摘要
为了解决傅里叶变换轮廓术重建熔池三维面形遇到的频谱混叠困难,研究了二维小波变换原理,采用图像二维小波分解的方法对熔池图像进行多尺度分解,重构熔池的背景图像,滤除频域中的零频成分,解决了零频与基频的混叠问题。利用小波分解法结合傅里叶变换轮廓术较好地实现了基频信息的提取与熔池的表面重构,提高了傅里叶变换轮廓术的测量范围。
For overcoming the challenge of spectrum aliasing in the process of the welding pool surface reconstruction by means of the Fourier transform profilometry, the two dimension image wavelet decomposition were adopt- ed to decompose welding pool images in multiscale under the principle of two dimension wavelet transform. As a resuit, the zero frequency components were fhered from the frequency domain after the success in reconstruction of background image of welding pool within the above method. Thus, the two dimension wavelet transform contributes to solving spectrum aliasing between fundamental and zero frequency. The combination of wavelet decomposition and Fourier transform profilometry could help the realization of extracting fundamental frequency component and recovering welding pool surface, and also could improve the measuring range of Fourier transform profilometry.
出处
《南昌大学学报（工科版）》
CAS
2013年第4期353-357,共5页
Journal of Nanchang University(Engineering & Technology)
基金
国家自然科学基金资助项目(50565003
51065020)
关键词
光学传感
焊接熔池
小波分解法
傅里叶变换轮廓术
频谱混叠
频域滤波
optical sensing
arc welding pool
wavelet decomposition
Fourier transform proflometry
spectrum aliasing
frequency domain filtering
