Posture control method for heading machine based on multi-source data fusion and dynamic solution

By deploying intelligent sensing nodes on the shaft tunneling machine, real-time collection of multi-source data and establishment of a coupled dynamic model, the problems of large error, poor robustness and control lag in existing guidance methods are solved, and high-precision and safe attitude control of the tunneling machine is achieved.

CN121879159BActive Publication Date: 2026-05-29CHINESE PEOPLES ARMED POLICE FORCE JIANGXI HYDRO POWER NO 2 GENERAL GRP
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
CHINESE PEOPLES ARMED POLICE FORCE JIANGXI HYDRO POWER NO 2 GENERAL GRP
Filing Date
2026-03-19
Publication Date
2026-05-29

AI Technical Summary

Technical Problem

Existing shaft tunneling machine guidance methods suffer from problems such as large model simplification errors, sensitivity to environmental disturbances, lagging control strategies, and lack of self-learning capabilities, resulting in low guidance accuracy, poor robustness, and insufficient safety.

Method used

By employing a multi-source data fusion and dynamic solution method, intelligent sensor nodes are deployed on the boom to collect real-time data on the boom's dynamic response and the distance to the shaft wall. A coupled dynamic model of boom-shaft-tunneling machine is established, and an intelligent control strategy is generated by combining adaptive state estimation algorithms and model predictive control. The shaft geometry model is also updated online.

Benefits of technology

It improves the accuracy of tunneling machine attitude calculation to the centimeter or even millimeter level, enhances the reliability and safety of the system, realizes active obstacle avoidance control, and improves construction safety and the level of intelligent engineering management.

✦ Generated by Eureka AI based on patent content.

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Abstract

The application provides a heading machine posture control method based on multi-source data fusion and dynamic calculation, which comprises the following steps: firstly, real-time extraction of the geometric deformation features and defect features of the shaft wall; establishment of a boom-shaft wall-heading machine coupling dynamics model fused with the constraint effect of the shaft wall; taking the state data of the heading machine, the geometric deformation features and defect features of the shaft wall, and the dynamic response data of the boom as observation inputs, real-time calculation of the current posture state of the heading machine through an adaptive state estimation algorithm; and generation of a control strategy for adjusting the posture of the heading machine and realizing shaft wall obstacle avoidance by using a model predictive control algorithm containing an environmental risk penalty term. The application solves the problem of the assumption defect of the traditional geometric method that the boom is regarded as an "ideal rigid rod" by establishing a boom-shaft wall-heading machine coupling dynamics model for state calculation, and improves the posture calculation accuracy from the decimeter level to the centimeter or even millimeter level, thereby greatly enhancing the reliability of the guide system.
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