Shaft cutting head slag accumulation bin slag discharge optimization design method and system

By using the Python platform for automatic modeling and Bayesian optimization algorithms, the problem of manual dependence in the design of the slag discharge structure of the vertical shaft cutting head was solved, achieving efficient parameter optimization and performance improvement, and making it suitable for rapid design verification under multiple working conditions.

CN122287273APending Publication Date: 2026-06-26ZHEJIANG UNIV +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
ZHEJIANG UNIV
Filing Date
2026-05-29
Publication Date
2026-06-26

AI Technical Summary

Technical Problem

The existing design of the vertical shaft cutting head slag removal structure relies on manual experience, resulting in low efficiency of parameter adjustment, heavy reliance on manual modeling processes, disconnect between simulation analysis and the actual situation, lack of systematic optimization methods, and difficulty in achieving high-frequency rapid iteration and efficient performance analysis.

Method used

Using Python as the core development platform, a closed-loop process of automatic modeling, simulation calculation, and parameter iterative optimization is established. Through automatic modeling, automatic simulation, and data analysis modules, the automatic adjustment of structural parameters and performance optimization are realized, and parameter optimization is carried out in combination with Bayesian optimization algorithm.

Benefits of technology

It significantly improves the efficiency and accuracy of the cutting head structure design, realizes high-frequency parameter iteration and rapid optimization under multiple working conditions, and enhances the performance and design quality of the slag discharge structure.

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Abstract

This invention discloses a method and system for optimizing the slag discharge design of a vertical shaft cutting head slag bin, belonging to the technical field of underground coal mine transportation equipment. The method is based on a Python script framework and includes an automatic modeling module, an automatic simulation module, and a data analysis and parameter optimization module. The automatic modeling module performs model verification and efficient automatic modeling of the slag bin structure; the automatic simulation module automatically performs mesh generation and boundary configuration on the modeling results and calls simulation software to run multiphysics simulations; the data analysis and parameter optimization module captures the slag discharge indicators of interest from the simulation results and calculates the slag discharge performance of the model, introducing a Bayesian optimization model for iterative optimization, achieving convergence of the structural parameters of the slag bin structure to the optimal structural parameters with the fewest simulations. This invention features high integration and strong automation, constructs a closed-loop optimization mechanism, breaks through the bottlenecks of existing design processes, and improves the efficiency and quality of structural performance design.
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