Study on intelligent image welding defects in recognition for the tube pressure vessels

Currently, the welding defects recognition of X-ray nondestructive inspection is principally carried out by manual work, which highly depends on the experience of the inspectors and costs plenty of workload. In this paper, an intelligent image processing and recognition method for the tube welding radiographic testing in large-scale pressure vessels is proposed. Firstly, the raw image is preprocessed by median filtering, pseudo point removing and non-lincar image enhancement. Secondly, the welded joints parts are separated from the whole image by edge detection and threshold segmentation algorithms. Then, the separated images are handled by FFT transformation. Finally, whether defects exist and the specific type of defects are judged by Support Vector Machine. Software developed basing on this method works stably on site, and experiments demonstrate that the recognition results are compliance with the JB/T 4730. 2 or ASME standards.

Classified recognition for metal magnetic memory signals of welding defects in API 5L X65 pipeline steel

Feature extraction and selection from signals is a key issue for metal magnetic memory testing technique. In order to realize the classification of metal magnetic memory signals of welding defects, four fractal analysis methods, such as box- counting, detrended fluctuation, minimal cover and rescaled-range analysis, were used to extract the feature signal after the original metal magnet memory signal was de-noising and differential processing, then the Karhunen-Lo^e transformation was adopted as classification tool to identify the defect signals. The result shows that this study can provide an efficient classification method for metal magnetic memory signal of welding defects.

Feature extraction of welding defect based on machine vision

There are many flaws in welding images such as noise, low contrast, and blurred edges, which affect feature extraction from welding defect regions and impede classification and recognition of welding defects. To deal with the complexity of welding defect images, this paper proposes an effective method for extracting the features of welding defect regions. Firstly, image preprocessing, image segmentation and image background removal are carried out to a welding image in order to extract welding defect region; and then an 8-connected-component labeling method is used to mark defect regions. Finally, it extracts geometric characteristic parameters including perimeter, area, circularity and others. The experimental result shows that the method proposed in the paper can accurately extract the features of welding defect regions. It has good adaptability and practicability.

Enlarged-end tool for friction stir lap welding towards hook defect controlling

Hook defect is one of the trickiest issues for friction stir lap welding,which remains to be resolved.In this study,a designed pin with an enlarged-end was proposed to control the interfacial hook defect by optimizing its morphology orientation.The insert aduncous structure at the advancing side is dissected by multilayer metallographic observation,which is the main character to terminate the inner-ward extension of the hook.The application of this tool was verified practical with a varied plunge depth of pin into the lower plate from 0.1 mm to 1.6 mm.The angle of the hook was small and terminated at the insert-structure or oriented toward the material convergence region.No joint fractured along the hook line and the highest joint efficiency reached 86%of the parent 6082-T4 aluminum alloy.

FEATURE ANALYSIS AND EXTRACTION OF INNER DEFECTS FOR SPOT WELD NUGGET OF ALUMINUM ALLOY

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Formative mechanism of the undercut defect in horizontal variable polarity plasma arc welding

Abstract Horizontal welding is important for heavy or huge welding structures. Keyhole mode variable polarity plasma arc welding of aluminum alloy plates with medium thickness was carried out in horizontal position. The characteristic of welding defects was introduced. Preliminary experiments indicated that the undercut defect could not be eliminated easily. The relationship between welding parameters and the undercut defect showed that this deject could be lessened by using higher heat input. The fluid flow of weld pool was observed by a high speed camera. The fluid flow in weld pool was not symmetric and much of molten metal gathered in the lower part. The fluid flow velocity in the lower part was bigger than that in the upper part. To this end, the formative mechanism of the undercut defect was proposed. The flowability of the molten metal was an influential factor for the undercut defect. A preheating method was designed to verify the formative mechanism.

Repair welding process of friction stir welding groove defect

The groove defect formed in the friction stir welding dramatically deteriorates weld appearances and mechanical properties of the joints owing to its larger size and penetration. Therefore, the friction stir repair welding was utilized to remove such a groove defect, and the focus was placed on the mechanical properties and microstructural characteristics of the repair joints so as to obtain an optimum repair welding process. The experimental results indicate that the groove defect can be removed by friction stir repair welding, and the offset repair welding process is superior to the symmetrical repair welding process. In the symmetrical repair welding process, a large number of fine cavity defects and an obvious aggregation of hard-brittle phase Al2Cu occur, accordingly the mechanical properties of the repair joint are weakened, and the fracture feature of repair joint is partially brittle and partially plastic. A good-quality repair joint can be obtained by the offset repair welding process, and the repair joint is fractured near the interface between the weld nugget zone and thermal-mechanically affected zone.

Multiaxial Fatigue Analysis on Reeled Deepwater Steel Catenary Risers with Girth Weld Defects

In the present study, we simulated the reel-lay installation process of deepwater steel catenary risers（SCRs） using the finite element method and proposed multiaxial fatigue analysis for reeled SCRs. The reel-lay method is one of the most efficient and economical pipeline installation methods. However, material properties of reeled risers may change, especially in the weld zone, which can affect the fatigue performance. Applying finite element analysis（FEA）, we simulated an installation load history through the reel, aligner, and straightener and analyzed the property variations. The impact of weld defects during the installation process, lack of penetration and lack of fusion, was also discussed. Based on the FEA results, we used the Brown-Miller criterion combined with the critical plane approach to predict the fatigue life of reeled and non-reeled models. The results indicated that a weld defect has a significant influence on the material properties of a riser, and the reel-lay method can significantly reduce the fatigue life of SCRs. The analysis conclusion can help designers understand the mechanical performance of welds during reel-lay installation.

Noise Reduction of Welding Defect Image Based on NSCT and Anisotropic Diffusion

In order to reduce noise effectively in the welding defect image and preserve the minutiae information, a noise reduction method of welding defect image based on nonsubsampled contourlet transform(NSCT) and anisotropic diffusion is proposed. Firstly, an X-ray welding defect image is decomposed by NSCT. Then total variation(TV) model and Catte_PM model are used for the obtained low-pass component and band-pass components, respectively. Finally, the denoised image is synthesized by inverse NSCT. Experimental results show that, compared with the hybrid method of wavelet threshold shrinkage with TV diffusion, the method combining NSCT with P_Laplace diffusion, and the method combining contourlet with TV model and adaptive contrast diffusion, the proposed method has a great improvement in the aspects of subjective visual effect, peak signal-to-noise ratio(PSNR) and mean-square error(MSE). Noise is suppressed more effectively and the minutiae information is preserved better in the image.

Defects of friction stir welded 1060 aluminum alloy and their effects on joint tensile property

9. 6 mm thick 1060-H24 aluminum alloy plates were friction stir welded and the influencing factors on groove and tunnel defects were examined. Results show that the welding speed range for achieving a groove-free joint is enlarged with increasing the rotating speed. The tunnel size decreases with decreasing the welding speed under the same rotating speed. Excessive or insufficient shoulder plunge depth will cause defective joints. At a relatively low rotating speed and high welding speed, the tool having a larger shoulder diameter has a larger range of processing parameters to obtain a groove-free joint. Moreover, the tensile fracture behaviors of the defective and defect-free samples are different.

Fatigue Behavior of a Dissimilar Aluminum Alloy Welding Joint With and Without Natural Defect

In order to investigate the influence of natural defect on the fatigue behavior of 5A06/7A05 dissimilar aluminum alloys welding joint,fatigue tests of two types of specimens with and without defects were carried out systematically under stress amplitude control conditions (stress ratio R=0.1) at normal temperature in laboratory air condition.Furthermore,a new parameter,i e,fatigue defect effect factor (FDEF) was introduced to assess the effect of defect on fatigue strength.The fatigue failure analysis was conducted as well to compare the fatigue and fracture behavior of the two types of specimens.The results show that:(1) natural defects have a strong effect on the fatigue lives of welding joint,and the differences between the specimens with and without defects can reach 80 times under a same theoretical net sectional stress;(2) the FDEF parameter introduced is effective to deal with the defect effect,and the FDEF decreases along with the increase of fatigue life.The mean relative error between the experimental data and predicted fatigue strength based on the FDEF is 10.2%;(3) the macro fracture of both types of specimens have three typical zones,i e,fatigue source zone,crack propagation zone and final fracture zone,while there are more than one fatigue sources for specimens with natural defects.The overall pattern of crack propagation zone and fracture zone are quite similar,but the morphologies are different in details.

Automated identification of steel weld defects,a convolutional neural network improved machine learning approach

This paper proposes a machine-learning-based methodology to automatically classify different types of steel weld defects,including lack of the fusion,porosity,slag inclusion,and the qualified(no defects)cases.This methodology solves the shortcomings of existing detection methods,such as expensive equipment,complicated operation and inability to detect internal defects.The study first collected percussed data from welded steel members with or without weld defects.Then,three methods,the Mel frequency cepstral coefficients,short-time Fourier transform(STFT),and continuous wavelet transform were implemented and compared to explore the most appropriate features for classification of weld statuses.Classic and convolutional neural network-enhanced algorithms were used to classify,the extracted features.Furthermore,experiments were designed and performed to validate the proposed method.Results showed that STFT achieved higher accuracies(up to 96.63%on average)in the weld status classification.The convolutional neural network-enhanced support vector machine(SVM)outperformed six other algorithms with an average accuracy of 95.8%.In addition,random forest and SVM were efficient approaches with a balanced trade-off between the accuracies and the computational efforts.

A new weld repair technique for friction stir welded aluminium structure:inertia friction pull plug welding

The paper gives an analysis on technical characteristics of repair techniques for friction stir welding defects. To overcome the defects,a new repair technique, inertia friction pull plug welding( IFPPW), was researched and its equipment was developed as well. Elementary datum was achieved by investigating the influences of technological parameters on mechanical properties and by analyzing the structural characteristics of repair joint with IFPPW. The study shows that the stability and reliability of welding process of IFPPW can be guaranteed through the constant energy from the flywheel.Integrated with the advantages of friction pull plug welding,the IFPPW,free from back anvil,is considered as a promising technique in repair of termination keyhole of bobbin tool friction stir welding and point-like defects in aluminum alloy welding.

Studies on the effect of weld defect on the fatigue behavior of welded structures

Structural integrity isstated as the science and technology of margin between safety and disaster. Systematic prediction of structural integrity of critical structures such ascombustion chambers,pressure vessels,nuclear reactor components,boilers etc.,ensures the human safety,environmental protection,and the economical considerations.The present work aims at prediction of fatigue behaviour of symmetric structures like pressure vessels in the presence of common welding defects such as lack of fusion( LOF),lack of penetration( LOP) and porosity.A ring type specimen which replicates the stress pattern in thepressure vessel is considered for the study of severity of weld imperfections. Initial dimensions of weld defects are arrived by performing NDT inspection.Crack growth analysis is carried out to determine the remaining life of the welded joint with defects.

A fast and adaptive method for automatic weld defect detection in various real-time X-ray imaging systems

A first and effective method is proposed to detect weld deject adaptively in various Dypes of real-time X-ray images obtained in different conditions. After weld extraction and noise reduction, a proper template of median filter is used to estimate the weld background. After the weld background is subtracted from the original image, an adaptite threshold segmentation algorithm is proposed to obtain the binary image, and then the morphological close and open operation, labeling algorithm and fids＇e alarm eliminating algorithm are applied to pracess the binary image to obtain the defect, ct detection result. At last, a fast realization procedure jbr proposed method is developed. The proposed method is tested in real-time X-ray image,s obtairted in different X-ray imaging sutems. Experiment results show that the proposed method is effective to detect low contrast weld dejects with few .false alarms and is adaptive to various types of real-time X-ray imaging systems.

Effect of undercut defect on deformation behavior TC4 titanium alloy laser welded butt joint under static tensile loading

By measuring and analyzing infrared thermal image of the specimen in static load tensile test process, it was studied that the influence of the undercut defects and double-sided dressing method on the deformation behavior of the laser welded joint specimens of TC4 titanium alloy. The results showed that for the unmodified specimens, the yield phenomenon occurs first in the region of the joint, but the undercut value has an effect on the stress and strain of starting to yield phenomenon, and a great effect on the plastic deformation behavior.When the undercut is less than a certain value, the large plastic deformation occurs in the base metal region and the plasticity of the specimen is comparable to that of the base metal, but the larger undercut defect results in a concentrated plastic deformation in the joint region and rapidly failed in this region. But the double-sided dressing specimen is significantly different. The physical yield is no longer concentrated in the joint region, but at the same time occurs in the several regions including joint and the base metal. And the plastic deformation mainly occurs in the base material area, similar to that of the base material.

Application of Support Vector Machine in Weld Defect Detection and Recognition of X-ray Images

Support vector machines（SVM） received wide attention for its excellent ability to learn, it has been applied in many fields. A review of the application of SVM in weld defect detection and recognition of X-ray image is been presented. We will show some commonly used methods of weld defect detection and recognition using SVM, and the advantages and disadvantages of each method will be discussed. SVM appears to be promising in weld defect detection and recognition, but future research is needed before it fully mature in this filed.

ON LINE MONITORING OF BURNING THROUGH FOR SHORT CIRCUIT CO_2 ARC WELDING BASED ON THE SELF-ORGANIZE FEATURE MAP NEURAL NETWORKS

A method for automatic detection of burning through of short circuit CO 2 arc welding is presented. It is based on the extraction of arc signal features as well as classification of the obtained features using self organize feature map(SOM) neural networks in order to get the weld quality information, for example, to determine if there is defect in the product. This is important for the on line monitoring of weld quality especially in robotic welding and lay the foundation for the further real time control of weld quality.

Numerical simulation of mechanical properties of straight pipe and elbow during in-service welding

Elbows are the most vulnerable parts in pipeline network systems. The residual stress for in-service welding repair has significant impacts on the mechanical properties of straight pipes and elbows. In this paper,the thermal elastic-plastic finite element method is employed to investigate the mechanical field during the in-service welding. The prediction of residual stress and deformation in the straight pipe and elbow is performed based on the validation of the numerical models. And the effects of the curvature radius and defects on the elbow are investigated. The results show that the residual stress distribution is uneven along various directions after welding. And the mechanical properties of the elbow decrease when the curvature radius is small. Compared to the intact elbow,the residual stress of the elbow with defects concentrates in the defective area. The depth of defect is the main factors affecting the mechanical properties of the elbow. A systematic analysis of the mechanical properties of straight pipes and elbows is proposed to provide guidance to the in-service welding.

Contrast Correction Using Hybrid Statistical Enhancement on Weld Defect Images

Luminosity and contrast variation problems are among the most challenging tasks in the image processing field,significantly improving image quality.Enhancement is implemented by adjusting the dark or bright intensity to improve the quality of the images and increase the segmentation performance.Recently,numerous methods had been proposed to normalise the luminosity and contrast variation.A new approach based on a direct technique using statistical data known as Hybrid Statistical Enhancement(HSE)is presented in this study.TheHSE method uses themean and standard deviation of a local and global neighbourhood and classified the pixel into three groups;the foreground,border,and problematic region(contrast&luminosity).The datasets,namely weld defect images,were utilised to demonstrate the effectiveness of the HSE method.The results from the visual and objective aspects showed that the HSE method could normalise the luminosity and enhance the contrast variation problem effectively.The proposed method was compared to the two(2)populor enhancement methods which is Homomorphic Filter(HF)and Difference of Gaussian(DoG).To prove the HSE effectiveness,a few image quality assessments were presented,and the results were discussed.The HSE method achieved a better result compared to the other methods,which are Signal Noise Ratio(8.920),Standard Deviation(18.588)and Absolute Mean Brightness Error(9.356).In conclusion,implementing the HSE method has produced an effective and efficient result for background correction and quality images improvement.