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2020 | Book

The Review of Spectrum Detection and Ultrasonic Vibration Control of Porosity Defects in Aluminum Alloy Welding Read chapter Read first chapter

Transactions on Intelligent Welding Manufacturing

Volume III No. 3 2019

Editors: Prof. Shanben Chen, Prof. Yuming Zhang, Dr. Zhili Feng

Publisher: Springer Singapore

Book Series : Transactions on Intelligent Welding Manufacturing

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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About this book

The primary aim of this volume is to provide researchers and engineers from both academic and industry with up-to-date coverage of new results in the field of robotic welding, intelligent systems and automation. The book is mainly based on papers selected from the 2019 International Workshop on Intelligentized Welding Manufacturing (IWIWM’2019) in USA. The articles show that the intelligentized welding manufacturing (IWM) is becoming an inevitable trend with the intelligentized robotic welding as the key technology. The volume is divided into four logical parts: Intelligent Techniques for Robotic Welding, Sensing of Arc Welding Processing, Modeling and Intelligent Control of Welding Processing, as well as Intelligent Control and its Applications in Engineering.

Table of Contents

Frontmatter

Feature Articles

Frontmatter
The Review of Spectrum Detection and Ultrasonic Vibration Control of Porosity Defects in Aluminum Alloy Welding
Abstract
The porosity defect in aluminum alloy welding is one of the common internal defects in the welding process. The traditional detection method is time-consuming and complex, the equipment requirements are high, and the existing pores are difficult to repair. The arc spectral signal contains a large amount of welding process information. It can be used as a signal for judging the internal porosity defects. The ultrasonic-assisted welding can effectively clean up the internal pores in the molten pool. By combining the two methods, it can realize online detection and feedback control of porosity defects in aluminum alloy welding. In this paper, the research status of pore detection and control methods is reviewed. The development prospect of spectral detection technology and ultrasonic-assisted welding and the advantages compared with the traditional methods are analyzed.
Jingyuan Xu, Shanben Chen

Research Papers

Frontmatter
Microstructure and Mechanical Properties of TC4 Titanium Alloy by Electron Beam Freeform Fabrication
Abstract
Titanium alloy was known as the intelligent metal of the twenty-first century. Its comprehensive mechanical properties were widely used in the high-end equipment manufacturing industries, such as modern aerospace and national defense industries. Especially, more and more experts paid attention to the technology of additive manufacturing technology for titanium alloys at home and abroad. Electron beam freeform fabrication of TC4 titanium alloy is a new generation of high-efficiency, pollution-free, and low-cost rapid prototyping technology. In this paper, TC4 titanium alloy was investigated as the research materials, and it was particular to research on the uniformity of TC4 titanium alloy by electron beam freeform fabrication. The structure was manufactured with controlling the heat input to reveal the microstructural evolution and analyze its mechanical properties. At the same time, the heat treatment was utilized to control the microstructural uniformity for improving its comprehensive mechanical properties.
Wenjun Sun, Liming Ke, Shanlin Wang, Wende Bu
Weld Flaw Recognition with Improved Convolutional Neural Network
Abstract
The simple linear iterative clustering (SLIC) algorithm and the improved exponential linear unit (ELU) activation function are used to construct CNN model for weld flaw detection image recognition. First, the ELU activation function is used in the CNN model to generate better robustness to the input noise when the response gradient disappears. At the same time, the SLIC algorithm is used to perform pixel block processing on image pixels, which increases the proportion of interest regions in the weld flaw detection image and improves the feature extraction ability of the model during training. Through the extraction of the interest region of weld detection image and the establishment of the CNN model described in this paper, the results show that the proposed method has better performance than the traditional convolution neural network in feature extraction, training time, and recognition accuracy of weld flaw detection image.
Ande Hu, Ding Fan, Jiankang Huang, Zhenya Xu
Mask R-CNN-Based Welding Image Object Detection and Dynamic Modelling for WAAM
Abstract
As a new emerging technology, wire arc additive manufacturing (WAAM) has attracted extensive interests from both academia and industry during recent years. WAAM uses welding arc as an energy source to fuse metal wire and deposit layer by layer, which provides the advantages of freeform deposition. In order to improve its manufacture precision, stability and repeatability, it is necessary to develop sensing and control strategy for WAAM process. This research develops a passive visual sensing system for a robotic WAAM system. A new deep learning technique (Mask R-CNN) is proposed to detect and segment the melt pool area, and the width of melt pool can be measured based on the coordinate of the bounding rectangle. The pseudo-random ternary (PRT) signals were used to stimulate the WAAM process, and the corresponding width can be measured by the Mask R-CNN. Based on the width data and corresponding PRT input, a dynamic model of adaptive neuro-fuzzy inference system was built for the WAAM process.
Chunyang Xia, Zengxi Pan, Shiyu Zhang, Joseph Polden, Huijun Li, Yanling Xu, Shanben Chen
Research on Fuzzy Comprehensive Evaluation of Seam Quality in Double-Wire Double-Pulsed MIG High-Speed Welding
Abstract
In this paper, quantitative evaluation method of the welding stability and quality based on current sample entropy and current probability density distribution function were explored. A comprehensive evaluation method of welding quality based on fuzzy logic inference was established, and the method was applied to double wire double pulse. The MIG high-speed welding process stability and weld quality were quantitatively evaluated. The current sample entropy algorithm was used to analyze the effects of twin-wire welding speed, waveform modulation mode, and low frequency on welding stability. From the probability density distribution function, the front and back wire current concentration K was selected as the stability index of double-wire welding. The effects of welding speed, waveform modulation mode, and low frequency on welding stability were studied. Two quantitative indexes of current sample entropy and current concentration were selected to establish a fuzzy logic quantitative evaluation system for double-wire high-speed welding seam quality. The test results show that the correctness rate of the fuzzy logical comprehensive assessment is 85.7%, and the evaluation results obtained by the fuzzy logic inference evaluation system are close to the evaluation results by the experts.
Huangsheng Xie, Zhihe Fu, Jiaxiang Xue, Yu Hu
Welding Deviation Extraction during K-TIG Welding Based on K-Means Clustering
Abstract
During K-TIG welding, due to the strong arc and the narrow seam, it is difficult to accurately identify the deviation of the welding, which would affect the K-TIG automatic welding. In this paper, a novel welding deviation visual inspection method is proposed. A high dynamic range camera is used to capture the welding images. Then, K-means-based image segmentation algorithm is used to automatically divide an image into arc region and seam area. An optimal path method is proposed to extract the feature points on the electrodes from the arc region image and get the position of the electrode tip points. The seam area is processed by a refinement algorithm to obtain the weld position, and finally, the deviation between the electrode tip and the seam is obtained. The experiment proves that the proposed algorithm can realize the automatic identification of K-TIG welding deviation.
Baori Zhang, Yonghua Shi
Thermal Characteristics of Narrow Gap GMA Welding at Vertical Position with Arc Swinging and Shifting
Abstract
Research on thermal characteristics is the base for deeply understanding the process of narrow gap–fine wire–gas protection–one pass one layer–arc swinging and shifting–vertical welding. The plane analytic geometry method is adapted to solve the arc speed and welding line energy by analyzing the arc movement path. Based on classic heat source model of double ellipsoid, update of arc center position and orientation is achieved by coordinate transformation. The dynamic evolution of the weld pool under certain conditions is simulated, and thermal cycle curves of single layer and multilayer are extracted. The results show that the line energy of the process is pulsed and alternately assigned to both sides of the side wall, which lead to a narrow coarse-grained heat-affected zone (CGHAZ). The thermal cycle curve of CGHAZ presents the double characteristic of multi-peak, dwell time at high temperature is short, and cooling rate at low temperature is low. In addition, the weakest CGHAZ in the joint transforms into several micro-zones along the thickness of the weld, and the area ratio of reheated CGHAZ by normalizing, incomplete normalizing, and tempering is 3:2:5. If the thickness of the welding layer is properly controlled, the original CGHAZ of base metal are subjected to the grain refinement under the different layer welding thermal cycles conditions.
Hu Lan, Huajun Zhang, Jinjun Shao, Gang Li, Rui Pan, Bin Wang
Kinematics Analysis of Mechanical Arm of a Ten-Joint Tunnel Arch Installation Trolley
Abstract
At present, the installation of steel arch centering is still completed by manual operation of trolley mechanical arm with low degree of automation. Kinematics analysis is one of the key technologies to realize automatic installation of supporting steel arch for multi-joint and heavy-load arch-centering manipulator. Through the D–H method, the link coordinate system of the trolley manipulator was established, the transformation matrix between the joints was obtained, the forward kinematics model was established, and the initial position and pose of the grab at the end of the manipulator were determined. According to the pose requirements of arch installation for the manipulator end grips, the Jacobian matrix was reconstructed, the inverse kinematics algorithm was written, and the inverse kinematics solution of the manipulator was obtained. On this basis, the motion path planning of the manipulator was completed, and the automatics positioning of the manipulator end grips was realized. The forward and inverse kinematics algorithms of the manipulator were verified by the simulated tunnel test, and the test results show that the accuracy of arch installation meets the requirements.
Long Xue, Junfen Huang, Jiqiang Huang, Kang Huang, Yingyu Cao, Wei Fang
Research of Multi-source Information Sensing Technology in Defect Detection on Automatic Welding
Abstract
As one of the key technologies of large-scale machinery construction, welding technology has been attached great importance to by shipbuilding enterprises all over the world. With the general progress and development of welding intelligent automation technology, most of the welding work in simple operating environment is gradually transformed from manual operation to welding robot. Through the integration of automation to operate it, so the detection of welding quality is also an important part. Because of the complex physical and chemical reactions in the welding process, a variety of information sources can be extracted for analysis and identification. In the process of robot welding, the accurate extraction and analysis of the effective feature information in the dynamic process of welding are an effective guarantee for the automation and intelligence of welding. In this part, the detection of weld defects can help the welding quality from another aspect. Through the real-time monitoring and analysis of defects, the corresponding features can be extracted to the penetration of the dynamic process of welding. Status provides reference significance.
Dapeng Yang, Junfeng Han, Na Lv, Zhiqiang Feng

Short Papers and Technical Notes

Frontmatter
Research on Resonant High-Voltage Plasma Power Supply
Abstract
In view of the shortcomings of traditional high-voltage plasma power supply, such as large volume, complicated circuit, and poor control precision, this paper proposes a high-voltage plasma power supply with embedded control system. In this work, the working principle of circuit is firstly introduced, and a main circuit model with MATLAB/Simulink is built so as to analyze the working process in circuit. In addition, the structure of control system and the programmed control flowchart are addressed in detail. Finally, a prototype with output voltage of 15 kV and output current of 200 mA is built to verify the validation. The result shows that the experimental waveform is consistent with the simulation waveform, which can meet the actual requirements.
Zixin Hu, Song Yuan, Zhuoran Wang, Min Zeng
Backmatter
Metadata
Title
Transactions on Intelligent Welding Manufacturing
Editors
Prof. Shanben Chen
Prof. Yuming Zhang
Dr. Zhili Feng
Copyright Year
2020
Publisher
Springer Singapore
Electronic ISBN
978-981-15-7215-9
Print ISBN
978-981-15-7214-2
DOI
https://doi.org/10.1007/978-981-15-7215-9