@inproceedings{6d29d94f2d0a4e06a92167521e08d791,
title = "Porosity defect detection based on FastICA-RBF during pulsed TIG welding process",
abstract = "Porosity is a common defect of the aluminum alloy pulsed alternating current (AC) argon tungsten-arc welding (TIG) welding, which can cause huge damage to weld quality. The spectral information which is directly derived from the optical radiation of the arc is intrinsically related to the welding defects. Aiming at the redundancy of arc spectral, this paper proposed a method of porosity defect detection based on fast independent component analysis (fastICA) and radial basis function (RBF) network. The spectral data is collected by spectrometer, and continuous spectra are removed by calculating lower envelope twice. Then fastICA is applied to extract features from selected line spectra. Finally, the porosity defect is detected by RBF network according to the mean value in period of extracted features. Experimental results show that the proposed method can be used to detect the porosity defects during aluminum alloy pulsed TIG welding process.",
keywords = "RBF network, arc spectral, fastICA, porosity defect detection, pulsed TIG welding",
author = "Riwei Luan and Guangrui Wen and Ruxin Zhang and Zheng Chen and Zhifen Zhang",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 13th IEEE Conference on Automation Science and Engineering, CASE 2017 ; Conference date: 20-08-2017 Through 23-08-2017",
year = "2017",
month = jul,
day = "1",
doi = "10.1109/COASE.2017.8256161",
language = "英语",
series = "IEEE International Conference on Automation Science and Engineering",
publisher = "IEEE Computer Society",
pages = "548--553",
booktitle = "2017 13th IEEE Conference on Automation Science and Engineering, CASE 2017",
}