Flaw Detection in Wire and Arc Additive Manufacturing Using In-Situ Wide Frequency Bandwidth Acoustic Pressure

A. Ramalho, T. Santos, Ben Bevans, Z. Smoqi, Prahalada K. Rao, J. P. Oliveira
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Abstract

Wire and arc additive manufacturing (WAAM) is an additive manufacturing (AM) process that can produce large metallic components with low material waste and high production rates. However, WAAM’s high deposition rates require high heat input which can result in potential defects such as pores, cracks, lack of fusion or distortion. For practical implementation of the WAAM process in an industrial environment it is necessary to ensure defects-free production. However, the NDT inspection using traditional NDT techniques (ultrasound, eddy currents, x-ray, for example) is a very demanding task, especially during part production. Therefore, reliable online NDT inspection and monitoring techniques are needed for the industrial spread of WAAM. The objective of this work is to detect flaw formation on WAAM produced parts using in-situ acquired acoustic data with a frequency bandwidth from 10 to 1MHz. WAAM parts were processed with deliberately introduced contaminations while its acoustic signal was obtained to correlate different signal characteristics with defects. To identify flaw formation, two distinct types of microphones were employed to acquire data from the same deposition process. The processing of the signal consisted of applying time and frequency domain techniques, namely, Power Spectral Density and Short Time Fourier Transform. The acoustic signatures obtained allowed for the differentiation between flawed and flaw free signals and for the spatial location of the contaminations. The acoustic signal acquired also showed that the data acquired by conventional microphones is not enough to fully characterize the acoustic spectrum emitted by the WAAM process. This work demonstrates the potential of acoustic data and signal processing in the online inspection of WAAM produced parts.
利用原位宽频带声压检测线材和电弧增材制造中的缺陷
电线和电弧增材制造(WAAM)是一种增材制造(AM)工艺,可以生产大型金属部件,材料浪费少,生产率高。然而,WAAM的高沉积速率需要高热量输入,这可能导致潜在的缺陷,如孔隙,裂纹,缺乏融合或变形。为了在工业环境中实际实施WAAM工艺,有必要确保无缺陷生产。然而,使用传统无损检测技术(例如超声波,涡流,x射线)的无损检测是一项非常苛刻的任务,特别是在零件生产过程中。因此,WAAM的工业推广需要可靠的在线无损检测和监测技术。这项工作的目的是使用带宽从10到1MHz的现场采集声学数据来检测WAAM生产部件上的缺陷形成。在对WAAM零件进行加工时,故意引入污染物,同时获取其声信号,将不同的信号特征与缺陷联系起来。为了识别缺陷的形成,使用了两种不同类型的麦克风来获取来自同一沉积过程的数据。信号的处理包括应用时域和频域技术,即功率谱密度和短时傅里叶变换。所获得的声学特征允许区分有缺陷的和无缺陷的信号,以及污染物的空间位置。采集的声信号也表明,传统麦克风采集的数据不足以完全表征WAAM过程发出的声频谱。这项工作证明了声学数据和信号处理在WAAM生产零件在线检测中的潜力。
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