scholarly journals An Improved Feature Parameter Extraction Algorithm of Composite Detection Method Based on the Fusion Theory

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Zhou Ying ◽  
Jin Heli ◽  
Liu Banteng ◽  
Chen Yourong
Keyword(s):  
Eddy Current ◽  
Dispersion Model ◽  
Parameter Extraction ◽  
Quantitative Detection ◽  
Differential Signal ◽  
Feature Parameters ◽  
Pulsed Eddy Current ◽  
Extraction Algorithm ◽  
Feature Parameter ◽  
Subsurface Defects

An improved feature parameter extraction algorithm is proposed in this study to solve the problem of quantitative detection of subsurface defects. Firstly, the common feature parameters from the differential signal of pulsed eddy current and ultrasonic are extracted in time domain and frequency domain. Then, the dispersion model and ReliefF model are established to determine the weights of each parameter. Finally, the weights from the two different algorithms are fused by the D-S evidence theory to determine feature parameters. Compared with the PCA feature parameter algorithm from the pulsed eddy current or ultrasonic, the experiment results show the feature parameters extracted by the algorithm proposed in this paper are more effective in quantitative detection of subsurface defects. It will lead to high accuracy in the subsurface defections.

scholarly journals Detection of Subsurface Defects in Steels using Pulsed Eddy Current Thermography

2016 ◽  
Author(s):  
A. Taram ◽  
C. Roquelet ◽  
M. Anderhuber ◽  
P. Meilland ◽  
K. Mouhoubi ◽  
...  
Keyword(s):  
Eddy Current ◽  
Pulsed Eddy Current ◽  
Subsurface Defects

Improved Window Function in the Application of MFCC Feature Parameter Extraction

2014 ◽  
Vol 556-562 ◽  
pp. 3703-3706
Author(s):  
Le Qiang Bai ◽  
Xue Wei Zhang
Keyword(s):  
Recognition Rate ◽  
Parameter Extraction ◽  
Side Lobe ◽  
Window Function ◽  
Main Lobe ◽  
Impact Function ◽  
Extraction Algorithm ◽  
Feature Parameter ◽  
Lobe Width ◽  
Kaiser Window

In view of spectrum leakage and the contradictory problem of spectrum accuracy of main lobe and reducing spectrum leakage, MFCC algorithm based on improved window function is proposed. Improved window function is based on the mathematical analysis of Kaiser window, and under the condition of finite sampling points minuses weighted impact function where is at the frequencies that side lobe peaks of correspond to. The amplitude of improved window compared with Kaiser window is smaller, and main lobe width is the same, solving the conflicting problem of main lobe width and side lobe amplitude and reducing spectrum leakage. The experimental results show that speech recognition rate of MFCC feature parameter extraction algorithm based on improved window function is better than Kaiser window and Hamming window.

Automatic Defect Extraction and Segmentation in Welding Seam Based on X-Ray Images

2011 ◽  
Vol 130-134 ◽  
pp. 2558-2562
Author(s):  
Ming Quan Wang ◽  
Yu Wang
Keyword(s):  
Mathematical Morphology ◽  
Parameter Extraction ◽  
Thin Wall ◽  
Edge Extraction ◽  
Welding Seam ◽  
X Ray ◽  
Extraction Algorithm ◽  
Feature Parameter ◽  
Defect Extraction ◽  
Enhancement Algorithm

In light of the characteristic of thin-wall weld joint in X-ray image, Flaw-edge extraction algorithm and image enhancement algorithm which is based on mathematical morphology are proposed in the study of flaw extraction technique. Therefore, the area of flaw and background can be removed successfully. On this basis, there are two algorithms to identify different flaw types: one is that spatial domain transform to extract flaw edge for clack, the other one is mathematical morphology which is combined with iteration threshold to extract flaw edge for pore; Experimental results show that both of algorithms can implement flaw extraction and segmentation automatically, which is lay a good foundation for flaw feature parameter extraction and recognition.

scholarly journals Traditional Eddy Current–Pulsed Eddy Current Fusion Diagnostic Technique for Multiple Micro-Cracks in Metals

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2909 ◽  
Author(s):  
Zhenwei Wang ◽  
Yating Yu
Keyword(s):  
Eddy Current ◽  
Health Monitoring ◽  
Diagnostic Technique ◽  
Working Environment ◽  
Quantitative Detection ◽  
Safe Operation ◽  
Metal Structures ◽  
Pulsed Eddy Current ◽  
Micro Cracks ◽  
Oil Gas

Due to a harsh working environment, micro-cracks in metal structures (e.g., airplane, oil/gas pipeline, hydro-turbine) often lead to serious accidents, so health monitoring of the metals is of great significance to ensure their safe operation. However, it is hard to perform quantitative detection of multiple micro-cracks by a single nondestructive testing (NDT) technique because of their limits. To monitor for multiple micro-cracks in metals, a Traditional Eddy Current (TEC) and Pulsed Eddy Current (PEC) fusion NDT technique is proposed in this paper. In the proposed technique, the TEC technique is adopted to seek the locations of the micro-cracks in the whole of the metal, while the PEC technique is adopted to acquire information on the depth of micro-cracks automatically according to the location information by the TEC. The experiments indicate that the TEC–PEC fusion NDT system can localize the micro-cracks as well as detect the micro-cracks quantitatively and automatically; therefore, it can be applied in structural health monitoring of metal equipment or in picking candidate components in re-manufacturing engineering.

Scanning induction thermography for subsurface defect orientation detection and depth quantification

2020 ◽  
Vol 64 (1-4) ◽  
pp. 869-877
Author(s):  
Hui Xia ◽  
Erlong Li ◽  
Jianbo Wu ◽  
Qiao Qiu ◽  
Jie Wang ◽  
...  
Keyword(s):  
Eddy Current ◽  
Experimental Studies ◽  
Extraction Methods ◽  
Destructive Testing ◽  
Pulsed Eddy Current ◽  
Subsurface Defect ◽  
New Feature ◽  
Lock In ◽  
Non Destructive ◽  
Subsurface Defects

Pulsed eddy current thermography (PECT) and eddy current lock-in thermography (ECLIT) are non-destructive testing (NDT) techniques of high promising and interest in subsurface defect detection. In the previous researches, the induction coil was set above the defect region and it always parallel to the defect orientation. However, the location and orientation of subsurface defects cannot be determined before detection. Therefore, the scanning induction thermography (SIT) based on dynamic thermography is proposed by some researchers to localize and distinguish the subsurface defects. Still, the main challenges of SIT are how to detect the subsurface defect orientation and quantify the depth. So that, the quantitative analysis in SIT with the new feature extraction methods was investigated and improved to detect the subsurface defect orientation and quantify the defect depth within 5 mm by using experimental studies.

A Method Study of Recognizing the Defect Type for the Continuous Casting Slab by Pulsed Eddy Current

2011 ◽  
Vol 233-235 ◽  
pp. 2424-2427
Author(s):  
Ou Yang Qi ◽  
Li Zhi Zhang ◽  
Li Ming Zhao ◽  
Wan Hong Li ◽  
Song Peng
Keyword(s):  
Continuous Casting ◽  
Working Conditions ◽  
Eddy Current ◽  
Differential Method ◽  
Practical Significance ◽  
Differential Signal ◽  
Defect Type ◽  
Continuous Casting Slab ◽  
Pulsed Eddy Current ◽  
Peak Value

Defect of continue casting slab is closely related with technology and working conditions, one productive condition usually leads to the same type of defect. So it has a great practical significance to evaluate the operative process by effective recognition of defect types. In this paper, a damped oscillating signal is acquired by differential method. The defect type of continues casting slab is preliminary qualitative detected via three eigenvalue, the wave peak value(called WPV below), the lagging time of peak(called LTP below) and the peak value difference between the rising and failing edge(called PVD below) which extracting from the differential signal.

Analysis of field uniformity and quantitative evaluation of subsurface pitting corrosion in conductors via GPEC

2020 ◽  
Vol 64 (1-4) ◽  
pp. 19-29
Author(s):  
Shuting Ren ◽  
Yong Li ◽  
Bei Yan ◽  
Jinhua Hu ◽  
Ilham Mukriz Zainal Abidin ◽  
...  
Keyword(s):  
Quantitative Evaluation ◽  
Eddy Current ◽  
Pitting Corrosion ◽  
Gradient Field ◽  
Uniform Field ◽  
Eddy Current Method ◽  
Optimal Position ◽  
Pulsed Eddy Current ◽  
Field Uniformity ◽  
Processing Algorithms

Structures of nonmagnetic materials are broadly used in engineering fields such as aerospace, energy, etc. Due to corrosive and hostile environments, they are vulnerable to the Subsurface Pitting Corrosion (SPC) leading to structural failure. Therefore, it is imperative to conduct periodical inspection and comprehensive evaluation of SPC using reliable nondestructive evaluation techniques. Extended from the conventional Pulsed eddy current method (PEC), Gradient-field Pulsed Eddy Current technique (GPEC) has been proposed and found to be advantageous over PEC in terms of enhanced inspection sensitivity and accuracy in evaluation and imaging of subsurface defects in nonmagnetic conductors. In this paper two GPEC probes for uniform field excitation are intensively analyzed and compared. Their capabilities in SPC evaluation and imaging are explored through simulations and experiments. The optimal position for deployment of the magnetic field sensor is determined by scrutinizing the field uniformity and inspection sensitivity to SPC based on finite element simulations. After the optimal probe structure is chosen, quantitative evaluation and imaging of SPC are investigated. Signal/image processing algorithms for SPC evaluation are proposed. Through simulations and experiments, it has been found that the T-shaped probe together with the proposed processing algorithms is advantageous and preferable for profile recognition and depth evaluation of SPC.

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