To solve the problem of low detection accuracy for complex weld defects,the paper proposes a weld defects detection method based on improved YOLOv5s.To enhance the ability to focus on key information in feature maps,t...To solve the problem of low detection accuracy for complex weld defects,the paper proposes a weld defects detection method based on improved YOLOv5s.To enhance the ability to focus on key information in feature maps,the scSE attention mechanism is intro-duced into the backbone network of YOLOv5s.A Fusion-Block module and additional layers are added to the neck network of YOLOv5s to improve the effect of feature fusion,which is to meet the needs of complex object detection.To reduce the computation-al complexity of the model,the C3Ghost module is used to replace the CSP2_1 module in the neck network of YOLOv5s.The scSE-ASFF module is constructed and inserted between the neck network and the prediction end,which is to realize the fusion of features between the different layers.To address the issue of imbalanced sample quality in the dataset and improve the regression speed and accuracy of the loss function,the CIoU loss function in the YOLOv5s model is replaced with the Focal-EIoU loss function.Finally,ex-periments are conducted based on the collected weld defect dataset to verify the feasibility of the improved YOLOv5s for weld defects detection.The experimental results show that the precision and mAP of the improved YOLOv5s in detecting complex weld defects are as high as 83.4%and 76.1%,respectively,which are 2.5%and 7.6%higher than the traditional YOLOv5s model.The proposed weld defects detection method based on the improved YOLOv5s in this paper can effectively solve the problem of low weld defects detection accuracy.展开更多
The visual automatic detection method based on artificial intelligence has attracted more and more attention. In order to improve the performance of weld nondestructive defect detection,we propose DRepDet(Dilated RepP...The visual automatic detection method based on artificial intelligence has attracted more and more attention. In order to improve the performance of weld nondestructive defect detection,we propose DRepDet(Dilated RepPoints Detector). First, we analyze the weld defect dataset in detail and summarize the distribution characteristics of weld defect data, that is, the defect scale is very different and the aspect ratio distribution range is large. Second, according to the distribution characteristics of defect data, we design DResBlock module, and introduce dilated convolution with different dilated rates in the process of feature extraction to expand the receptive field and improve the detection performance of large-scale defects. Based on DResBlock and anchor-free detection framework RepPoints, we design DRepDet. Extensive experiments show that our proposed detector can detect 7 types of defects. When using combined dilated rate convolution network in detection, the AP50 and Recall50 of big defects are improved by 3.1% and 3.3% respectively, while the performance of small defects is not affected, almost the same or slightly improved. The final performance of the whole network is improved a large margin,with 6% AP50 and 4.2% Recall50 compared with Cascade RCNN and 1.4% AP50 and 2.9% Recall50 compared with RepPoints.展开更多
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 me...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.展开更多
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 met...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.展开更多
The quality of rebar welds directly impacts the overall service performance of highway infrastructure.However,current assessments of weld appearance quality primarily rely on traditional inspection methods such as man...The quality of rebar welds directly impacts the overall service performance of highway infrastructure.However,current assessments of weld appearance quality primarily rely on traditional inspection methods such as manual visual inspection,which suffer from significant limitations in accuracy,reliability,and efficiency.Given the increasing demand for safety performance inspections of highway infrastructure in China,traditional methods struggle to meet modern rapid inspection requirements.Therefore,this study proposes the design of a portable,non-destructive inspection device for rebar weld appearance,utilizing visible light vision and line-structured light 3D scanning technology.The device is equipped with an STM32 master control chip to manage encoder reading,scanning laser control,ring fill light,industrial camera synchronization,image acquisition,and serial port command transmission.Additionally,a weld image processing and detection software system was developed to receive,store,and identify weld defects.A field inspection prototype was created and subjected to various defect weld detection experiments in a laboratory setting.Experimental results demonstrate that the device can accurately measure weld parameters by acquiring multimodal images,fulfilling defect detection requirements.The device features high detection accuracy,portability,and user-friendliness,making it significant for the objective inspection and evaluation of rebar weld appearance and welding quality.展开更多
With von Mises yield criterion,the loading range of Net Section Collapse(NSC) Criteria is extended from combined tension and bending loadings to combined bending,torsion and internal pressure loadings.A new theoretica...With von Mises yield criterion,the loading range of Net Section Collapse(NSC) Criteria is extended from combined tension and bending loadings to combined bending,torsion and internal pressure loadings.A new theoretical analyzing method of plastic limit load for pressure pipe with incomplete welding defects based on the extended NSC Criteria is presented and the correlative formulas are deduced,the influences of pipe curvature,circumferential length and depth of incomplete welding defects on the plastic limit load of pressure pipe are considered as well in this method.Meanwhile,according to the orthogonal experimental design method,the plastic limit loads are calculated by the finite element method and compared with the theoretical values.The results show that the expressions of plastic limit load of pressure pipe with incomplete welding defects under bending,torsion and internal pressure based on extended NSC criteria are reliable.The study provides an important theoretical basis for the establishment of safety assessment measure towards pressure pipe with incomplete welding defects.展开更多
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 p...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.展开更多
A series of experiments was performed to investigate the weldability of steel used in an aged bridge.A steel material used in an aged railway bridge constructed in 1912 was extracted for this investigation.The chemica...A series of experiments was performed to investigate the weldability of steel used in an aged bridge.A steel material used in an aged railway bridge constructed in 1912 was extracted for this investigation.The chemical compositions of this steel were suitable for welding.However,the aged steel contained much sulfur.Cruciform welded joints were fabricated with this aged steel.Welding defects or cracks were not observed in the joints.The Vickers hardness test on the welded part did not confirm extreme hardening or softening.After yielding by the static tensile test,the cruciform joints were fractured at the welded parts.One of the specimens was fractured in the middle of the thickness of the aged steel.The Sulfur contained in the aged steel might cause this type of fracture.The results show that there may be a risk of brittle fracture not only from the welded part but also from the base metal.The chemical compositions of aged steel must be analyzed when repair welding is applied to the steel.展开更多
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 analys...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.展开更多
With the increase of surface assembly density and the rapid development of surface mount technology (SMT), electronic products tend to be miniaturized and integrated. The welding quality and welding technology of surf...With the increase of surface assembly density and the rapid development of surface mount technology (SMT), electronic products tend to be miniaturized and integrated. The welding quality and welding technology of surface mount components have attracted more and more attention. Reflow processing technology is a comprehensive scientific research. There are many reasons for the welding quality defects of each electronic component. Any material performance change or unreasonable processing parameters may lead to hidden welding quality defects. Therefore, in the specific production process, it is necessary to make in-depth analysis of practical problems and constantly improve the reflow soldering process, so as to improve the reflow soldering quality, ensure the up-to-standard rate of new products and improve the stability of electronic products and commodity quality.展开更多
Multi-pass TIG welding was conducted on plates(15×300×180 mm^(3))of aluminum alloy Al-5083 that usually serves as the component material in structural applications such as cryogenics and chemical processing ...Multi-pass TIG welding was conducted on plates(15×300×180 mm^(3))of aluminum alloy Al-5083 that usually serves as the component material in structural applications such as cryogenics and chemical processing industries.Porosity formation and solidification cracking are the most common defects when TIG welding Al-5083 alloy,which is sensitive to the welding heat input.In the experiment,the heat input was varied from 0.89 kJ/mm to 5 kJ/mm designed by the combination of welding torch travel speed and welding current.Tensile,micro-Vicker hardness and Charpy impact tests were executed to witness the impetus response of heat input on the mechanical properties of the joints.Radiographic inspection was performed to assess the joint’s quality and welding defects.The results show that all the specimens displayed inferior mechanical properties as compared to the base alloy.It was established that porosity was progressively abridged by the increase of heat input.The results also clinched that the use of medium heat input(1-2 kJ/mm)offered the best mechanical properties by eradicating welding defects,in which only about 18.26% of strength was lost.The yield strength of all the welded specimens remained unaffected indica ted no influence of heat input.Partially melted zone(PMZ)width also affected by heat input,which became widened with the increase of heat input.The grain size of PMZ was found to be coarser than the respective grain size in the fusion zone.Charpy impact testing revealed that the absorbed energy by low heat input specimen(welded at high speed)was greater than that of high heat input(welded at low speed)because of low porosity and the formation of equiaxed grains which induce better impact toughness.Cryogenic(-196℃)impact testing was also performed and the results corroborate that impact properties under the cryogenic environment revealed no appreciable change after welding at designated heat input.Finally,Macro and micro fractured surfaces of tensile and impact specimens were analyzed using Stereo and Scanning Electron Microscopy(SEM),which have supported the experimental findings.展开更多
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 ...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.展开更多
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 me...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.展开更多
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 anisotropi...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.展开更多
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...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.展开更多
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 ...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.展开更多
Welded joint impact performances of low-alloy carbon steel plates welded by full-automatic gas metal arc welding （GMAW） were evaluated. To clarity the effect of impact temperature on impact properties of weld metal ...Welded joint impact performances of low-alloy carbon steel plates welded by full-automatic gas metal arc welding （GMAW） were evaluated. To clarity the effect of impact temperature on impact properties of weld metal （WM） and heat- affected zone （ HAZ）, Charpy V impact tests at different temperatures and fracture surface analysis were carried out. The Charpy V impact energy decreases with the decreasing test temperature both for the WM and HAZ, while the proportion of crystal zone on WM and HAZ impact fracture surface increases with the decreasing test temperature. Research results indicate that the welding defects （void and slag） make the impact energy of WM more scattered and lower than that of HAZ.展开更多
In this paper,a finite element model with girth weld defects considering crack tip singularity was established in order to facilitate the accurate and rapid safety assessment on girth weld defects of long distance gas...In this paper,a finite element model with girth weld defects considering crack tip singularity was established in order to facilitate the accurate and rapid safety assessment on girth weld defects of long distance gas Transmission pipeline.Then the J-integral of girth weld cracks in pipes with different defect sizes was calculated,and the influence of weld matching coefficient and material hardening index on J-integral is analyzed.Furthermore,the influence factors of limit load of pipeline with girth weld defects based on J-integral theory are studied.Based on this,the engineering calculation formula which can calculate J-integral and limit load rapidly in the situations with specific matching coefficient and material hardening index was proposed.And the following research results were obtained.First,the engineering calculation formula based on the fitting of finite element calculation results has high accuracy,which can calculate the J-integral of defects in a large geometric range and the limit load of pipelines with girth weld cracks.Second,the J-integral of cracks in pipes with girth weld defects is closely related to defect size,material properties and weld matching coefficient,and the limit load of pipes with defects decreases as the crack size increases and increases as the material hardening index increases.Third,for the X80 pipes with surface cracks at the centerline of the girth weld,the load carrying capacity of the pipes with low-strength matched weld are lower than that with high-strength or equivalent-matched weld.In conclusion,the research results can be used as reference for the safety evaluation and integrity management of in-service gas pipelines.展开更多
With more application of welding technology in important structures more attention was paid to the evaluation of the safety of welded structures, the life prediction and decision to repair the welded structures. Based...With more application of welding technology in important structures more attention was paid to the evaluation of the safety of welded structures, the life prediction and decision to repair the welded structures. Based on material fracture mechanism and Chinese standard of safety evaluations of pressure vessels, an expert system was developed to evaluate the safety of welded pressure vessels. The system can analyze the weld defects in a pressure vessel, convert different kinds of defects into equivalent cracks and obtain their equivalent sizes. Furthermore, the system can calculate the stress and strain in the positions of weld defects and make decision on whether the defects are tolerable or not according to the code. When it is tolerable, the system will calculate the safety margin. The fatigue life can be predicted if the defects undergo fatigue load too. Moreover, data bases are built for storing mechanical properties of material and evaluated results.展开更多
The cause of the premature failure of 304 stainless steel tube heat exchanger was investigated.The unique skeleton structure inside the leakage point reveals that this is a new damage mechanism caused by a δ+γ two-p...The cause of the premature failure of 304 stainless steel tube heat exchanger was investigated.The unique skeleton structure inside the leakage point reveals that this is a new damage mechanism caused by a δ+γ two-phase structure and crevice corrosion.The three-dimensional structure of the leakage point was demonstrated using X-ray diffraction topography.The results of scanning electron microscope examination show the microstructure of the weld to be columnar and dendritic.It is found by electron probe microscope analysis and transmission electron microscopy that columnar dendrites consisted of γ-dendrite and an amount of δ-ferrite phases at the dendrite trunk.Simulated corrosion test results confirmed that the corrosion medium was the chloride ion.Crevice corrosion of chloride ions occurred at weld defects on the inner wall thus forming a concentration cell.Grains of columnar dendrites were then corroded by chloride ions and δ-ferrite phases on the grain boundaries were retained,which formed the particular skeleton corrosion structure.As a result,it led to leakage when the corrosion of weld occurred from the inner wall to the outer wall.展开更多
基金supported by Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.KYCX24_4084).
文摘To solve the problem of low detection accuracy for complex weld defects,the paper proposes a weld defects detection method based on improved YOLOv5s.To enhance the ability to focus on key information in feature maps,the scSE attention mechanism is intro-duced into the backbone network of YOLOv5s.A Fusion-Block module and additional layers are added to the neck network of YOLOv5s to improve the effect of feature fusion,which is to meet the needs of complex object detection.To reduce the computation-al complexity of the model,the C3Ghost module is used to replace the CSP2_1 module in the neck network of YOLOv5s.The scSE-ASFF module is constructed and inserted between the neck network and the prediction end,which is to realize the fusion of features between the different layers.To address the issue of imbalanced sample quality in the dataset and improve the regression speed and accuracy of the loss function,the CIoU loss function in the YOLOv5s model is replaced with the Focal-EIoU loss function.Finally,ex-periments are conducted based on the collected weld defect dataset to verify the feasibility of the improved YOLOv5s for weld defects detection.The experimental results show that the precision and mAP of the improved YOLOv5s in detecting complex weld defects are as high as 83.4%and 76.1%,respectively,which are 2.5%and 7.6%higher than the traditional YOLOv5s model.The proposed weld defects detection method based on the improved YOLOv5s in this paper can effectively solve the problem of low weld defects detection accuracy.
文摘The visual automatic detection method based on artificial intelligence has attracted more and more attention. In order to improve the performance of weld nondestructive defect detection,we propose DRepDet(Dilated RepPoints Detector). First, we analyze the weld defect dataset in detail and summarize the distribution characteristics of weld defect data, that is, the defect scale is very different and the aspect ratio distribution range is large. Second, according to the distribution characteristics of defect data, we design DResBlock module, and introduce dilated convolution with different dilated rates in the process of feature extraction to expand the receptive field and improve the detection performance of large-scale defects. Based on DResBlock and anchor-free detection framework RepPoints, we design DRepDet. Extensive experiments show that our proposed detector can detect 7 types of defects. When using combined dilated rate convolution network in detection, the AP50 and Recall50 of big defects are improved by 3.1% and 3.3% respectively, while the performance of small defects is not affected, almost the same or slightly improved. The final performance of the whole network is improved a large margin,with 6% AP50 and 4.2% Recall50 compared with Cascade RCNN and 1.4% AP50 and 2.9% Recall50 compared with RepPoints.
基金supported by the National Key Natural Science Foundation of China(Grant No.50739004)the National Natural Science Foundation of China(Grant Nos.51009093 and 51379005)
文摘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.
基金support of Shanghai Pinlan Data Technology Co.,Ltd.,and Open Fund of Shanghai Key Laboratory of Engineering Structure Safety,SRIBS(No.2021-KF-06).
文摘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.
基金Supported by the Central Public-Interest Scientific Institution Basal Research Fund(2023-9062)the Transport Power Pilot Project(2021-C334)。
文摘The quality of rebar welds directly impacts the overall service performance of highway infrastructure.However,current assessments of weld appearance quality primarily rely on traditional inspection methods such as manual visual inspection,which suffer from significant limitations in accuracy,reliability,and efficiency.Given the increasing demand for safety performance inspections of highway infrastructure in China,traditional methods struggle to meet modern rapid inspection requirements.Therefore,this study proposes the design of a portable,non-destructive inspection device for rebar weld appearance,utilizing visible light vision and line-structured light 3D scanning technology.The device is equipped with an STM32 master control chip to manage encoder reading,scanning laser control,ring fill light,industrial camera synchronization,image acquisition,and serial port command transmission.Additionally,a weld image processing and detection software system was developed to receive,store,and identify weld defects.A field inspection prototype was created and subjected to various defect weld detection experiments in a laboratory setting.Experimental results demonstrate that the device can accurately measure weld parameters by acquiring multimodal images,fulfilling defect detection requirements.The device features high detection accuracy,portability,and user-friendliness,making it significant for the objective inspection and evaluation of rebar weld appearance and welding quality.
基金Project (No. X106871) supported by the Natural Science Foundation of Zhejiang Province,China
文摘With von Mises yield criterion,the loading range of Net Section Collapse(NSC) Criteria is extended from combined tension and bending loadings to combined bending,torsion and internal pressure loadings.A new theoretical analyzing method of plastic limit load for pressure pipe with incomplete welding defects based on the extended NSC Criteria is presented and the correlative formulas are deduced,the influences of pipe curvature,circumferential length and depth of incomplete welding defects on the plastic limit load of pressure pipe are considered as well in this method.Meanwhile,according to the orthogonal experimental design method,the plastic limit loads are calculated by the finite element method and compared with the theoretical values.The results show that the expressions of plastic limit load of pressure pipe with incomplete welding defects under bending,torsion and internal pressure based on extended NSC criteria are reliable.The study provides an important theoretical basis for the establishment of safety assessment measure towards pressure pipe with incomplete welding defects.
文摘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.
文摘A series of experiments was performed to investigate the weldability of steel used in an aged bridge.A steel material used in an aged railway bridge constructed in 1912 was extracted for this investigation.The chemical compositions of this steel were suitable for welding.However,the aged steel contained much sulfur.Cruciform welded joints were fabricated with this aged steel.Welding defects or cracks were not observed in the joints.The Vickers hardness test on the welded part did not confirm extreme hardening or softening.After yielding by the static tensile test,the cruciform joints were fractured at the welded parts.One of the specimens was fractured in the middle of the thickness of the aged steel.The Sulfur contained in the aged steel might cause this type of fracture.The results show that there may be a risk of brittle fracture not only from the welded part but also from the base metal.The chemical compositions of aged steel must be analyzed when repair welding is applied to the steel.
基金This work was supported by Tianjin Natural Science Foundation （No. 11JCYBJC06000） and Specialized Research Fund for the Doctoral Program of Higher Education of China （No. 20100032120019）.
文摘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.
文摘With the increase of surface assembly density and the rapid development of surface mount technology (SMT), electronic products tend to be miniaturized and integrated. The welding quality and welding technology of surface mount components have attracted more and more attention. Reflow processing technology is a comprehensive scientific research. There are many reasons for the welding quality defects of each electronic component. Any material performance change or unreasonable processing parameters may lead to hidden welding quality defects. Therefore, in the specific production process, it is necessary to make in-depth analysis of practical problems and constantly improve the reflow soldering process, so as to improve the reflow soldering quality, ensure the up-to-standard rate of new products and improve the stability of electronic products and commodity quality.
文摘Multi-pass TIG welding was conducted on plates(15×300×180 mm^(3))of aluminum alloy Al-5083 that usually serves as the component material in structural applications such as cryogenics and chemical processing industries.Porosity formation and solidification cracking are the most common defects when TIG welding Al-5083 alloy,which is sensitive to the welding heat input.In the experiment,the heat input was varied from 0.89 kJ/mm to 5 kJ/mm designed by the combination of welding torch travel speed and welding current.Tensile,micro-Vicker hardness and Charpy impact tests were executed to witness the impetus response of heat input on the mechanical properties of the joints.Radiographic inspection was performed to assess the joint’s quality and welding defects.The results show that all the specimens displayed inferior mechanical properties as compared to the base alloy.It was established that porosity was progressively abridged by the increase of heat input.The results also clinched that the use of medium heat input(1-2 kJ/mm)offered the best mechanical properties by eradicating welding defects,in which only about 18.26% of strength was lost.The yield strength of all the welded specimens remained unaffected indica ted no influence of heat input.Partially melted zone(PMZ)width also affected by heat input,which became widened with the increase of heat input.The grain size of PMZ was found to be coarser than the respective grain size in the fusion zone.Charpy impact testing revealed that the absorbed energy by low heat input specimen(welded at high speed)was greater than that of high heat input(welded at low speed)because of low porosity and the formation of equiaxed grains which induce better impact toughness.Cryogenic(-196℃)impact testing was also performed and the results corroborate that impact properties under the cryogenic environment revealed no appreciable change after welding at designated heat input.Finally,Macro and micro fractured surfaces of tensile and impact specimens were analyzed using Stereo and Scanning Electron Microscopy(SEM),which have supported the experimental findings.
基金supported by Special Program for Trend Setting Research of Jiangsu Province(Grant No.BY2015065-07)Research Foundation of Jiangsu Key Laboratory of Recycling and Reusing Technology for Mechanical and Electronic Products(Grant No.RRME-KF1605)
文摘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.
文摘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.
基金Supported by the National Natural Science Foundation of China(No.60872065)Open Foundation of State Key Laboratory of Advanced Welding and Connection,Harbin Institute of Technology(AWPT-M04)Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘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.
文摘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.
文摘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.
文摘Welded joint impact performances of low-alloy carbon steel plates welded by full-automatic gas metal arc welding （GMAW） were evaluated. To clarity the effect of impact temperature on impact properties of weld metal （WM） and heat- affected zone （ HAZ）, Charpy V impact tests at different temperatures and fracture surface analysis were carried out. The Charpy V impact energy decreases with the decreasing test temperature both for the WM and HAZ, while the proportion of crystal zone on WM and HAZ impact fracture surface increases with the decreasing test temperature. Research results indicate that the welding defects （void and slag） make the impact energy of WM more scattered and lower than that of HAZ.
基金Project supported by the National Key R&D Program of China“Integrity Evaluation Technology of Oil/Gas Pipeline and Storage and Transportation Facilities”(No.:2016YFC0802105)National Science and Technology Major Project“Development Demonstration Project of Large Carbonate Gas Field in Sichuan Basin-Key Technology Research and Solutions of HSE Guarantee in Large Sour Gas Field Development”(No.:2016ZX05052).
文摘In this paper,a finite element model with girth weld defects considering crack tip singularity was established in order to facilitate the accurate and rapid safety assessment on girth weld defects of long distance gas Transmission pipeline.Then the J-integral of girth weld cracks in pipes with different defect sizes was calculated,and the influence of weld matching coefficient and material hardening index on J-integral is analyzed.Furthermore,the influence factors of limit load of pipeline with girth weld defects based on J-integral theory are studied.Based on this,the engineering calculation formula which can calculate J-integral and limit load rapidly in the situations with specific matching coefficient and material hardening index was proposed.And the following research results were obtained.First,the engineering calculation formula based on the fitting of finite element calculation results has high accuracy,which can calculate the J-integral of defects in a large geometric range and the limit load of pipelines with girth weld cracks.Second,the J-integral of cracks in pipes with girth weld defects is closely related to defect size,material properties and weld matching coefficient,and the limit load of pipes with defects decreases as the crack size increases and increases as the material hardening index increases.Third,for the X80 pipes with surface cracks at the centerline of the girth weld,the load carrying capacity of the pipes with low-strength matched weld are lower than that with high-strength or equivalent-matched weld.In conclusion,the research results can be used as reference for the safety evaluation and integrity management of in-service gas pipelines.
基金The research is supported by China Postdoctoral Science Foundation （No. 20080430129 ） and National Key Technology R＆D Program （ No. 2007BAE07 B07 ）.
文摘With more application of welding technology in important structures more attention was paid to the evaluation of the safety of welded structures, the life prediction and decision to repair the welded structures. Based on material fracture mechanism and Chinese standard of safety evaluations of pressure vessels, an expert system was developed to evaluate the safety of welded pressure vessels. The system can analyze the weld defects in a pressure vessel, convert different kinds of defects into equivalent cracks and obtain their equivalent sizes. Furthermore, the system can calculate the stress and strain in the positions of weld defects and make decision on whether the defects are tolerable or not according to the code. When it is tolerable, the system will calculate the safety margin. The fatigue life can be predicted if the defects undergo fatigue load too. Moreover, data bases are built for storing mechanical properties of material and evaluated results.
文摘The cause of the premature failure of 304 stainless steel tube heat exchanger was investigated.The unique skeleton structure inside the leakage point reveals that this is a new damage mechanism caused by a δ+γ two-phase structure and crevice corrosion.The three-dimensional structure of the leakage point was demonstrated using X-ray diffraction topography.The results of scanning electron microscope examination show the microstructure of the weld to be columnar and dendritic.It is found by electron probe microscope analysis and transmission electron microscopy that columnar dendrites consisted of γ-dendrite and an amount of δ-ferrite phases at the dendrite trunk.Simulated corrosion test results confirmed that the corrosion medium was the chloride ion.Crevice corrosion of chloride ions occurred at weld defects on the inner wall thus forming a concentration cell.Grains of columnar dendrites were then corroded by chloride ions and δ-ferrite phases on the grain boundaries were retained,which formed the particular skeleton corrosion structure.As a result,it led to leakage when the corrosion of weld occurred from the inner wall to the outer wall.
