Title :
Magnetic Flux Leakage signal processing in strip steel flaw area detection
Author :
Jiangying Chen ; Weiting Chen ; Shijin Qian ; Delu Chen
Author_Institution :
Software Eng. Inst., East China Normal Univ., Shanghai, China
Abstract :
The strip steel is widely used in industries, but there always exists some flaws during its manufacturing. The flaws are difficult to be detected and the analysis of the data obtained from Magnetic Flux Leakage (MFL) inspection of the strip steel is quite a challenge. In order to solve this problem, the MFL data is first processed with difference method, and then removed the baseline drift by wavelet transform. Wavelet-based NLMS adaptive filter as well as wavelet thresholding is further used to remove noises. As for the feature extraction section, k-step deviation method has been improved and successfully applied to characterize the default area.
Keywords :
adaptive filters; difference equations; feature extraction; image segmentation; magnetic flux; production engineering computing; steel; strips; wavelet transforms; MFL data; difference method; feature extraction section; k-step deviation method; magnetic flux leakage signal processing; strip steel flaw area detection; wavelet thresholding; wavelet transform; wavelet-based NLMS adaptive filter; Adaptive filters; Magnetic flux leakage; Sensors; Steel; Strips; Wavelet transforms; Adaptive Filter; Baseline Drift Removing; K-step Deviation Method; Magnetic Flux Leakage Signal; Wavelet Transformation;
Conference_Titel :
Image and Signal Processing (CISP), 2013 6th International Congress on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4799-2763-0
DOI :
10.1109/CISP.2013.6745219
