, using 64uint type to write 4 address data at once.

[0013] Furthermore, the liquid supply submodule includes server-side attributes and telemetry attributes. The server-side attributes include emulsion pump control attributes (ruhuabeng), spray pump control attributes (penwubeng), and start-up mode attributes (qidongfangshi). The telemetry attributes include at least the overall operating status of the spray pump (gyPwbAllRun), the overall operating status of the emulsion pump (gyRhbAllRun), the individual parameters of the spray pump (gyPwb), and the individual parameters of the emulsion pump (gyRhb). The pump group start-up and shutdown control logic of the liquid supply submodule is as follows: When the value of the start-up method attribute (qidongfangshi) is 0, each pump corresponds to an independent start-up and stop control address. The start-up and stop control of a single pump is achieved by writing a boolean value "true" or "false" to the corresponding address. When the value of the start-up method attribute (qidongfangshi) is 1, all pumps share the same start-stop control address. The bit control logic is defined by JSON format control parameters. The JSON control parameters include at least an "index" field, a "value" field, and an "allbitlength" field. The "index" field is used to define the bit position of the pump to be controlled, the "value" field is used to define the control value of the bit (0 or 1), and the "allbitlength" field is used to define the total bit length corresponding to the address. For example, when the JSON control parameters are {"index":[0], "value":1, "allbitlength":16}, it indicates that pump number 1 corresponding to bit 0 is started.

[0014] Furthermore, the cutting rate calculation rule chain of the coal mining machine submodule includes an initialization node, a timing node, and a calculation node. The initialization node sets qidongshike, tingzhishike, sycjsshike, jiyishichang, and yjqdshichang when the coal mining machine starts. The timing node triggers a calculation every 30 seconds, and if the current state is a memorized coal cutting state, it accumulates jiyishichang. The calculation node calculates the real-time cutting rate using the formula "cutting rate = jiyishichang / yjqdshichang × 100%", and also supports setting a fixed cutting rate through the server-side attribute gudingjiegelv.

[0015] Furthermore, the one-click start / stop process of the operating console submodule includes condition judgment, command issuance, status feedback, and progress update steps; the condition judgment step checks whether the operating console and all participating devices are in centralized control mode and whether "rpckaiguan" is enabled; the command issuance step issues start / stop commands in a preset order; the status feedback step receives the start / stop results of each device and tracks the status through the newmsg.iskztqiting, newmsg.sbqtwancheng, and newmsg.replayed attributes; the progress update step displays the start / stop progress and failure prompts in real time on the WebUI.

[0016] Furthermore, the system also includes a power supply module, which configures loop information through a rule chain, defines the correspondence between devices and loops, including huiluName, huiluGongdianDeviceName, and img, and configures shijiandaima parsing rules to map loop event codes into readable fault information, and displays the power supply status and fault type of each loop through a WebUI.

[0017] Compared with the prior art, the present invention has the following beneficial effects: It adopts a service-oriented architecture, supports clustered deployment and horizontal scaling, can handle large-scale device access, and meets the needs of fully mechanized mining faces of different sizes; It supports multiple IoT protocols, enabling unified access and management of devices from different manufacturers and of different types, and solving protocol compatibility issues; The system employs a rules engine to implement flexible control logic, which can be customized according to actual production needs, thus improving the system's adaptability. Intelligent control of the main equipment in the fully mechanized mining face has been realized, including electro-hydraulic control, hydraulic supply, belt conveyor and three machines, coal mining machine, etc., which improves production efficiency and control accuracy. It provides rich data visualization functions and multi-channel alarm mechanisms, making it easy for operators to grasp the system status in real time and handle abnormal situations in a timely manner; It supports multiple deployment methods, adapting to different network environments and hardware conditions in coal mines, thus improving the system's deployment flexibility.

[0018] This invention achieves comprehensive intelligent management and control of fully mechanized mining faces through Internet of Things (IoT) technology, providing coal mining enterprises with an efficient, safe, and reliable production solution with broad application prospects. Detailed Implementation

[0019] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The present invention will now be described in detail with reference to the embodiments.

[0020] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application are clearly and completely described below. Obviously, the described embodiments are merely some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present application.

[0021] The IoT-based intelligent control system for longwall mining faces includes a service-oriented architecture module, a multi-level hardware interaction module, an intelligent control module, a data visualization and alarm module, and a flexible deployment module.

[0022] The service-oriented architecture module is built using horizontally scalable open-source technology, supports clustered deployment, ensures that each node in the cluster has consistent functionality and no single point of failure, a single server node can handle tens of thousands of device connections, and the cluster can handle millions of device connections. It also has persistent data storage capabilities and customizable function expansion capabilities, and new functions can be added through customizable components and rule engine nodes.

[0023] The multi-level hardware interaction module comprises a communication layer, a kernel layer, and a rule engine layer. The communication layer supports multiple IoT protocols, including MQTT, HTTP, CoAP, LwM2M, Modbus, OPC-UA, and SNMP. The MQTT transmission component provides a gateway API to enable multi-device connections and sensor data acquisition. After receiving device messages, the communication layer parses and pushes them to a persistent message queue, only sending feedback to the device after the message queue confirms receipt. The kernel layer handles REST API calls and WebSocket subscriptions, stores active device session information, and monitors device connection status. It uses an Actor model to manage tenants and device entities, supports multi-node cluster deployment, and each node is responsible for processing incoming messages in a specific partition. The rule engine layer is the core data processing unit of the system. It uses an Actor model to manage rule chains and rule node entities, supports cluster deployment and message partitioning, subscribes to data from the message queue, and confirms messages after processing. It provides two operating modes: shared mode and isolated mode.

[0024] The intelligent control module includes an electro-hydraulic control submodule, a fluid supply submodule, a belt conveyor and three-machine submodule, a coal mining machine submodule, an underground control console submodule, and an operating console module. The electro-hydraulic control submodule defines equipment protocol parsing rules and RPC control command formats through a JSON configuration file, supporting independent control of a single support and group control of multiple supports. Single support control includes actions such as column pressure adjustment and push stroke control. Group control supports selection of the up-and-down channel and configuration of the number of supports. Control commands are parsed via a rule chain and then sent to the equipment via the Modbus protocol. The fluid supply submodule configures the server attributes and telemetry attributes of the emulsifying pump and spray pump, supporting two start-stop control modes: mode one assigns an independent start-stop address to each pump, and mode two allows all pumps to share a single start-stop address and distinguish different pumps using bits. Simultaneously, it uses a rule chain to parse pump operating status and construct control commands. In the belt conveyor and three-machine submodule, the belt conveyor submodule is configured with line-side interlocking, The monitoring attributes such as belt misalignment and smoke detection are analyzed using rule chains to determine the belt start / stop status and achieve centralized control of multiple belts. The three-machine sub-module assigns attributes to sub-equipment such as crushers and transfer conveyors through equipment profiles, supporting independent status monitoring and joint start / stop control of sub-equipment. The coal mining machine sub-module collects operating parameters such as traction motor temperature and cutting current through the Modbus protocol, supports both hold-type and non-hold-type button control, and implements cutting rate calculation and one-key start / stop logic through rule chains. The underground control console sub-module collects the operating console mode of each device through the Modbus protocol, sends control commands to associated devices, and receives device status feedback to determine the feasibility of one-key start / stop. The operating console module supports three control modes: centralized control, local control, and maintenance control. One-key start / stop is only allowed when both the operating console and the equipment are in centralized control mode. Control command sending permissions are controlled through the server attribute "rpckaiguan", and control permissions are automatically locked when no command is issued.

[0025] The data visualization and alarm module provides a WebUI interface, builds stateless static components based on the Express.js framework, obtains system data through REST API and WebSocket API, supports real-time data display, historical data playback, geolocation and map display, and provides custom dashboard and report generation functions; the alarm module triggers alarms based on a rule engine, supports multiple types of alarms such as communication failure, infrared failure, and stress over-limit, and sends notifications through multiple channels such as email, SMS and Webhook.

[0026] The flexible deployment module supports local deployment, cloud deployment, and edge deployment. It supports containerized deployment, can run in a dedicated network without internet access, and supports automatic discovery of new server nodes and load balancing.

[0027] The rule engine layer of the service-oriented architecture module includes a protocol parsing node and an RPC protocol parsing node. The protocol parsing node defines field parsing rules through JSON configuration, supporting the parsing of the fields dongzuoxinxi1, dongzuoxinxi2, zhuangtai, gongzuomianinfo1, and gongzuomianinfo2. The configuration includes the index range, data length, whether to convert, parsing method, and alarm triggering conditions. When "tongxinzhuangtai" is parsed as true, a communication failure alarm is triggered. The RPC protocol parsing node defines the RPC instruction format through JSON configuration, supporting the parsing of the setgenjimingling and setcaimeijifangxiang instructions. The configuration includes the instruction tag, data type, function code, address, and data length. It uses little-endian mode to store multi-byte data, with the least significant byte stored at the lowest address and the most significant byte stored at the highest address.

[0028] The JSON configuration file of the electro-hydraulic control submodule includes general configuration, working face protocol configuration, support telemetry information configuration, and support RPC control configuration. The general configuration defines general rules for data parsing. The working face protocol configuration defines the function codes and addresses of fields such as startendno and shebeimoshi. The support telemetry information configuration defines fields such as lizhuyali and tuiyixingcheng, using the naming rule of "field name + device number". The support RPC control configuration defines instructions such as setdongzuokongzhi, which uses 64uint type to write 4 address data at a time.

[0029] Furthermore, the liquid supply submodule includes server-side attributes and telemetry attributes. The server-side attributes include emulsion pump control attributes (ruhuabeng), spray pump control attributes (penwubeng), and start-up mode attributes (qidongfangshi). The telemetry attributes include at least the overall operating status of the spray pump (gyPwbAllRun), the overall operating status of the emulsion pump (gyRhbAllRun), the individual parameters of the spray pump (gyPwb), and the individual parameters of the emulsion pump (gyRhb). The pump group start-up and shutdown control logic of the liquid supply submodule is as follows: When the value of the start-up method attribute (qidongfangshi) is 0, each pump corresponds to an independent start-up and stop control address. The start-up and stop control of a single pump is achieved by writing a boolean value "true" or "false" to the corresponding address. When the value of the start-up method attribute (qidongfangshi) is 1, all pumps share the same start-stop control address. The bit control logic is defined by JSON format control parameters. The JSON control parameters include at least an "index" field, a "value" field, and an "allbitlength" field. The "index" field is used to define the bit position of the pump to be controlled, the "value" field is used to define the control value of the bit (0 or 1), and the "allbitlength" field is used to define the total bit length corresponding to the address. For example, when the JSON control parameters are {"index":[0], "value":1, "allbitlength":16}, it indicates that pump number 1 corresponding to bit 0 is started.

[0030] The cutting rate calculation rule chain of the coal mining machine submodule includes an initialization node, a timing node, and a calculation node. The initialization node sets qidongshike, tingzhishike, sycjsshike, jiyishichang, and yjqdshichang when the coal mining machine starts. The timing node triggers a calculation every 30 seconds, and if the current state is a memorized coal cutting state, it accumulates jiyishichang. The calculation node calculates the real-time cutting rate using the formula "cutting rate = jiyishichang / yjqdshichang × 100%", and also supports setting a fixed cutting rate through the server-side attribute gudingjiegelv.

[0031] The one-click start / stop process of the control panel submodule includes condition judgment, command issuance, status feedback, and progress update steps. The condition judgment step checks whether the control panel and all participating devices are in centralized control mode and whether "rpckaiguan" is enabled. The command issuance step issues start / stop commands in a preset order. The status feedback step receives the start / stop results of each device and tracks the status through the newmsg.iskztqiting, newmsg.sbqtwancheng, and newmsg.replayed attributes. The progress update step displays the start / stop progress and failure prompts in real time on the WebUI.

[0032] The system also includes a power supply module, which configures loop information through a rule chain, defines the correspondence between devices and loops, including huiluName, huiluGongdianDeviceName, and img. At the same time, it configures shijiandaima parsing rules to map loop event codes into readable fault information and displays the power supply status and fault type of each loop through a WebUI.

[0033] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, component splitting or combination, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An intelligent control system for a fully-mechanized coal mining face based on the Internet of Things, characterized in that: It includes a service-oriented architecture module, a multi-level hardware interaction module, an intelligent control module, a data visualization and alarm module, and a flexible deployment module; The service architecture module is built using horizontally scalable open-source technology, supports clustered deployment, and ensures that each node in the cluster has consistent functionality and no single point of failure. A single server node can handle tens of thousands of device connections, and the cluster can handle millions of device connections. It also has persistent data storage capabilities and customizable function expansion capabilities, and new functions can be added through customizable components and rule engine nodes. The multi-level hardware interaction module includes a communication layer, a kernel layer, and a rule engine layer. The communication layer supports multiple IoT protocols such as MQTT, HTTP, CoAP, LwM2M, Modbus, OPC-UA, and SNMP. The MQTT transmission component provides a gateway API to enable multi-device connection and sensor data acquisition. After receiving device messages, the communication layer parses them and pushes them to a persistent message queue. It only sends the message transmission result back to the device after the message queue confirms receipt. The kernel layer is responsible for handling REST API calls and WebSocket subscriptions, storing active device session information, and monitoring device connection status. It uses an Actor model to manage tenants and device entities, supports multi-node cluster deployment, and each node is responsible for processing incoming messages for a specific partition. The rules engine layer is the core data processing unit of the system. It adopts the Actor model to implement the management of rule chains and rule node entities, supports cluster deployment and message partitioning processing, subscribes to data from the message queue and confirms the message after processing, and provides two operating modes: shared mode and isolated mode. The intelligent control module includes an electro-hydraulic control submodule, a fluid supply submodule, a belt conveyor and three-machine submodule, a coal mining machine submodule, an underground control console submodule, and an operating console module. The electro-hydraulic control submodule defines equipment protocol parsing rules and RPC control command formats through a JSON configuration file, supporting independent control of a single support and group control of multiple supports. Single support control includes actions such as column pressure adjustment and push stroke control. Group control supports selection of the up-and-down channel and configuration of the number of supports. Control commands are parsed via a rule chain and then sent to the equipment via the Modbus protocol. The fluid supply submodule configures the server attributes and telemetry attributes of the emulsifying pump and spray pump, supporting two start-stop control modes: mode one assigns an independent start-stop address to each pump, and mode two allows all pumps to share a single start-stop address and distinguish different pumps using bits. Simultaneously, it uses a rule chain to parse pump operating status and construct control commands. In the belt conveyor and three-machine submodule, the belt conveyor submodule is configured with line-side interlocking, The monitoring attributes such as belt misalignment and smoke detection are analyzed using rule chains to determine the belt start / stop status and achieve centralized control of multiple belts. The three-machine sub-module assigns attributes to sub-equipment such as crushers and transfer conveyors through equipment profiles, supporting independent status monitoring and joint start / stop control of sub-equipment. The coal mining machine sub-module collects operating parameters such as traction motor temperature and cutting current through the Modbus protocol, supports both hold-type and non-hold-type button control, and implements cutting rate calculation and one-key start / stop logic through rule chains. The underground control console sub-module collects the operating console mode of each device through the Modbus protocol, sends control commands to associated devices, and receives device status feedback to determine the feasibility of one-key start / stop. The operating console module supports three control modes: centralized control, local control, and maintenance control. One-key start / stop is only allowed when both the operating console and the equipment are in centralized control mode. Control command sending permissions are controlled through the server attribute "rpckaiguan", and control permissions are automatically locked when no command is issued. The data visualization and alarm module provides a WebUI interface, builds stateless static components based on the Express.js framework, obtains system data through REST API and WebSocket API, supports real-time data display, historical data playback, geolocation and map display, and provides custom dashboard and report generation functions; the alarm module triggers alarms based on a rule engine, supports multiple types of alarms such as communication failure, infrared failure, and stress overload, and sends notifications through multiple channels such as email, SMS and Webhook. The flexible deployment module supports local deployment, cloud deployment, and edge deployment. It supports containerized deployment, can run in a dedicated network without internet access, and supports automatic discovery of new server nodes and load balancing.

2. The Internet of Things based intelligent control system of a fully mechanized coal mining face according to claim 1, characterized in that, The rule engine layer of the service-oriented architecture module includes a protocol parsing node and an RPC protocol parsing node. The protocol parsing node defines field parsing rules through JSON configuration, supporting the parsing of the fields dongzuoxinxi1, dongzuoxinxi2, zhuangtai, gongzuomianinfo1, and gongzuomianinfo2. The configuration includes the index range, data length, whether to convert, parsing method, and alarm triggering conditions. When "tongxinzhuangtai" is parsed as true, a communication failure alarm is triggered. The RPC protocol parsing node defines the RPC instruction format through JSON configuration, supporting the parsing of the setgenjimingling and setcaimeijifangxiang instructions. The configuration includes the instruction tag, data type, function code, address, and data length. It uses little-endian mode to store multi-byte data, with the least significant byte stored at the lowest address and the most significant byte stored at the highest address.

3. The intelligent control system for fully mechanized mining faces based on the Internet of Things as described in claim 1, characterized in that, The JSON configuration file of the electro-hydraulic control submodule includes general configuration, working face protocol configuration, support telemetry information configuration, and support RPC control configuration. The general configuration defines general rules for data parsing. The working face protocol configuration defines the function codes and addresses of fields such as startendno and shebeimoshi. The support telemetry information configuration defines fields such as lizhuyali and tuiyixingcheng, using the naming rule of "field name + device number". The support RPC control configuration defines instructions such as setdongzuokongzhi, which uses 64uint type to write 4 address data at a time.

4. The intelligent control system for fully mechanized mining faces based on the Internet of Things as described in claim 1, characterized in that, The liquid supply submodule includes server-side attributes and telemetry attributes. The server-side attributes include emulsion pump control attributes, spray pump control attributes, and start-up mode attributes. The telemetry attributes include at least the overall operating status of the spray pump, the overall operating status of the emulsion pump, individual parameters of the spray pump, and individual parameters of the emulsion pump. The pump group start-up and shutdown control logic of the liquid supply submodule is as follows: When the value of the start-up mode attribute is 0, each pump corresponds to an independent start-stop control address. The start-stop control of a single pump is achieved by writing a boolean value "true" or "false" to the corresponding address. When the start-up mode attribute is set to 1, all pumps share the same start-stop control address. The bit control logic is defined by JSON format control parameters, which at least include an "index" field, a "value" field, and an "allbitlength" field. The "index" field is used to define the bit position of the pump to be controlled, the "value" field is used to define the control value of the bit, and the "allbitlength" field is used to define the total bit length corresponding to the address.

5. The intelligent control system for fully mechanized mining faces based on the Internet of Things as described in claim 1, characterized in that, The cutting rate calculation rule chain of the coal mining machine submodule includes an initialization node, a timing node, and a calculation node; the initialization node sets qidongshike, tingzhishike, sycjsshike, jiyishichang, and yjqdshichang when the coal mining machine starts; the timing node triggers a calculation every 30 seconds, and if the current state is a memorized coal cutting state, it accumulates jiyishichang. The compute node calculates the real-time cutoff rate using the formula "cutoff rate = jiyishichang / yjqdshichang × 100%", and also supports setting a fixed cutoff rate through the server-side attribute gudingjiegelv.

6. The intelligent control system for fully mechanized mining faces based on the Internet of Things as described in claim 1, characterized in that, The one-click start / stop process of the control panel submodule includes condition judgment, command issuance, status feedback, and progress update steps. The condition judgment step checks whether the control panel and all participating devices are in centralized control mode and whether "rpckaiguan" is enabled. The command issuance step issues start / stop commands in a preset order. The status feedback step receives the start / stop results of each device and tracks the status through the newmsg.iskztqiting, newmsg.sbqtwancheng, and newmsg.replayed attributes. The progress update step displays the start / stop progress and failure prompts in real time on the WebUI.

7. The intelligent control system for fully mechanized mining faces based on the Internet of Things as described in claim 1, characterized in that, It also includes a power supply module, which configures loop information through a rule chain, defines the correspondence between devices and loops, including huiluName, huiluGongdianDeviceName, and img, and configures shijiandaima parsing rules to map loop event codes into readable fault information, and displays the power supply status and fault type of each loop through a WebUI.