Using of a diverse field algorithm in ultrasonic signal processing for nondestructive testing

2001 ◽  
Vol 15 (1) ◽  
pp. 3-6 ◽  
Author(s):  
K. M. Mahmud ◽  
N. Baba ◽  
R. Ohba
Keyword(s):  
Signal Processing ◽  
Nondestructive Testing ◽  
Ultrasonic Signal ◽  
Diverse Field

Effective detection of metal surface defects based on double-line laser ultrasonic with convolutional neural networks

2021 ◽  
pp. 2150263
Author(s):  
Zixi Liu ◽  
Zhengliang Hu ◽  
Longxiang Wang ◽  
Tianshi Zhou ◽  
Jintao Chen ◽  
...  
Keyword(s):  
Signal Processing ◽  
Metal Surface ◽  
Surface Defects ◽  
Ultrasonic Signal ◽  
Classification Model ◽  
Frequency Resolution ◽  
Laser Ultrasonic ◽  
Double Line ◽  
Time Frequency ◽  
Defects Classification

The time–frequency analysis by smooth Pseudo-Wigner-Ville distribution (SPWVD) is utilized for the double-line laser ultrasonic signal processing, and the effective detection of the metal surface defect is achieved. The double-line source laser is adopted for achieving more defects information. The simulation model by using finite element method is established in a steel plate with three typical metal surface defects (i.e. crack, air hole and surface scratch) in detail. Besides, in order to improve the time resolution and frequency resolution of the signal, the SPWVD method is mainly used. In addition, the deep learning defect classification model based on VGG convolutional neural network (CNN) is set up, also, the data enhancement method is adopted to extend training data and improve the defects detection properties. The results show that, for different types of metal surface defects with sub-millimeter size, the classification accuracy of crack, air holes and scratch surface are 94.6%, 94% and 94.6%, respectively. The SPWVD and CNN algorithm for processing the laser ultrasonic signal and defects classification supplies a useful way to get the defect information, which is helpful for the ultrasonic signal processing and material evaluation.

Denoising and Defect Diagnosis of Material Ultrasonic Detection signal Based on Best Wavelet Packet Base

2012 ◽  
Vol 239-240 ◽  
pp. 52-56
Author(s):  
Xiao Ling Yan ◽  
Shi Yun Dong ◽  
Wang Long Wang ◽  
Bin Shi Xu
Keyword(s):  
Nondestructive Testing ◽  
Wavelet Packet ◽  
Steel Specimen ◽  
Ultrasonic Signal ◽  
Defect Size ◽  
New Method ◽  
Accurate Information ◽  
Ultrasonic Nondestructive Testing ◽  
Internal Defect ◽  
Ultrasonic Detection

The use of ultrasonic nondestructive testing of material internal defect，ultrasonic signal acquired at actual working spot usually includes large amount of noise.Extraction of the defect characteristic information will be influeced greatly if the ultrasonic signal is not effectively denoised. A new method based on best wavelet packet base is present to denoise and detect the ultrasonic signal. The superiority of new method is verified by simulation examples. Experiment of processing ultrasonic signal which comes from the 45 Steel specimen with flaws has been implemented. The accurate information that characterizes of defect size,location can be extracted from the processing result, the results show that the new method based on best wavelet packet base is in favor of enhancing the degree of accuracy for quantitatively analyzing the defect inside the material.

Application of Wavelet Analysis in Nondestructive Testing of Steel and Iron Materials and DSP Implementation

2013 ◽  
Vol 321-324 ◽  
pp. 1270-1273
Author(s):  
Pei Yue Liu ◽  
Jun Fen Wang ◽  
Bao Qiu Ma
Keyword(s):  
Signal Processing ◽  
Nondestructive Testing ◽  
Wavelet Analysis ◽  
Digital Signal Processing ◽  
Digital Signal ◽  
Analog Signal ◽  
Testing Device ◽  
Dsp Implementation ◽  
Testing Signal ◽  
Wavelet Algorithm

Aiming at improving the unideal testing result by means of analog signal processing, wavelet analysis is introduced in the nondestructive testing of steel and iron materials, based on the characteristics of electromagnetic nondestructive testing signal. According to the requirement of wavelet algorithm for hardware, the advantages of DSP, digital signal processing function and high calculating speed, design scheme of the steel electromagnetic nondestructive testing device is proposed in this paper. Experiments show that this method can extract detection signal effectively.

The Research of Signal Processing in Ultrasonic Nondestructive Testing and Evaluation

2013 ◽  
Vol 712-715 ◽  
pp. 2069-2075
Author(s):  
Chun An Ai ◽  
Qiao Wang ◽  
Zhi Gao Xu
Keyword(s):  
Neural Network ◽  
Support Vector Machine ◽  
Signal Processing ◽  
Nondestructive Testing ◽  
Ultrasonic Testing ◽  
Processing Technology ◽  
Support Vector ◽  
Ultrasonic Nondestructive Testing ◽  
Qualitative And Quantitative ◽  
Testing And Evaluation

The development of signal processing technology not only improves the reliability of qualitative and quantitative ultrasound detection, but also promotes the sensitivity and precision. This paper introduces the new progress of signal processing technology in application of Ultrasonic Nondestructive Testing, including the basic principle, characteristic and localization of Wavelet Transform, Adaptive Filter Technique, Artificial Neural Network and Support Vector Machine application in Ultrasonic Testing, and the trend of development in the future.

A comparison of computing architectures for ultrasonic signal processing

2006 ◽  
Author(s):  
A. Hernandez ◽  
J. Urena ◽  
M. Mazo ◽  
A. Jimenez ◽  
J.J. Garcia ◽  
...  
Keyword(s):  
Signal Processing ◽  
Ultrasonic Signal
Sign in / Sign up

Export Citation Format

Share Document