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Ensemble of artificial neural networks to control the induction soldering of spacecraft's waveguide paths

机译:人工神经网络的集合来控制宇宙飞船波导路径的感应焊接

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This article discusses the development of an intelligent technology designed to solve the problem of controlling the process of induction soldering of waveguide paths of spacecraft. The solution to this problem is complicated by the peculiarities due to the use of non-contact temperature sensors. Intelligent methods have proven themselves well in solving control problems under conditions of uncertainty. The use of intelligent methods is well suited both for solving problems of identification and correction of errors in measuring instruments, and for direct control of the technological process of induction soldering of waveguide paths of spacecraft. The essence of the proposed technology lies in the use of ensemble of artificial neural networks to solve the problem of controlling the induction soldering process at its following stages: assessing the quality of temperature measurements in the heating zone obtained using pyrometric sensors; correction of measurements in case of detection of non-standard errors in measuring instruments; control of the induction heating process in the absence of reliable readings of measuring instruments. The use of the presented intelligent system will improve the quality of control of the technological process of induction soldering of waveguide paths of spacecraft by reducing costs associated with the features of the technological process and non-contact temperature measurement sensors.
机译:本文讨论了智能技术的开发,旨在解决控制航天器波导路径的感应焊接过程的问题。由于使用非接触式温度传感器,该问题的解决方案是复杂的。智能方法在解决不确定性条件下解决了控制问题。智能方法的使用非常适合解决测量仪器中误差的识别问题,以及直接控制航天器波导路径的感应焊接的技术过程。所提出的技术的本质在于利用人工神经网络的集合来解决其在其以下阶段控制感应焊接过程的问题:评估使用高温传感器获得的加热区中的温度测量质量;在测量仪器中检测非标准误差的情况下测量的校正;在没有可靠读数的测量仪器的情况下控制感应加热过程的控制。通过降低与技术过程和非接触温度测量传感器的特征相关的成本,使用所呈现的智能系统将提高航天器的波导路径的诱导焊接路径的技术过程的控制质量。

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