Flaw Detection in Pipe-Welded Zone by Using Wavelet Transform and SH-EMAT

2012 ◽  
Vol 36 (12) ◽  
pp. 1511-1519 ◽  
Author(s):  
Jin-Hyuk Lee ◽  
Dae-Hyun Kim
2007 ◽  
Vol 347 ◽  
pp. 115-120
Author(s):  
Magdalena Rucka ◽  
Krzysztof Wilde

This paper presents experimental study on dispersive waves propagation in steel rails. The propagation of longitudinal and transverse waves was generated by an impulse hammer and measured in three points. Wavelet transform (WT) and short time Fourier transform (STFT) were applied to analyze the time signals. Analysis of signal by STFT does not provide a proper timefrequency representation due to a fixed size window. The wavelet transform can effectively identify the time-frequency components in waves. The wavelet signal processing of the experimental wave propagation signals is intended to be used for rail flaw detection.


2011 ◽  
Vol 383-390 ◽  
pp. 4755-4761
Author(s):  
Shao Jiang Wang ◽  
Li Hou ◽  
Yu Lin Wang ◽  
Jian Quan Zhang

In order to ensure that small diameter steel pipes with thick wall have high intensity and high quality, ultrasonic immersion method with focusing probe was used to detect the flaw of the small-diameter steel pipes with thick wall. In practice, the echoes are often corrupted with external noise or internal noise, therefore, it is necessary to reduce the noise and to enhance the SNR of ultrasonic signals. A technique for improving the SNR of ultrasonic signals using wavelet transform is presented. In this method, WT, consider as one band-pass filter, is used to remove the noises. The performance of this technique has been verified by experimental, which is done by using a series of flaw ultrasonic echoes obtained from a specimen of the small-diameter steel pipes with thick wall. In particular we have found the processing of the ultrasonic signals using wavelet transform extremely useful for noise reduction. After processing, the SNR of ultrasonic signals are enhanced substantially. All experimental results show that this technique is effective for removing the white noise from the ultrasonic signals.


1997 ◽  
Vol 36 (04/05) ◽  
pp. 356-359 ◽  
Author(s):  
M. Sekine ◽  
M. Ogawa ◽  
T. Togawa ◽  
Y. Fukui ◽  
T. Tamura

Abstract:In this study we have attempted to classify the acceleration signal, while walking both at horizontal level, and upstairs and downstairs, using wavelet analysis. The acceleration signal close to the body’s center of gravity was measured while the subjects walked in a corridor and up and down a stairway. The data for four steps were analyzed and the Daubecies 3 wavelet transform was applied to the sequential data. The variables to be discriminated were the waveforms related to levels -4 and -5. The sum of the square values at each step was compared at levels -4 and -5. Downstairs walking could be discriminated from other types of walking, showing the largest value for level -5. Walking at horizontal level was compared with upstairs walking for level -4. It was possible to discriminate the continuous dynamic responses to walking by the wavelet transform.


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