IIOT-remote mobile cooperative monitoring and intelligent management and control system for fully mechanized coal mining face of coal mine

Abstract

The invention belongs to the technical field of mine intelligent mining and industrial Internet of Things crossing, particularly relates to an IIOT-remote mobile cooperative monitoring and intelligent management and control system for a fully mechanized coal mining face of a coal mine, and solves the problems of poor mobility, data fragmentation, slow emergency response and difficulty in cross-platform adaptation of a traditional monitoring system for the fully mechanized coal mining face of the coal mine. A'cloud-end 'framework is adopted, an equipment layer, a network layer, a cloud data layer and a mobile application layer are integrated, the equipment layer collects operation data of fully mechanized mining equipment, the cloud data layer realizes data convergence, storage and rule engine operation based on an industrial Internet of Things platform, and the mobile application layer develops a cross-platform terminal based on a Flutter framework. A multi-equipment monitoring module, a data analysis module, a fault alarm module and the like are integrated, alarm millisecond-level pushing is achieved through long connection communication and a rule engine, and real-time mobile monitoring, unified data research and judgment, rapid fault response and cross-platform intelligent management and control of fully mechanized coal mining face equipment are achieved.

Description

Technical Field

[0001] This invention belongs to the technical field of intelligent mining and industrial Internet of Things, specifically involving an IIoT-remote mobile collaborative monitoring and intelligent control system for fully mechanized coal mining faces. Background Technology

[0002] Against the backdrop of accelerated smart mine construction, the intelligent management and control level of fully mechanized coal mining faces, as the core scenario of mine production, directly determines mining efficiency and operational safety. Currently, the coal mining industry generally relies on fixed centralized control centers for monitoring equipment in underground fully mechanized mining faces. Traditional monitoring systems have the following significant limitations when adapting to the development needs of smart mines and the Industrial Internet of Things: 1. Insufficient mobility and delayed information transmission: Traditional systems rely on fixed terminals (such as computers in the central control room). When staff leave the fixed location, they cannot obtain real-time operating data and fault information of underground equipment. Moreover, due to the limitation of the "fixed operation - hierarchical reporting - process approval" model, the emergency response process is lengthy (usually with a response delay of more than 5 minutes), making it difficult to meet the needs of the production front line for "real-time monitoring and rapid decision-making." In extreme cases, information delays may lead to safety accidents. 2. Data fragmentation and low analysis efficiency: Monitoring data from different equipment (such as coal mining machines, pump stations, and three-machine systems) are often scattered across independent platforms (such as coal mining machine monitoring systems and pump station management systems), lacking a unified mobile terminal display and analysis interface. Staff need to frequently switch platforms to complete comprehensive data analysis, increasing the average analysis time by 20-30 minutes, seriously affecting decision-making efficiency. 3. Poor adaptability to weak networks and low functional consistency: Network signals are weak in some areas underground (such as the working face end and roadway). Traditional mobile terminals are mostly developed based on a single platform (such as native Android applications), which are prone to data disconnection and interface lag under weak network conditions. Moreover, deployment across devices (such as Android and iOS phones) requires repeated development, making it difficult to ensure functional consistency and increasing development and maintenance costs.

[0003] To address the aforementioned issues of limited space, fragmented data, and delayed response, there is an urgent need for an intelligent system that can combine industrial IoT technology with cross-platform mobile terminals to achieve real-time monitoring, unified analysis, rapid alarm, and mobile control of equipment in fully mechanized mining faces. Summary of the Invention

[0004] Therefore, the purpose of this invention is to provide an IIoT-based remote mobile collaborative monitoring and intelligent control system for fully mechanized coal mining faces, which features strong mobility, data integration capabilities, rapid emergency response, and cross-platform adaptability. This system aims to overcome the shortcomings of traditional fully mechanized coal mining face monitoring systems, such as poor mobility, data fragmentation, slow emergency response, and difficulty in cross-platform adaptability.

[0005] To achieve the aforementioned objectives, the technical solution adopted is as follows: An IIoT-based remote mobile collaborative monitoring and intelligent control system for fully mechanized coal mining faces adopts a "cloud-edge" architecture, comprising a device layer, a network layer, a cloud data layer, and a mobile application layer connected in sequence. The system achieves unified deployment of mobile terminals through Flutter cross-platform technology, enables real-time data interaction from devices through deep protocol integration with an industrial IoT platform, configures specific alarm rules for coal mine equipment through a rule engine, and achieves millisecond-level reception and push of alarm information through long-connection communication. Wherein: Equipment layer: Includes sensor and controller devices, used to collect operating data of coal mine fully mechanized mining face equipment and execute control commands; among them, sensor devices include various sensor devices deployed on the fully mechanized mining face, such as: coal mining machine speed sensor, pump station pressure sensor, three-machine temperature sensor and support displacement sensor, etc.; controller devices include hydraulic support controller, etc.

[0006] Cloud Data Layer: Relying on the IoT platform, it realizes the aggregation, storage, and rule engine operation of device data; Data Aggregation and Storage: It receives real-time data uploaded by the device layer through multi-protocol interfaces (MQTT, HTTPS), uses a time-series database to store historical data, and supports 6-month data backtracking query; Rule Engine Operation: It configures special alarm rules for coal mine equipment (such as "pump station emulsion level ≤ 20% triggers level 1 alarm" and "coal mining machine cutting current ≥ 300A triggers level 2 alarm"), and realizes data filtering, preprocessing, and alarm triggering through a two-level architecture of "root rule chain - sub-rule chain"; Data Forwarding: It pushes the processed real-time data and alarm information to the mobile application layer through WebSocket.

[0007] Network Layer: Used to enable bidirectional communication between the device layer, cloud data layer, and mobile application layer; Communication Method: Employs a converged "wired + wireless" communication approach. The underground working face connects sensors and gateways via industrial Ethernet (such as a gigabit ring network), while the ground enables bidirectional communication between the cloud and mobile terminals via 4G / 5G or WiFi; Protocol Support: Compatible with MQTT (for real-time transmission of device telemetry data), HTTPS (for transmission of configuration data and control commands), and WebSocket (for long-term push of alarm information), ensuring data transmission stability in different scenarios.

[0008] Mobile Application Layer: A cross-platform mobile terminal developed based on the Flutter framework, integrating online monitoring modules for coal mining machines, pump stations, three machines (coal mining machine, pump station, and pump station), equipment data analysis, fault alarm, equipment management, and gateway edge computing. It enables data visualization, data analysis, equipment status display, fault location alarms, and alarm push notifications. The coal mining machine online monitoring module displays real-time parameters such as traction speed, cutting current, and drum height, supporting dynamic curve graphs (time granularity 1s / point) to show parameter change trends. The pump station online monitoring module displays data such as emulsion level, oil pressure, and oil temperature, comparing the operation of different pump stations (1#-3#) through bar charts. Status; Three-machine online monitoring module: monitors the speed, bearing temperature, and chain tension of scraper conveyor, transfer conveyor, and crusher, and marks abnormalities with a red warning; Equipment data analysis module: automatically calculates equipment operating efficiency (such as the effective operating rate of coal mining machine) and fault frequency, and generates daily / weekly reports; Fault alarm module: receives alarm information pushed from the cloud and displays the equipment ID, alarm type, and trigger time; Equipment management module: manages equipment ledgers and supports remote issuance of start / stop and parameter adjustment commands; Gateway edge computing module: deployed on the underground gateway, performs local preprocessing of sensor data (such as filtering noise data and removing outliers), reduces cloud data transmission volume by more than 40%, and improves system response speed.

[0009] As a further improvement of the present invention, the mobile application layer uses Dart language combined with Flutter responsive UI components to build an interactive interface, supporting real-time data visualization functions, including dynamic curve charts, bar charts and status monitoring tables.

[0010] As a further improvement of the present invention, the mobile application layer utilizes Flutter's asynchronous programming model (Future / Stream) to achieve asynchronous communication with the backend service, ensuring stable reception of data streams and timely interface refresh in weak network environments.

[0011] As a further improvement of the present invention, the mobile application layer supports multi-protocol data access: it obtains device telemetry data through MQTT and HTTPS protocol interfaces, and configures an entity permission system. By parsing the role identifier in the JWT token, it dynamically loads the functional modules with corresponding permissions on the mobile terminal.

[0012] As a further improvement of the present invention, alarm push is implemented in the following way: when the rule engine (RuleChain) triggers an alarm rule, the IoT platform pushes it to the mobile terminal via WebSocket; the mobile terminal establishes a long connection through the web_socket_channel plugin, and triggers a native notification in conjunction with the Flutter LocalNotification plugin, with a delay of ≤200ms from alarm generation to terminal notification.

[0013] As a further improvement of the present invention, the rule engine of the cloud data layer executes a five-stage alarm processing flow: (1) Data enters the platform’s default “root rule chain” via the protocol. The root rule chain filters data by message type and routes data that meets the alarm association conditions to the corresponding sub-rule chain. (2) The sub-rule chain preprocesses the data, including verifying the integrity of the format, filtering redundant information, and converting nested format data into standard format through field mapping; (3) The rule chain uses "judgment node" or custom script execution conditions to identify whether the data meets the abnormality criteria; (4) If the abnormal criteria are met, the rule chain triggers an alarm operation: when the alarm is triggered for the first time, a new alarm is created containing the device ID, alarm type and trigger time. When the abnormality continues, the alarm status is updated. When the data is restored to normal, the alarm is marked as "cleared" and the recovery time is recorded. (5) The platform will persistently store alarm information in the database and send notifications via email, SMS or third-party system push.

[0014] As a further improvement of the present invention, the interactive interface of the mobile terminal supports real-time display of equipment status and fault location alarm functions, and can display the operating parameters and working status of equipment such as coal mining machines, pumping stations, three machines and supports.

[0015] As a further improvement of the present invention, the gateway edge computing module is used to assist in the local preprocessing and edge computing of device data, thereby improving data transmission efficiency and system response speed.

[0016] The beneficial effects of this invention are: 1. Full-scene mobile control: Free from the limitations of fixed terminals, staff can monitor underground equipment in real time through their mobile phones, covering the entire scenario of "central control room - working face - inspection route", and realizing "all personnel, all time" management; 2. Improved data integration efficiency: Unified integration of data from multiple devices such as coal mining machines, pump stations, and three machines allows for comprehensive analysis without switching platforms, improving decision-making efficiency by more than 50%. 3. Strong adaptability to weak networks: Based on Flutter asynchronous communication and edge computing, it can still run stably in the weak network environment underground, solving the "disconnection and lag" problems of traditional mobile terminals; 4. Significantly faster emergency response speed: Alarm delay ≤200ms, combined with the closed-loop process of "alarm-location-command issuance", the emergency response time is shortened from the traditional 5 minutes to within 1 minute, reducing the risk of safety accidents; 5. Reduced development and maintenance costs: Flutter's cross-platform technology reduces repetitive development work by more than 60%, and multi-protocol access and access control improve system compatibility and security, reducing long-term maintenance costs. Attached Figure Description

[0017] The accompanying drawings, which form part of this application, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings: Figure 1 This is an architecture diagram of the system described in this invention; Figure 2 This is an interaction timing diagram of the system described in this invention; Figure 3 This is a flowchart of the fault alarm process of the present invention; Figure 4 This invention provides an interface diagram of a mobile terminal. Detailed Implementation

[0018] 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 accompanying drawings and embodiments.

[0019] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0020] like Figure 1-4As shown, an IIoT-based remote mobile collaborative monitoring and intelligent control system for fully mechanized coal mining faces adopts a "cloud-edge" architecture, including a device layer, a network layer, a cloud data layer, and a mobile application layer connected in sequence. The system achieves unified deployment of mobile terminals through Flutter cross-platform technology, enables real-time data interaction from devices through deep protocol integration with an industrial IoT platform, configures specific alarm rules for coal mine equipment through a rule engine, and achieves millisecond-level reception and push of alarm information through long-connection communication; wherein: Equipment layer: Includes sensor and controller devices, used to collect operating data of coal mine fully mechanized mining face equipment and execute control commands; among them, sensor devices include various sensor devices deployed on the fully mechanized mining face, such as: coal mining machine speed sensor, pump station pressure sensor, three-machine temperature sensor and support displacement sensor, etc.; controller devices include hydraulic support controller, etc.

[0021] Cloud Data Layer: Relying on the IoT platform, it realizes the aggregation, storage, and rule engine operation of device data; Data Aggregation and Storage: It receives real-time data uploaded by the device layer through multi-protocol interfaces (MQTT, HTTPS), uses a time-series database to store historical data, and supports backtracking and querying of data from the past 6 months to the past year; Rule Engine Operation: It configures special alarm rules for coal mine equipment (such as "pump station emulsion level ≤ 20% triggers a first-level alarm" and "coal mining machine cutting current ≥ 300A triggers a second-level alarm"), and realizes data filtering, preprocessing, and alarm triggering through a two-level architecture of "root rule chain - sub-rule chain"; Data Forwarding: It pushes the processed real-time data and alarm information to the mobile application layer via WebSocket.

[0022] Network Layer: Used to enable bidirectional communication between the device layer, cloud data layer, and mobile application layer; Communication Method: Employs a converged "wired + wireless" communication approach. The underground working face connects sensors and gateways via industrial Ethernet (such as a gigabit ring network), while the ground enables bidirectional communication between the cloud and mobile terminals via 4G / 5G or WiFi; Protocol Support: Compatible with MQTT (for real-time transmission of device telemetry data), HTTPS (for transmission of configuration data and control commands), and WebSocket (for long-term push of alarm information), ensuring data transmission stability in different scenarios.

[0023] Mobile Application Layer: A cross-platform mobile terminal developed based on the Flutter framework, integrating online monitoring modules for coal mining machines, pump stations, three machines (coal mining machine, pump station, and pump station), equipment data analysis, fault alarm, equipment management, and gateway edge computing. It enables data visualization, data analysis, equipment status display, fault location alarms, and alarm push notifications. The coal mining machine online monitoring module displays real-time parameters such as traction speed, cutting current, and drum height, supporting dynamic curve graphs (time granularity 1s / point) to show parameter change trends. The pump station online monitoring module displays data such as emulsion level, oil pressure, and oil temperature, comparing the operation of different pump stations (1#-3#) through bar charts. Status; Three-machine online monitoring module: monitors the speed, bearing temperature, and chain tension of scraper conveyor, transfer conveyor, and crusher, and marks abnormalities with a red warning; Equipment data analysis module: automatically calculates equipment operating efficiency (such as the effective operating rate of coal mining machine) and fault frequency, and generates daily / weekly reports; Fault alarm module: receives alarm information pushed from the cloud and displays the equipment ID, alarm type, and trigger time; Equipment management module: manages equipment ledgers and supports remote issuance of start / stop and parameter adjustment commands; Gateway edge computing module: deployed on the underground gateway, performs local preprocessing of sensor data (such as filtering noise data and removing outliers), reduces cloud data transmission volume by more than 40%, and improves system response speed.

[0024] The mobile application layer uses the Dart language combined with Flutter's responsive UI components to build the interactive interface, and supports real-time data visualization functions, including dynamic line charts, bar charts and status monitoring tables.

[0025] The mobile application layer utilizes Flutter's asynchronous programming model (Future / Stream) to achieve asynchronous communication with the backend service, ensuring stable reception of data streams and timely interface refresh in weak network environments.

[0026] The mobile application layer supports multi-protocol data access: it obtains device telemetry data through MQTT and HTTPS protocol interfaces, and configures an entity permission system. By parsing the role identifier in the JWT token, it dynamically loads the corresponding permission function modules on the mobile terminal.

[0027] Alarm push is implemented in the following way: When the rule engine (RuleChain) triggers an alarm rule, the IoT platform pushes it to the mobile terminal via WebSocket; the mobile terminal establishes a long connection through the web_socket_channel plugin, and triggers a native notification in combination with Flutter's LocalNotification plugin. The delay from alarm generation to terminal notification is ≤200ms.

[0028] The rule engine of the cloud data layer executes a five-stage alarm processing procedure: (1) Data enters the platform’s default “root rule chain” via the protocol. The root rule chain filters data by message type and routes data that meets the alarm association conditions to the corresponding sub-rule chain. (2) The sub-rule chain preprocesses the data, including verifying the integrity of the format, filtering redundant information, and converting nested format data into standard format through field mapping; (3) The rule chain uses "judgment node" or custom script execution conditions to identify whether the data meets the abnormality criteria; (4) If the abnormal criteria are met, the rule chain triggers an alarm operation: when the alarm is triggered for the first time, a new alarm is created containing the device ID, alarm type and trigger time. When the abnormality continues, the alarm status is updated. When the data is restored to normal, the alarm is marked as "cleared" and the recovery time is recorded. (5) The platform will persistently store alarm information in the database and send notifications via email, SMS or third-party system push.

[0029] The mobile terminal's interactive interface supports real-time display of equipment status and fault location alarm functions, and can display the operating parameters and working status of equipment such as coal mining machines, pump stations, three machines and supports.

[0030] The gateway edge computing module is used to assist in the local preprocessing and edge computing of device data, thereby improving data transmission efficiency and system response speed.

[0031] 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 IIoT-based remote mobile collaborative monitoring and intelligent control system for fully mechanized coal mining faces, characterized in that: The system adopts a "cloud-on-device" architecture, comprising a device layer, a network layer, a cloud data layer, and a mobile application layer connected sequentially. It achieves unified deployment on mobile terminals through Flutter cross-platform technology, enables real-time data interaction with the industrial IoT platform through deep protocol integration, configures specific alarm rules for coal mine equipment through a rule engine, and achieves millisecond-level reception and push of alarm information through long-connection communication. Specifically: Equipment layer: Includes sensor and controller devices, used to collect operating data of coal mine fully mechanized mining face equipment and execute control commands; Cloud data layer: Relying on the Internet of Things platform to realize the aggregation, storage and rule engine operation of device data; Network layer: Used to enable bidirectional communication between the device layer, cloud data layer, and mobile application layer; Mobile Application Layer: A cross-platform mobile terminal developed based on the Flutter framework, integrating online monitoring modules for coal mining machines, pump stations, three machines, and equipment, as well as equipment data analysis, fault alarm, equipment management, and gateway edge computing modules, to achieve data visualization, data analysis, equipment status display, fault location alarm, and alarm push functions.

2. The IIoT-remote mobile collaborative monitoring and intelligent control system for fully mechanized coal mining faces according to claim 1, characterized in that: The mobile application layer uses the Dart language combined with Flutter's responsive UI components to build the interactive interface, and supports real-time data visualization functions, including dynamic line charts, bar charts and status monitoring tables.

3. The IIoT-remote mobile collaborative monitoring and intelligent control system for fully mechanized coal mining faces according to claim 1, characterized in that: The mobile application layer utilizes Flutter's asynchronous programming model to achieve asynchronous communication with backend services, ensuring stable reception of data streams and timely interface refresh in weak network environments.

4. The IIoT-remote mobile collaborative monitoring and intelligent control system for fully mechanized coal mining faces according to claim 1, characterized in that: The mobile application layer supports multi-protocol data access: it obtains device telemetry data through MQTT and HTTPS protocol interfaces, and configures an entity permission system. By parsing the role identifier in the JWT token, it dynamically loads the corresponding permission function modules on the mobile terminal.

5. The IIoT-remote mobile collaborative monitoring and intelligent control system for fully mechanized coal mining faces according to claim 1, characterized in that: Alarm push is implemented in the following way: When the rule engine triggers an alarm rule, the IoT platform pushes it to the mobile terminal via WebSocket; the mobile terminal establishes a long connection through the web_socket_channel plugin, and triggers a native notification in combination with Flutter's LocalNotification plugin. The delay from alarm generation to terminal notification is ≤200ms.

6. The IIoT-remote mobile collaborative monitoring and intelligent control system for fully mechanized coal mining faces according to claim 1, characterized in that: The rule engine of the cloud data layer executes a five-stage alarm processing procedure: (1) Data enters the platform’s default “root rule chain” via the protocol. The root rule chain filters data by message type and routes data that meets the alarm association conditions to the corresponding sub-rule chain. (2) The sub-rule chain preprocesses the data, including verifying the integrity of the format, filtering redundant information, and converting nested format data into standard format through field mapping; (3) The rule chain uses "judgment node" or custom script execution conditions to identify whether the data meets the abnormality criteria; (4) If the abnormal criteria are met, the rule chain triggers an alarm operation: when the alarm is triggered for the first time, a new alarm is created containing the device ID, alarm type and trigger time. When the abnormality continues, the alarm status is updated. When the data is restored to normal, the alarm is marked as "cleared" and the recovery time is recorded. (5) The platform will persistently store alarm information in the database and send notifications via email, SMS or third-party system push.

7. The IIoT-remote mobile collaborative monitoring and intelligent control system for fully mechanized coal mining faces according to claim 1, characterized in that: The mobile terminal's interactive interface supports real-time display of equipment status and fault location alarm functions, and can display the operating parameters and working status of equipment such as coal mining machines, pump stations, three machines and supports.

8. The IIoT-remote mobile collaborative monitoring and intelligent control system for fully mechanized coal mining faces according to claim 1, characterized in that: The gateway edge computing module is used to assist in the local preprocessing and edge computing of device data, thereby improving data transmission efficiency and system response speed.

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