Forecasting and Detection of Fatigue Cracks in Polycrystalline Alloys With Ultrasonic Testing Via Discrete Wavelet Transform

2021 ◽  
Vol 4 (3) ◽  
Author(s):  
Hassan Alqahtani ◽  
Asok Ray
Keyword(s):  
Fatigue Crack ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Ultrasonic Testing ◽  
Fatigue Testing ◽  
Fatigue Cracks ◽  
Ground Truth ◽  
Discrete Wavelet ◽  
Polycrystalline Alloys ◽  
Synergistic Combination

Abstract Forecasting and detection of fatigue cracks play a key role in damage mitigation of mechanical structures (e.g., those made of polycrystalline alloys) to enhance their service life, and ultrasonic testing (UT) has emerged as a powerful tool for detection of fatigue cracks at early stages of damage evolution. Along this line, the work reported in this paper aims to improve the performance of fatigue crack forecasting and detection based on a synergistic combination of discrete wavelet transform (DWT) and Hilbert transform (HT) of UT data, collected from a computer-instrumented and computer-controlled fatigue-testing apparatus. Performance of the proposed method is evaluated by comparison with the images generated from a digital microscope, which are treated as the ground truth in this paper. The results of comparison reveal that forthcoming fatigue cracks can be detected ahead of their appearance on the surface of test specimens. The proposed method apparently outperforms both HT and conventional DWT, when they are applied individually, because the synergistic combination of DWT and HT provides a better characterization of UT signal attenuation for detection of fatigue crack damage.

Improving Space Localization Properties of the Discrete Wavelet Transform

Informatica ◽  
2013 ◽  
Vol 24 (4) ◽  
pp. 657-675
Author(s):  
Jonas Valantinas ◽  
Deividas Kančelkis ◽  
Rokas Valantinas ◽  
Gintarė Viščiūtė
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Discrete Wavelet ◽  
Space Localization

An Adaptive Binarization Method for Cost-efficient Document Image System in Wavelet Domain

2020 ◽  
Vol 64 (3) ◽  
pp. 30401-1-30401-14 ◽  
Author(s):  
Chih-Hsien Hsia ◽  
Ting-Yu Lin ◽  
Jen-Shiun Chiang
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Document Image ◽  
Background Information ◽  
Raspberry Pi ◽  
Discrete Wavelet ◽  
Image System ◽  
Low Frequencies ◽  
Cost Efficient ◽  
Binarization Method

Abstract In recent years, the preservation of handwritten historical documents and scripts archived by digitized images has been gradually emphasized. However, the selection of different thicknesses of the paper for printing or writing is likely to make the content of the back page seep into the front page. In order to solve this, a cost-efficient document image system is proposed. In this system, the authors use Adaptive Directional Lifting-Based Discrete Wavelet Transform to transform image data from spatial domain to frequency domain and perform on high and low frequencies, respectively. For low frequencies, the authors use local threshold to remove most background information. For high frequencies, they use modified Least Mean Square training algorithm to produce a unique weighted mask and perform convolution on original frequency, respectively. Afterward, Inverse Adaptive Directional Lifting-Based Discrete Wavelet Transform is performed to reconstruct the four subband images to a resulting image with original size. Finally, a global binarization method, Otsu’s method, is applied to transform a gray scale image to a binary image as the output result. The results show that the difference in operation time of this work between a personal computer (PC) and Raspberry Pi is little. Therefore, the proposed cost-efficient document image system which performed on Raspberry Pi embedded platform has the same performance and obtains the same results as those performed on a PC.

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