Detection of out-of-seam and out-of-scope mining using double filtering method

Area of Science:

• Geosciences
• Mining Engineering
• Geoinformatics

Background:

• Small-scale coal mines in China face safety risks due to out-of-seam and out-of-scope mining, especially near depletion.
• Existing detection methods are often slow and lack precision, contributing to frequent accidents.

Purpose of the Study:

• To develop an accurate and efficient method for identifying unauthorized mining activities in coal mines.
• To overcome the limitations of current time-consuming and inaccurate detection techniques.

Main Methods:

• Integration of Kalman and particle dual filtering techniques with handheld positioning and data acquisition devices.
• Utilizing a strapdown inertial navigation unit with Kalman filtering and zero-speed correction for real-time navigation.
• Employing particle filtering for dynamic error correction using Bluetooth beacon zones and Simultaneous Localization and Mapping (SLAM) for data analysis.

Main Results:

• The system provides real-time navigation and precise trajectory data of mine inspectors.
• SLAM algorithms effectively analyze inspector data against official mine maps.
• Experimental trials validated the precise and efficient identification of out-of-seam and out-of-scope mining.

Conclusions:

• The proposed dual filtering approach offers a significant advancement in detecting illegal mining operations.
• This technology enhances mine safety by enabling accurate and timely identification of hazardous mining practices.
• The system's real-time capabilities and validated accuracy make it a valuable tool for mine inspection and regulation.