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<p>This study proposes an optimized induction brazing approach for waveguides aimed at improving joint quality and thermal stability, which are critical requirements in high-reliability aerospace assemblies. A multi-objective optimization framework is formulated to minimize deviation from a target temperature profile (within ± 5&#xa0;°C), reduce temperature differences between brazed parts to below 2&#xa0;°C, and limit heating-rate mismatch to less than 0.2&#xa0;°C/s. Optimal trade-offs among these competing objectives are obtained using the Non-dominated Sorting Genetic Algorithm II (NSGA-II), with simplified single- and bi-objective formulations adopted for practical implementation. The thermal behavior of the waveguide is modeled using a heat conduction equation accounting for reflected electromagnetic energy. The optimized trajectories are implemented using a PID-controlled induction heating system with infrared pyrometric feedback. Experimental validation on aluminum alloy AD31 waveguides demonstrates that the proposed method reduces thermal nonuniformity to below 2&#xa0;°C and decreases the joint defect rate to 1%, confirming its effectiveness for stable and high-quality induction brazing.</p>

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Automated induction brazing control system based on optimal trajectory planning

  • 期刊论文

  • 发表日期：

    2026年2月3日

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  • Vadim Tynchenko,
  • Sergei Kurashkin,
  • Dmitry Martysyuk,
  • Alexander Murygin,
  • Valeriya Tynchenko,
  • Ivan Malashin

摘要

This study proposes an optimized induction brazing approach for waveguides aimed at improving joint quality and thermal stability, which are critical requirements in high-reliability aerospace assemblies. A multi-objective optimization framework is formulated to minimize deviation from a target temperature profile (within ± 5 °C), reduce temperature differences between brazed parts to below 2 °C, and limit heating-rate mismatch to less than 0.2 °C/s. Optimal trade-offs among these competing objectives are obtained using the Non-dominated Sorting Genetic Algorithm II (NSGA-II), with simplified single- and bi-objective formulations adopted for practical implementation. The thermal behavior of the waveguide is modeled using a heat conduction equation accounting for reflected electromagnetic energy. The optimized trajectories are implemented using a PID-controlled induction heating system with infrared pyrometric feedback. Experimental validation on aluminum alloy AD31 waveguides demonstrates that the proposed method reduces thermal nonuniformity to below 2 °C and decreases the joint defect rate to 1%, confirming its effectiveness for stable and high-quality induction brazing.