Effect of contaminations on the acoustic emissions during wire and arc additive manufacturing of 316L stainless steel
Effect of contaminations on the acoustic emissions during wire and arc additive manufacturing of 316L stainless steel
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DOI：
10.1016/j.addma.2021.102585
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发表时间：
2021-12
影响因子：
11
通讯作者：
A. Ramalho;T. Santos;Ben Bevans;Z. Smoqi;Prahalada K. Rao;J. P. Oliveira
中科院分区：
文献类型：
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作者：
A. Ramalho;T. Santos;Ben Bevans;Z. Smoqi;Prahalada K. Rao;J. P. Oliveira
增材制造（AM）工艺允许创建具有近净形状的复杂零件。线弧增材制造（WAAM）是一种AM工艺，可以以低材料浪费和高生产率生产大型金属部件。通常，WAAM能够实现粉末基AM工艺的10倍以上的体积沉积速率。然而，WAAM的高沉积速率需要高的热输入来熔化大体积的材料，这又导致潜在的缺陷，例如孔隙、裂纹、变形、机械性能损失和低尺寸精度。因此，为了在工业环境中实际实施WAAM工艺，必须确保无污染的生产。因此，为了保证WAAM的生产级可扩展性，在过程中监控和检测缺陷形成是至关重要的。这项工作的目的是表征不同污染物对WAAM声谱的影响，并为基于麦克风的声学传感方法用于监测WAAM制造部件的质量奠定基础。为了实现这一目标，WAAM部件被故意引入缺陷，如材料污染，并使用时域和频域技术，即功率谱密度和短时傅立叶变换分析声信号。所获得的特征被用于确定缺陷形成的位置。研究结果表明，通过分析WAAM过程的声谱，可以识别污染物对WAAM的影响。
Additive Manufacturing (AM) processes allow the creation of complex parts with near net shapes. Wire and arc additive manufacturing (WAAM) is an AM process that can produce large metallic components with low material waste and high production rates. Typically, WAAM enables over 10-times the volumetric deposition rates of powder-based AM processes. However, the high depositions rates of WAAM require high heat input to melt the large volume of material, which in turn results in potential flaws such as pores, cracks, distortion, loss of mechanical properties and low dimensional accuracy. Hence, for practical implementation of the WAAM process in an industrial environment it is necessary to ensure flaw-free production. Accordingly, to guarantee the production-level scalability of WAAM it is fundamental to monitor and detect flaw formation during the process. The objective of this work is to characterize the effects of different contaminations on the acoustic spectrum of WAAM and lay the foundations for a microphone-based acoustic sensing approach for monitoring the quality of WAAM-fabricated parts. To realize this objective, WAAM parts were processed with deliberately introduced flaws, such as material contamination, and the acoustic signals were analyzed using the time and frequency domain techniques, namely, Power Spectral Density, and Short Time Fourier Transform. The signatures obtained were used to pinpoint the location of flaw formation. The results obtained in this study show that the effects of contamination in WAAM can be identified through the analysis of the acoustic spectrum of the process.