Abstract
Spectral analysis can realize the simultaneous detection of various elements with the advantages of fast response speed and low detection limit. Therefore, it has been widely used in metallurgy, geology, materials and medicine and other industries. With the development of electronic technology and computer technology, emission spectrum analysis technology has been developed rapidly. The characteristics of the arc welding process can be diagnosed by means of emission spectroscopy. Based on analyzing the characteristics of spectral lines of each element, this chapter proposes to extract spectral lines accurately and scientifically based on clustering algorithm, so as to avoid the interference of external factors such as zero drift and insufficient resolution of instruments. In order to obtain the optimal results, the k-medoids clustering method is improved to realize automatic acquisition of number of distinct categories and intelligent selection of initial points. In addition, the spectral distance suitable for spectral data was proposed as the measurement function. The centers obtained by clustering, namely the atomic and ion spectral lines of each element, are preliminarily studied. Furthermore, the influence of welding process parameters on the spectral lines is explored.
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Huang, Y., Chen, S. (2020). Basic Characteristics of Arc Spectrum in P-GTAW Process. In: Key Technologies of Intelligentized Welding Manufacturing. Springer, Singapore. https://doi.org/10.1007/978-981-13-7549-1_3
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DOI: https://doi.org/10.1007/978-981-13-7549-1_3
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Online ISBN: 978-981-13-7549-1
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