Research on Laser Target TBM Guidance System Modeling and Intelligent Posture Prediction Algorithms

Xuying Chai; Liying Deng; Yunzhe Gu; Shutao Yu; Haoqiang Zhang

doi:10.6919/ICJE.202502_11(2).0011

Authors

Xuying Chai
Liying Deng
Yunzhe Gu
Shutao Yu
Haoqiang Zhang

DOI:

https://doi.org/10.6919/ICJE.202502_11(2).0011

Keywords:

Laser Guidance System; Mathematical Modeling; Algorithm Accuracy; Machine Vision; MATLAB Simulation; Adaptive Neuro-Fuzzy Inference System.

Abstract

In complex geological environments, traditional laser target measurement algorithms face challenges due to multipath effects and spot identification errors, significantly impacting measurement accuracy. This study investigates the optimization of signal processing and spot recognition algorithms for a laser-targeted Tunnel Boring Machine (TBM) guidance system. Utilizing Halcon software for spot image processing and conducting MATLAB simulations, the research verifies the accuracy of position and attitude calculations of the laser target during the TBM digging process. Additionally, an Adaptive Neuro-Fuzzy Inference System (ANFIS) is introduced to predict thrust adjustment requirements for shield attitude control, considering multiple influencing factors. The results indicate that the coordinate deviation of the TBM cutter center was maintained within ±20 mm, meeting the design requirements, and the ANFIS model demonstrated strong learning capabilities in attitude control. These findings offer innovative ideas and methods to enhance the construction accuracy and efficiency of TBM guidance systems, addressing the limitations of traditional measurement techniques.

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