Mining Contract: LiDAR Technology Adaptation to Underground Coal Mines for Float Coal Dust and Rock Dust Mapping Applications

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Contract # 200-2013-56947
Start Date 9/16/2013
End Date 2/16/2015
Research Concept

The explosion hazard in coal mines related to float coal dust can be mitigated by distributing the proper concentration of rock dust given the amount of float coal dust being liberated by the mining process. The proposed sensing technology aims to estimate dispersion distances of float coal dust and assess rock dust coverage over large areas. Eventually, it could be used as an input to automated rock dusting equipment to optimize rock dust application.

Topic Areas

Contract Status & Impact

This contract is complete. To receive a copy of the final report, send a request to mining@cdc.gov.

Currently, a real-time measurement technique for float coal dust does not exist. The implementation of automated and new functionalities in both hardware and software would make existing measurement technology better suited to mapping and visualizing the dispersion of float coal dust in real time. In addition, a technique used to assess adequacies of rock dust along the ribs could obviously help to identify areas where more rock dust is required. The research performed by Electricore, Inc., under this contract utilized Light Detection and Ranging (LiDAR) technology as a means to achieve these two capabilities.

LiDAR sensing technology is an optical instrument capable of measuring the distance to a target by measuring the light duration round-trip between the instrument and the target using the reflectance and scattering properties of the target material. Because of its sensitivity, LiDAR allows for the mapping of dust dispersion within both longwall and continuous coal mine entries. Prior to this contract, a prototype unit using LiDAR technology was successfully demonstrated for measuring dust concentrations in simulated conditions of underground coal mine operations.

The focus for this new work was to achieve a real-time display of the float coal dust dispersion, automating or assisting the deployment of the prototype, and calibrating the prototype for different types of dust (e.g., float coal dust, rock dust). Hardware adaptations were completed which allowed for the measurement of concentrations of dust across a distance and the concentration grid to be fused with a picture. Software modifications were implemented which allowed illumination profile correction, precise distance calibration, reflectance calculation based upon image and distance, 3-D mapping, and the display in real time of deposited concentration map on contextual image. These adaptations have brought the instrument a step closer to a commercial system for use in underground mines, in that the LiDAR system has more capabilities and is more user-friendly. This system can now be easily utilized for research studies, but requires some further simplifications for everyday use in underground mines.

The LiDAR system demonstrated some potential benefits for mapping dust. It provided a 3-D map of the relative dust concentrations over a large area. Another potential advantage to the LiDAR system is that some preliminary data suggested that it may be able to determine the ratio of rock dust and coal dust in the air. This could be beneficial in automating a rock duster to ensure that the correct amount of rock dust is being provided. Further data is needed to verify this finding. Currently, a limitation to the LiDAR system is that a complicated calibration scheme is needed to determine the actual dust concentrations. The calibration factor depends upon dust type, particle size distribution, and other physical effects.

The LiDAR system’s capability for determining rock dust on the surface of coal mines was not as promising. Under dry conditions, the LiDAR system could determine if the surface was above an 80/20 mixture of a particular rock dust and coal dust. However, the system’s capability was strongly affected by humidity and would therefore be difficult to calibrate.


Page last reviewed: July 19, 2016
Page last updated: July 19, 2016