Corrosion steel welding cooperative control method and system

Through the multi-dimensional sensor array and adaptive Kalman filtering algorithm combined with multi-objective optimization algorithm, dynamic monitoring of the corrosive steel welding process and process parameter optimization are achieved, the problem of unstable weld quality in traditional methods is solved, the reliability and safety of welded joints are improved, and it is suitable for key structures in corrosive environments.

CN120460845AActive Publication Date: 2025-08-12THE 2ND ENG CO LTD OF CHINA RAILWAY URBAN CONSTR GRP
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Patent Information

Application Number
CN202510977834.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-07-16
Publication Date
2025-08-12
Estimated Expiration
2045-07-16

AI Technical Summary

Technical Problem

The existing corrosive steel welding technology lacks a comprehensive analysis of the corrosion grade distribution of materials in the weld area, the solidification behavior of the molten pool and the heat input efficiency, which makes it difficult to control the dynamic stability of the molten pool and the weld forming quality during the welding process, and cannot meet the manufacturing requirements of high-reliability welding structures in corrosive environments.

Method used

Through a multi-dimensional sensor array, weld geometric parameters, molten pool dynamic characteristic parameters and welding heat input parameters are collected in real time, and a characteristic space model of corroded steel welds is constructed. The melt pool morphology evolution prediction model is established in combination with the adaptive Kalman filtering algorithm. A multi-objective optimization algorithm is used to generate a dynamic adjustment strategy for welding process parameters. Through the coordinated implementation of the welding robot motion control system and the welding power control system, the coordinated control of molten pool dynamics, heat input distribution and weld forming is achieved.

Benefits of technology

It realizes multi-source data fusion and dynamic modeling prediction of corrosive steel welding process, improves the quality of weld forming and joint mechanical properties, ensures the stability, reliability and efficiency of the welding process, and is suitable for key structures such as bridges and pressure vessels that have been in corrosive environments for a long time.

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Abstract

The invention relates to the technical field of welding, in particular to a corrosion steel welding cooperative control method and system. Comprising the following steps that welding seam geometric parameters, molten pool dynamic characteristic parameters and welding heat input parameters in the corrosion steel welding process are collected in real time through a multi-dimensional sensor array; constructing a corroded steel welding seam feature space model based on the welding seam geometric parameters, and determining material corrosion grade distribution and mechanical property parameters of a welding seam area in combination with a preset corroded steel material database; a molten pool form evolution prediction model is established through an adaptive Kalman filtering algorithm by utilizing the dynamic characteristic parameters of the molten pool and the welding heat input parameters, and the solidification behavior and the welding seam forming trend of the molten pool are predicted in real time; according to the material corrosion grade distribution, the mechanical property parameters and the molten pool forming trend, a dynamic adjustment strategy of the welding process parameters is generated through a multi-objective optimization algorithm; the reliability and safety of the corrosion steel welding joint can be improved.
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Citation Information

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