scholarly journals FEM Analysis of the Welding Seams Geometry in Case of Fillet Welds

2021 ◽  
Vol 343 ◽  
pp. 03006
Author(s):  
Claudiu Babiş ◽  
Andrei Dimitrescu ◽  
Ana Maria Alecusan ◽  
Marcela Babiş
Keyword(s):  
Weld Seam ◽  
Welding Process ◽  
Fem Analysis ◽  
Geometric Shape ◽  
Fillet Welds ◽  
Mechanical Resistance ◽  
Filler Materials ◽  
Welding Seam ◽  
Welding Regime ◽  
Materials Used

The role of the welding seam is to achieve the non-removable joint between two or more parts. In principle, three geometric profiles of the welding seams can be obtained: straight profile; concave profile and convex profile. In practice, this geometric shape of the weld seam profile is very important, both in terms of the resistance of the joint to static stresses and in terms of its fatigue life. There are many factors that can influence the geometric shape of the weld seam: the welding process; welding regime; the nature of the filler materials used, the rehabilitation techniques applied and others. Often, this geometric shape of the weld bead is neglected, which is particularly dangerous due to the fact that an improper geometric shape can generate low mechanical strength in static loads or poor fatigue strength in variable loads. An optimum of the geometric configuration of the welding must be found, which reconciles both situations: the mechanical resistance in case of static stresses and also the fatigue resistance in case of variable loads. In this paper, an analysis will be made with finite elements for the straight and convex profile of the welding seams in the case of fillet welds subjected to fatigue. Several elements will be considered such as: damage; total deformation; fatigue sensitivity versus loading history; equivalent von Misses stress; safety factor.

Classification of Weld Defects Based on Convolution Neural Network

2021 ◽  
pp. 23-36
Author(s):  
A.I. Gavrilov ◽  
M.Tr. Do
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Convolutional Neural Network ◽  
Weld Seam ◽  
Control Process ◽  
Welding Process ◽  
Optimal Solution ◽  
Automatic Welding ◽  
Welding Seam ◽  
Noise Factors

Automatic welding technology has been widely applied in many industrial fields. It is a complex process with many nonlinear parameters and noise factors affecting weld quality. Therefore, it is necessary to inspect and evaluate the quality of the weld seam during welding process. However, in practice there are many types of welding seam defects, causes and the method of corrections are also different. Therefore, welding seam defects need to be classified to determine the optimal solution for the control process with the best quality. Previously, the welder used his experience to classify visually, or some studies proposed visual classification with image processing algorithms and machine learning. However, it requires a lot of time and accuracy is not high. The paper proposes a convolutional neural network structure to classify images of welding seam defects from automatic welding machines on pipes. Based on comparison with the classification results of some deep machine learning networks such as VGG16, Alexnet, Resnet-50, it shows that the classification accuracy is 99.46 %. Experimental results show that the structure of convolutional neural network is proposed to classify images of weld seam defects have availability and applicability

Investigation of Weld Seam Structures of Tailor Welded Blanks for Hot Stamping

2015 ◽  
Vol 639 ◽  
pp. 235-242 ◽  
Author(s):  
Ralf Kolleck ◽  
Robert Vollmer ◽  
Christian Both ◽  
Arndt Breuer
Keyword(s):  
Mechanical Properties ◽  
Weld Seam ◽  
Hot Stamping ◽  
Fem Analysis ◽  
Body Parts ◽  
Welding Seam ◽  
Press Hardening ◽  
Safety Requirements ◽  
Tailor Welded Blanks ◽  
Testing Tool

Increasing safety requirements for hot stamped structural car body parts are demanding sufficient mechanical properties of integrated welding seams. Especially conventional tailor welded AlSi-coated 22MnB5 sheets are only fulfilling these requirements when ablated before laser welding and thermo-mechanically treated in a correct way. This paper shows a method that evaluates the hot stamping process of tailor welded blanks by press hardening different sheet thicknesses and thickness combinations in a testing tool. Furthermore, appropriate testing methods for the evaluation of mechanical properties of the welding seam are introduced. The results are ultimately compared with a special developed FEM analysis to predict failure cases in future.

Modeling of underwater wet welding process based on visual and arc sensor

2014 ◽  
Vol 41 (3) ◽  
pp. 311-317 ◽  
Author(s):  
Bo Chen ◽  
Jicai Feng
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Weld Seam ◽  
Back Propagation ◽  
Welding Process ◽  
Welding Quality ◽  
Welding Seam ◽  
Content Type ◽  
Underwater Welding ◽  
Underwater Wet Welding

Purpose – The purpose of this paper was to use visual and arc sensors to simultaneously obtain the underwater wet welding information, and a weld seam-forming model was made to predict the weld seam's geometric parameters. It is difficult to obtain a fine welding quality in underwater welding because of the intense disturbances of the water environment. To automatically control the welding quality, the weld seam-forming model should first be established. Thus, the foundation was laid for automatically controlling the underwater welding seam-forming quality. Design/methodology/approach – Visual and arc sensors were used simultaneously to obtain the weld seam image, current and voltage information; then signal algorithms were used to process the information, and the back propagation (BP) neural network was used to model the process. Findings – Experiment results showed that the BP neural network model could precisely predict the weld seam-forming parameters of underwater wet welding. Originality/value – A weld seam-forming model of underwater wet welding process was made; this laid the foundation for establishing a controller for controlling the underwater wet welding process automatically.

scholarly journals Horizontal welding quality control of the CO2 gas shielded welding

2018 ◽  
Vol 207 ◽  
pp. 04006
Author(s):  
Zhi-ling Wang
Keyword(s):  
Weld Seam ◽  
Skill Training ◽  
Welding Process ◽  
Practical Training ◽  
Welding Seam ◽  
Co2 Gas ◽  
Butt Welding ◽  
Operation Process ◽  
Training Topic ◽  
Selection Of

In the process of horizontal butt welding of CO2 gas shielded welding, the molten metal will squat under the effect of its own weight. Therefore, the upper part of the weld seam is very easy to produce undercuts, and the lower part is prone to defects such as welding and unwelding. If the problem is serious, it will cause welding. Seam cannot pass the weld quality test. This article is based on the welding skill training topic “CO2 gas shielded welding transverse welding”. Through trial and error of preparations before welding, selection of welding process parameters, and welding operation process, Weld seam quality is well controlled, weld seams are beautifully formed, and relevant experience is promoted in practical training.

Analysis of Underwater Wet Welding Seam Forming Based on Arc Sensor Information

2013 ◽  
Vol 300-301 ◽  
pp. 500-503
Author(s):  
Bo Chen ◽  
Hong Tao Zhang ◽  
Ji Cai Feng
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Weld Seam ◽  
Water Environment ◽  
Welding Process ◽  
Welding Quality ◽  
Welding Seam ◽  
Underwater Welding ◽  
Arc Sensor ◽  
Sensor Information

It is difficult to obtain fine weld seam of underwater welding because of the water environment, this paper used arc sensor to obtain electrical information of the under water wet welding process, and BP neural network was used to model the process, experiment results showed the model could predict the process precisely, this laid the foundation for further controlling the welding quality automatically.

PENGEMBANGAN ALAT UKUR COMPRESSION TESTER

2019 ◽  
Vol 3 (2) ◽  
pp. 111-118
Author(s):  
Bahtiar Wilantara ◽  
Raharjo Raharjo
Keyword(s):  
Pressure Gauge ◽  
Welding Process ◽  
Field Trials ◽  
Ease Of Use ◽  
Hole Drilling ◽  
Measurement Tool ◽  
Drilling Process ◽  
Measuring Instrument ◽  
Digital Compression ◽  
Materials Used

This study aims to develop an analog compression tester measuring instrument into a digital compression tester as a measurement tool that can provide effectiveness and efficiency to users.                     This research is a research and development or R&D. This research was conducted in several steps, namely: problem identification, information gathering, product design, product manufacture, expert validation, product revision, testing, final production. The development of analog compression tester was first validated by material experts, media experts, and 15 students, and 5 students for field trials. The subjects of this study were vocational students at Taman Karya Madya Teknik Kebumen. Data collection techniques used in this study using instruments in the form of a questionnaire. The data analysis technique of this research is descriptive qualitative and quantitative descriptive percentage.                 The results of the development of digital compression tester designs are: 1) the tools and materials used are electric drill, grinding, cutter, goggles, gloves, masks, ruler, acetaminine welding, screwdriver, scissors, digital dial pressure gauge, hose, spark plugs, clamps , and nepel, 2) the manufacturing process that starts from the cutting process, the hole drilling process, the welding process and the process of connecting between components, 3) the workings of digital compression tester design that is reading the pressure or compression of the machine displayed on the monitor digitally using dial pressure digital gauge, 4) the test results obtained from the validation results from: a) material experts at 89% or Eligible; b) media experts at 85% or reasonable; c) response of field trial students in terms of ease of use and reading of 90% or feasible. Thus, the conclusion that the digital compression tester measuring instrument declared feasible to use for measurement.

Modeling and Analysis of Underwater Wet Weld Process Based on Regression Method

2013 ◽  
Vol 690-693 ◽  
pp. 2621-2624
Author(s):  
Bo Chen ◽  
Ji Cai Feng
Keyword(s):  
Weld Seam ◽  
Welding Process ◽  
Regression Method ◽  
Modeling And Analysis ◽  
Underwater Wet Welding ◽  
Underwater Environment ◽  
Arc Sensor ◽  
Weld Parameters ◽  
Automation Technology ◽  
Weld Automation

Underwater weld technology is urgently needed for the widely development of marine recourses, and weld automation technology is the inevitable choice because of the underwater environment. Because of the influence of the rigorous environment, the weld seam forming of underwater wet welding is very poor. To control the weld seam forming automatically, the model between the weld parameters and the weld seam shape must be built. This paper used arc sensor to monitor the electrical information of underwater wet welding process, and regression method was used to model the process, and the factors that influence the weld seam forming mostly were analyzed.

FEA of SAW penetration of Ramor 500 steel

2020 ◽  
Vol 62 (12) ◽  
pp. 1192-1198
Author(s):  
Ali Kaya Gur ◽  
Semih Taskaya ◽  
Subramaniam Shankar ◽  
Thangamuthu Mohanraj
Keyword(s):  
Three Dimensional ◽  
Welding Process ◽  
Source Model ◽  
Strength Properties ◽  
Steel Plates ◽  
Constant Current ◽  
Welding Seam ◽  
Depth Increase ◽  
Thermal Cooling ◽  
Submerged Arc

Abstract Ramor 500 steel plates are used as a ballistic material due to their greater hardness and strength properties. This steel can be produced with a 2-30 mm thickness sheet which may attain 505-590 HV hardness. In the present work, Ramor 500 steel pairs are joined using a submerged arc welding (SAW) process and taking various parameters into consideration. An austenitic additional wire is used for the welding process which contains Cr, Ni, and Mn. The source model prototype was developed using ANSYS software and considering a time-dependent three dimensional thermal model with source cooling. The highest tensile stress voltage value was determined in the sample applying a constant current of 250 A, 25 V and 30 cm × min-1welding speed. It was observed that the welding seam width increases as welding tension grows and that welding height and depth increase and decrease more or less in tandem. A ANSYS thermal cooling analysis revealed that welding tension grows with heat transfer which increases 15 mm from the main center of the welding area.

An Investigation of Dissimilar Welding Aluminum Alloys to Stainless Steel by the Tungsten Inert Gas (TIG) Welding Process

2017 ◽  
Vol 904 ◽  
pp. 19-23
Author(s):  
Van Nhat Nguyen ◽  
Quoc Manh Nguyen ◽  
Dang Thi Huong Thao ◽  
Shyh Chour Huang
Keyword(s):  
Stainless Steel ◽  
Aluminum Alloy ◽  
Welding Process ◽  
Dissimilar Materials ◽  
Welding Current ◽  
Tig Welding ◽  
Inert Gas ◽  
Dissimilar Welding ◽  
Adjacent Area ◽  
Welding Seam

Welding dissimilar materials has been widely applied in industries. Some of them are considered this as a strategy to develop their future technology products. Aluminum alloy and stainless steel have differences in physical, thermal, mechanical and metallurgic properties. However, selecting a suitable welding process and welding rods can solve this problem. This research aimed to investigate the T-joint welding between A6061 aluminum alloy and SUS304 stainless steel using new welding rods, Aluma-Steel by the Tungsten Inert Gas (TIG) welding process. The mechanical properties, the characteristics of microstructure, and component analysis of the welds have been investigated by the mechanical testing, scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS). As a result, the fracture occurred at the adjacent area between welding seam and A6061 alloys plate. The thermal cracking appeared at central welding-seam along the base metals if high welding current. A large amount of copper elements found in the welds due to using the new welding rod, Aluma-Steel rod.

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