Study of Feature Extraction Method in Ultrasonic Phased Array Testing for Long-Distance Pipeline

2008 ◽  
Author(s):  
Jian Li ◽  
Xianglin Zhan ◽  
Shili Chen ◽  
Zhoumo Zeng ◽  
Shijiu Jin ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Extraction Method ◽  
Phased Array ◽  
Flaw Detection ◽  
Long Distance ◽  
Feature Extraction Method ◽  
Feature Extraction Algorithm ◽  
Extraction Algorithm ◽  
Ultrasonic Phased Array ◽  
Flaw Classification

Though ultrasonic phased array technology is more efficient than traditional manual ultrasonic testing method, automatic flaw classification is a challenge and still hasn’t been well solved. Whether the representative features can be extracted from each type of ultrasonic flaw signal is a key to influencing the accuracy rate of automatic flaw classification. In this paper, second generation wavelet transform (SGWT) is proposed as a flaw feature extraction method, having the advantages of high computation speed, simple structure and occupying less memory. After introducing the principle of SGWT, the SGWT-based feature extraction algorithm is analyzed. Separability measure based on Euclidean distance is introduced as the evaluation criterion to assess flaw feature extraction performance. For comparison, first generation wavelet packet transform (WPT), a common feature extraction method, is also adopted to extract flaw feature. The experiment result is indicated that the classification performance of SGWT-based feature extraction algorithm is improved than WPT-based feature extraction algorithm, and the classification speed of the former is almost two times of the latter, which is valuable for automatic flaw detection and classification of pipeline girth weld.

An Automatic Flaw Identification Method for Defect Inspection of Pipeline Girth Weld

2008 ◽  
Author(s):  
Jian Li ◽  
Xianglin Zhan ◽  
Shili Chen ◽  
Jingchang Zhuge ◽  
Shijiu Jin ◽  
...  
Keyword(s):  
Phased Array ◽  
Flaw Detection ◽  
Inspection System ◽  
Energy Status ◽  
Long Distance ◽  
Feature Extraction Method ◽  
Identification Method ◽  
Ultrasonic Phased Array ◽  
Flaw Classification ◽  
Girth Welds

Various types of defect may be formed in girth welds of long-distance pipeline in the process of welding. They are hidden dangers to pipeline transportation safety. Currently, ultrasonic phased array instrument is commonly adopted for quick automatic positioning and quantitative analysis of flaws in the girth weld after welding. But as for qualitative analysis – flaw classification, traditional manual identification method is still used. By traditional method, human-made error is easily introduced and classification result is depended on the detection experiences of the inspecting person. To overcome these deficiencies, a new method combined second generation wavelet transform (SGWT) with Radial Basis Function neural network (RBFN) is proposed in this paper, realizing automatic flaw classification and reducing human factors impaction. SGWT is ideally matched local characteristics of the flaw signal, improving both the computational speed and flaw classification efficiency. Then, based on the “energy-status” feature extraction method and the above SGWT analysis, feature eigenvectors of the flaw signals are extracted, training the following RBFN. And then when the feature of any flaw is extracted, it can be recognized by the network. The output of the network is the type of the input flaw signal, realizing automatic flaw classification. Finally, an ultrasonic phased array inspection system is described. The system is integrated with automatic flaw detection and classification. Experiments are tested on a long-distance pipeline girth weld block with artificial defects in it. The results validate that the proposed method is efficient, which is helpful to increasing inspection speed and reliability of flaw inspection for long-distance pipeline girth welds.

A FOURIER-RADIAL DESCRIPTOR ALGORITHM FOR INVARIANT FEATURE EXTRACTION

2006 ◽  
Vol 04 (01) ◽  
pp. 197-212
Author(s):  
CHALLA S. SASTRY ◽  
ARUN K. PUJARI ◽  
B. L. DEEKSHATULU
Keyword(s):  
Feature Extraction ◽  
Extraction Method ◽  
Symmetric Functions ◽  
It Use ◽  
Feature Extraction Method ◽  
Invariant Feature ◽  
Feature Extraction Algorithm ◽  
Extraction Algorithm ◽  
Gabor Feature ◽  
Gabor Feature Extraction

By integrating the Fourier techniques and the edge information obtained using the radial symmetric functions, we propose in this paper an invariant feature extraction algorithm. Unlike the Gabor feature extraction method, the present method does not use direction dependent filters, nor does it use the images in polar form, for rotation invariance. Besides, the present Fourier-Radial invariant feature extraction algorithm, suitable for both the texture and non-texture images, has functional analogy with the Gabor feature extraction method, and hence, is easily implementable. It is mathematically proved, and justified through computations, that the method can generate the invariant and discriminative feature vectors. Our simulation results demonstrate that the method can be used for such applications as content-based image retrieval.

A modified welding image feature extraction algorithm for rotating arc narrow gap MAG welding

2015 ◽  
Vol 42 (3) ◽  
pp. 222-227 ◽  
Author(s):  
Wenhang Li ◽  
Yunhong Ji ◽  
Jing Wu ◽  
Jiayou Wang
Keyword(s):  
Feature Extraction ◽  
Extraction Method ◽  
Image Feature ◽  
Mag Welding ◽  
Narrow Gap ◽  
Image Feature Extraction ◽  
Content Type ◽  
Feature Extraction Method ◽  
Extraction Algorithm ◽  
Welding Image

Purpose The purpose of this paper is to provide a modified welding image feature extraction algorithm for rotating arc narrow gap metal active-gas welding (MAG) welding, which is significant for improving the accuracy and reliability of the welding process. Design/methodology/approach An infrared charge-coupled device (CCD) camera was utilized to obtain the welding image by passive vision. The left/right arc position was used as a triggering signal to capture the image when the arc is approaching left/right sidewall. Comparing with the conventional method, the authors’ sidewall detection method reduces the interference from arc; the median filter removes the welding spatter; and the size of the arc area was verified to reduce the reflection from welding pool. In addition, the frame loss was also considered in the authors’ method. Findings The modified welding image feature extraction method improves the accuracy and reliability of sidewall edge and arc position detection. Practical implications The algorithm can be applied to welding seam tracking and penetration control in rotating or swing arc narrow gap welding. Originality/value The modified welding image feature extraction method is robust to typical interference and, thus, can improve the accuracy and reliability of the detection of sidewall edge and arc position.

scholarly journals Research on Feature Extraction Method of Indoor Visual Positioning Image Based on Area Division of Foreground and Background

2021 ◽  
Vol 10 (6) ◽  
pp. 402
Author(s):  
Ping Zheng ◽  
Danyang Qin ◽  
Bing Han ◽  
Lin Ma ◽  
Teklu Merhawit Berhane
Keyword(s):  
Feature Extraction ◽  
Open Source Software ◽  
Extraction Method ◽  
Feature Matching ◽  
Physical World ◽  
Feature Points ◽  
Feature Extraction Method ◽  
Visual Positioning ◽  
Extraction Algorithm ◽  
Better Than

In the process of indoor visual positioning and navigation, difficult points often exist in corridors, stairwells, and other scenes that contain large areas of white walls, strong consistent background, and sparse feature points. Aiming at the problem of positioning and navigation in the real physical world where the walls with sparse feature points are difficult to be filled with pictures, this paper designs a feature extraction method, ARAC (Adaptive Region Adjustment based on Consistency) using Free and Open-Source Software and tools. It divides the image into foreground and background and extracts their features respectively, to achieve not only retain positioning information but also focus more energy on the foreground area which is favourable for navigation. In the test phase, under the combined conditions of illumination, scale and affine changes, the feature matching maps by the feature extraction algorithm proposed in this paper are compared with those by SIFT and SURF. Experiments show that the number of correctly matched feature pairs obtained by ARAC is better than SIFT and SURF, and whose time of feature extraction and matching is comparable to SURF, which verifies the accuracy and efficiency of the ARAC feature extraction method.

The Image Feature Extraction Algorithm Based on the DWT and the Improved 2DPCA

2014 ◽  
Vol 556-562 ◽  
pp. 5042-5045 ◽  
Author(s):  
Wu Li
Keyword(s):  
Feature Extraction ◽  
Extraction Method ◽  
Target Recognition ◽  
Image Feature ◽  
Image Feature Extraction ◽  
Two Dimension ◽  
Feature Extraction Method ◽  
Extraction Algorithm ◽  
New Feature ◽  
Pca Algorithm

The technology of 2DPCA is the feature extraction method proposed aiming at two-dimension image based on the traditional PCA algorithm. The paper proposed a improved weighting 2DPCA algorithm, combined with the two-dimension discrete DWT to handle the image, posing the new feature abstraction method, experiment improved that the new feature abstraction method can improve the target recognition efficiently compared with the original 2DPCA algorithm.

Research on the NPC Three-Level Inverter Fault Feature Extraction Method Based on Wavelet Analysis

2014 ◽  
Vol 494-495 ◽  
pp. 1410-1413
Author(s):  
Rong Hua ◽  
Ping Ping Ji
Keyword(s):  
Feature Extraction ◽  
Extraction Method ◽  
Wavelet Packet ◽  
Extraction Procedure ◽  
Wavelet Packet Transform ◽  
Matlab Simulation ◽  
Feature Extraction Method ◽  
Extraction Algorithm ◽  
Fault Feature Extraction ◽  
Fault Information

This paper study a fault feature extraction method based on wavelet packet transform, using this method to extract fault information of output signal in the NPC three-level inverter fault. After analysis the structure principle of NPC three-level inverter and the wavelet packets fault feature extraction algorithm, brings up a fault feature extraction procedure of NPC three-level inverter based on wavelet packet transform. Through MATLAB simulation experiments, prove the rationality of wavelet packet transform in fault feature extraction, and the reliability in intelligent fault diagnosis.

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