Research on Adaptive Drilling Control Technology Based on Coal Rock Traits During the Drilling Process

The anti-punch drilling robot is a core piece of equipment used to realize unmanned drilling and pressure relief operations in underground coal mines. Adaptive drilling, conducted according to the coal rock properties encountered during drilling, is essential to improve the safety and efficiency of the pressure relief working face. This paper analyzed the composition of the anti-punch drilling robot drilling system and workflow of the drilling system and then calculated the optimal rotary speed and the optimal feed speed for different Platts hardness coefficients of the coal rock through the analysis of the drilling rod force. Based on the characteristics of the drilling electrohydraulic control system, a rotary adaptive controller based on a self-resistant control algorithm and a feed adaptive controller based on sliding mode variable structure control were designed. A joint simulation was carried out using AMESim 2020.1 and Simulink 2020b software to analyze the control performance of each controller. Finally, an experimental platform for the drilling robot electrohydraulic control system was constructed; different hardness coefficients of concrete specimens were used to simulate the hardness of the coal rock with different traits. Single coal rock hardness experiments and drilling experiments with sudden changes in coal rock hardness were carried out. The experimental results showed that the adaptive control strategy proposed in this paper satisfies the requirements of drilling system control.

Authors

Institutions

Publication Details

Journal
Machines
Published
2025-02-10
DOI
https://doi.org/10.3390/machines13020133
Citations
1
Primary Topic
Drilling and Well Engineering
Type
article
Field-Weighted Citation Impact
1.15

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on Adaptive Drilling Control Technology Based on Coal Rock Traits During the Drilling Process

Guangpeng Shan, Guang Li, Bin Liang
1 citations
Machines
Drilling and Well Engineering
1.15
article

Research on Adaptive Drilling Control Technology Based on Coal Rock Traits During the Drilling Process

Guangpeng Shan, Guang Li, Bin Liang
article en
1 citations

Abstract

The anti-punch drilling robot is a core piece of equipment used to realize unmanned drilling and pressure relief operations in underground coal mines. Adaptive drilling, conducted according to the coal rock properties encountered during drilling, is essential to improve the safety and efficiency of the pressure relief working face. This paper analyzed the composition of the anti-punch drilling robot drilling system and workflow of the drilling system and then calculated the optimal rotary speed and the optimal feed speed for different Platts hardness coefficients of the coal rock through the analysis of the drilling rod force. Based on the characteristics of the drilling electrohydraulic control system, a rotary adaptive controller based on a self-resistant control algorithm and a feed adaptive controller based on sliding mode variable structure control were designed. A joint simulation was carried out using AMESim 2020.1 and Simulink 2020b software to analyze the control performance of each controller. Finally, an experimental platform for the drilling robot electrohydraulic control system was constructed; different hardness coefficients of concrete specimens were used to simulate the hardness of the coal rock with different traits. Single coal rock hardness experiments and drilling experiments with sudden changes in coal rock hardness were carried out. The experimental results showed that the adaptive control strategy proposed in this paper satisfies the requirements of drilling system control.

MachinesVol. 13(2)
China University of Mining and Technology (CN), Changsha Mining and Metallurgy Research Institute (China) (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Openalex Percentile: Top 27%
Drilling and Well Engineering
1.15
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.