Intelligent optimization method for tunnel rotary drilling based on drill string status estimation

Authors

YAO Ningping, China Coal Research Institute, Beijing 100013, China; CCTEG Xi’an Research Institute (Group) Co., Ltd., Xi’an 710077, ChinaFollow
WEI Hongchao, China Coal Research Institute, Beijing 100013, China; CCTEG Xi’an Research Institute (Group) Co., Ltd., Xi’an 710077, ChinaFollow
ZHANG Jinbao, CCTEG Xi’an Research Institute (Group) Co., Ltd., Xi’an 710077, China
LU Chengda, School of Automation, China University of Geosciences, Wuhan 430074, China
LI Hao, China Coal Research Institute, Beijing 100013, China; CCTEG Xi’an Research Institute (Group) Co., Ltd., Xi’an 710077, China
YAO Yafeng, China Coal Research Institute, Beijing 100013, China; CCTEG Xi’an Research Institute (Group) Co., Ltd., Xi’an 710077, China
KE Yougang, School of Automation, China University of Geosciences, Wuhan 430074, China
ZHANG Youzhen, China Coal Research Institute, Beijing 100013, China; CCTEG Xi’an Research Institute (Group) Co., Ltd., Xi’an 710077, China

Abstract

To address the issue in existing research where it is difficult to obtain bottom-hole drilling parameters while drilling, and to overcome the problem of low accuracy and insufficient improvement when optimizing rotary drilling operational parameters using only borehole data, an intelligent optimization method for near-horizontal tunnel rotary drilling based on drill string status is proposed. This involves constructing an in-hole state observer to estimate bottom-hole drilling parameter information. Firstly, the characteristics of rotary drilling in underground coal mine tunnels are analyzed, considering the constraints of actual drilling, and an optimization target evaluation method for mechanical drilling speed and drill bit wear is proposed. Subsequently, a concentrated mass drill string dynamics model in axial and torsional dimensions is established, and a drill string state space equation based on this model is constructed, yielding a mapping relationship between the borehole and bottom-hole drill string motion states. Based on this, a state observer is designed, using Lyapunov stability analysis method to obtain the feedback gain matrix L, to estimate the motion state of the bottom-hole drill bit, and conduct simulation analysis and evaluation. Finally, by combining data collected from the borehole and estimated bottom-hole state, the optimization of the power head speed and feed pressure was achieved using the NSGA-II multi-objective optimization algorithm, and verified with actual drilling data from a coal mine in Huainan, Anhui. The results show that the drilling speed and driller operation improved by 32.47% after optimization based on drill string state estimation of bottom-hole information, compared to an estimated 15.04% improvement using only borehole measured data. Thus, the intelligent optimization method for tunnel rotary drilling based on drill string state estimation has more advantages, and the estimated bottom-hole drilling information plays a key role in improving the level of drilling. This research has significant theoretical and practical significance for achieving efficient and intelligent drilling in coal mine tunnel rotary drilling.

Keywords

rotary drilling, status estimation, dynamical model, multi-objective optimization, coal mine

DOI

10.12363/issn.1001-1986.23.06.0329

Recommended Citation

YAO Ningping, WEI Hongchao, ZHANG Jinbao, et al. (2023) "Intelligent optimization method for tunnel rotary drilling based on drill string status estimation," Coal Geology & Exploration: Vol. 51: Iss. 11, Article 16.
DOI: 10.12363/issn.1001-1986.23.06.0329
Available at: https://cge.researchcommons.org/journal/vol51/iss11/16

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