Introduce

The occurrence of rockburst will result in casualties, production shutdowns, and rectification, greatly affecting the safety of mining operations. In order to predict and prevent the hazards of rockburst, various rockburst monitoring systems (microseismic monitoring system, stress monitoring system, drilling cuttings monitoring system, hydraulic support monitoring system, etc.) have been built in the mining area. Each monitoring system has played a certain role in predicting and preventing safety hazards in mining production, but none has been able to predict and prevent all safety hazards. The mine needs a comprehensive multi parameter warning platform system for rockburst that can comprehensively analyze safety hazards, to guide the safe and smooth progress of production. This system integrates data from conventional monitoring systems such as microseismic, stress, drill cuttings, and hydraulic supports for monitoring the hazards of ground pressure impact. By jointly analyzing multiple monitoring data, reasonable predictions and warnings can be made on the hazardous situation in the monitoring area to ensure the safety of production.

Technical Proposal

01. Automatic monitoring data collection function

Multi data collection

The data collector collects subsystem monitoring data and uploads it to the comprehensive warning platform through TCP protocol to complete automatic data collection.

02. Subsystem data standardization function

Standardized overall configuration interface

Warning Platform Server Settings Interface

Data collection parameter setting interface

Configure warning platform server parameters, subsystem monitoring data categories, monitoring data location offset, monitoring data time offset, and database related information. Through location offset and time offset, multiple monitoring data with different coordinate spaces and time zones can be unified into the same coordinate space and time zone.

03. Comprehensive display function of monitoring data

Main window interface

Monitoring data is displayed in three-dimensional scenes in different shapes and colors, categorized by type and degree of harm. By combining the tunnel model in the 3D scene, it is possible to more intuitively control the hazardous area and degree, which is beneficial for taking protective measures more quickly.

04. Regional monitoring and warning function

Regional hazard indication interface

Develop different monitoring indicators based on the geological and mining conditions of different regions, and provide real-time monitoring and early warning for each area.

05. 3D scene display and operation functions

3D scene point selection

This platform integrates a 3D engine (OSG library) to load DXF mine models, Surpac mine models, and various monitoring data, providing a more vivid and three-dimensional display. The 3D scene provides functions such as rotation, translation, scaling, changing the rotation center point, top-down projection, side view projection, front view projection, and point selection. Double click and select to view detailed information on monitoring data (location, energy, hazard level, etc.), which allows for a comprehensive view of the monitoring data and the safety status of the surrounding area.

06. Regional hazard cloud map display function

Cloud map of microseismic energy hazards

Display the hazard status of the area in the form of cloud maps, providing a more intuitive reflection of high-risk areas.

07. Automatic reporting function

Report production interface

The function of automatic report generation and one click export facilitates the backup and management of production safety status data in mining areas. The function of automatic report generation and one click export facilitates the backup and management of production safety status data in mining areas.

08. Real time warning function

WeChat warning information

This platform has functions such as software interface warning prompts, sound and light warnings, and WeChat warnings. WeChat alerts push warning information to authorized users by type and level.

09. Intelligent warning function based on machine learning

Intelligent analysis of hazard index

On the basis of self built algorithm models, this platform has obtained a convolutional neural network system through training with a large amount of monitoring data. This neural network system is capable of real-time hazard warning and analysis of regional security conditions. The neural network system also has self-learning capabilities, continuously adjusting the weight parameters within the system through self-learning of monitoring data and hazard conditions, in order to achieve reliable hazard warning.

Product advantages

This platform has conducted comprehensive analysis and early warning of subsystem monitoring data, assisting users in timely and effective safety protection work, reducing the occurrence of hazardous accidents, mitigating the impact of hazardous accidents, and ensuring the smooth progress of user safety production.

Case Presentation

• Yulon Group Tangyang Coal Mine Impact Ground Pressure Multi parameter Comprehensive Early Warning Platform
• Yulon Group Yineng Coal Mine Impact Ground Pressure Multi parameter Comprehensive Early Warning Platform
• Shaanxi Jinyuan Zhaoxian Coal Mine Impact Ground Pressure Multi parameter Comprehensive Early Warning Platform