Application of New Void Detection Algorithm for Analysis of Feed Pressure and Rotation Pressure of Roof Bolters

"Roof and rib instability is an important issue in underground mining. To optimize ground support design, enhance ground stability, and reduce the possibility of roof or rib failure with minimal use of artificial ground support, it is essential to have an accurate understanding of ground conditions. This includes the location of voids, cracks, and discontinuities, as well as information about the different strata in the immediate roof. This paper briefly introduces ongoing research on void detection by using the roof bolter feed and rotation pressure. The goal of this project is to improve the sensitivity of detection programs to locate smaller joints and reduce the number of false alarms. This paper has presented a brief review of the testing procedures, data analysis, logic, and algorithms used for void detection. In addition, this paper has discussed the results of preliminary laboratory tests and statistical analysis of the data from these two drilling parameters used for void detection.INTRODUCTIONRoof falls are one of the most serious and frequent accidents in underground mining. Each year, personnel are injured or killed because of roof falls. Equipment can also be damaged when this occurs. According to Mine Safety and Health Administration statistics collected from 1999 to 2008, ground falls were the largest cause of fatal accidents in underground coal mining, causing around 40% of all fatalities (NIOSH, 2015a). Out of 8 to 10 fatalities and over 800 injuries are recorded each year in underground mines, there are nearly 2,000 reportable non-injury ground falls every year (NIOSH, 2015b).Certain features in the ground, such as voids, cracks, and discontinuities, are significant factors that cause roof support failures and roof fall accidents. Currently, several manufacturers provide smart roof bolters with limited capabilities for void detection. While successful in many instances, in laboratory experiments, the existing void detection systems have limited success in detecting void openings that are less than 1/8 inch This limited success was observed in testing concrete blocks with gaps in between, simulating a rock medium with voids. Detection programs have missed some voids, while, in some cases, they have shown false detection. These algorithms need to be more accurate in sensing voids to improve the capabilities of these programs."