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Läpihitsautuvuuden varmistaminen MAG-hitsauksessa infrapuna-termografian ja neuroverkon avulla

机译:使用红外热成像和神经网络确保MAG焊接的可焊性

摘要

In this study, an infrared thermography based sensor was studied with regard to usability and the accuracy of sensor data as a weld penetration signal in gas metal arc welding. The object of the study was to evaluate a specific sensor type which measures thermography from solidified weld surface. The purpose of the study was to provide expert data for developing a sensor system in adaptive metal active gas (MAG) welding. Welding experiments with considered process variables and recorded thermal profiles were saved to a database for further analysis. To perform the analysis within a reasonable amount of experiments, the process parameter variables were gradually altered by at least 10 %. Later, the effects of process variables on weld penetration and thermography itself were considered. SFS-EN ISO 5817 standard (2014) was applied for classifying the quality of the experiments. As a final step, a neural network was taught based on the experiments. The experiments show that the studied thermography sensor and the neural network can be used for controlling full penetration though they have minor limitations, which are presented in results and discussion. The results are consistent with previous studies and experiments found in the literature.
机译:在这项研究中,研究了基于红外热成像的传感器的可用性和作为气体金属电弧焊中焊缝熔深信号的传感器数据的准确性。研究的目的是评估一种特定的传感器类型,该传感器可测量凝固焊接表面的热像图。这项研究的目的是为开发自适应金属活性气体(MAG)焊接传感器系统提供专家数据。将考虑了工艺变量和记录的热曲线的焊接实验保存到数据库中,以进行进一步分析。为了在合理数量的实验中进行分析,过程参数变量至少要逐渐改变10%。后来,考虑了工艺变量对焊缝熔深和热成像本身的影响。 SFS-EN ISO 5817标准(2014)用于对实验质量进行分类。最后一步,根据实验讲授了神经网络。实验表明,所研究的热成像传感器和神经网络虽然有一些局限性,但仍可用于控制完全穿透,在结果和讨论中都有介绍。结果与文献中先前的研究和实验一致。

著录项

  • 作者

    Kinnunen Jussi;

  • 作者单位
  • 年度 2016
  • 总页数
  • 原文格式 PDF
  • 正文语种 en_US
  • 中图分类

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