Resistance Spot Welding Research Articles

Ultrasonic evaluation of stainless steel resistance spot welded based on deep learning

ABSTRACT Resistance spot welding (RSW) is a core process for joining thin sheets in aerospace, rail transportation and automotive manufacturing. The size of the weld nugget directly determines the strength of the joint, significantly affecting the reliability and service life of the entire structure. This study addresses the challenge of accurately measuring the true nugget size in stainless steel RSW joints due to the difficulty in distinguishing ultrasonic time-domain signals between the corona bond and the actual nugget. A deep learning-based ultrasonic spiral C-scan capsule detection method is proposed. First, a spiral C-scan capsule detection platform was designed and constructed, and typical joints were tested to obtain three-dimensional ultrasonic signals from different regions (non-welded, corona bond, nugget and defects). Then, a data processing model combining 3D Res-Unet and Transformer was used for semantic classification of the ultrasonic signals. The classification results were reconstructed into a two-dimensional imaging grid under the spiral scanning path, and image processing techniques were employed to extract the corona bond morphology and calculate the true nugget size. The results show that the Dice value for the nugget is 0.95, with a measurement error of less than 0.06 mm. This method provides a new perspective for in-situ detection of spot-welded joints and holds promise for engineering applications.

Assessment of resistance spot welding parameters on the strength and reliability of AISI 316L stainless steel joints

This study investigates how resistance spot welding parameters affect the joint strength and reliability of AISI 316L stainless steel, examining the effects of welding current, welding time, electrode pressure, and holding time. A 2ᵏ full factorial design combined with Weibull analysis was employed to systematically evaluate the influence of each parameter. Results indicate that the optimal welding conditions—4.0 kA welding current, 0.5 s welding time, 0.3 MPa electrode pressure, and 5.0 s holding time—lead to superior joint strength and reliability, achieving an average tensile shear force of 2376.02 N. Examination of the welded specimens revealed a pull-out failure mode and ductile fracture. Unlike previous studies that primarily focused on maximizing strength, this research integrates both strength and reliability assessments, providing a more comprehensive evaluation. The Weibull analysis not only validates findings from conventional analysis of variance, but also provides additional insights into joint reliability, demonstrating an effective alternative methodology for optimizing welding parameters. GRAPHICAL ABSTRACT HIGHLIGHTS A full factorial design combined with Weibull analysis was utilized to evaluate the effects of resistance spot welding parameters on AISI 316L stainless steel joints. High welding current, short welding time, low electrode pressure, and long holding time were identified as optimal conditions for achieving superior joint strength and reliability. Weibull analysis provided additional insight beyond ANOVA, enabling simultaneous assessment of strength and reliability, and guiding improved parameter selection for reliable welding.

Influence of ultrasonic vibration on weld quality in Al/Ti dissimilar resistance spot welding

Influence of ultrasonic vibration on weld quality in Al/Ti dissimilar resistance spot welding

A comparative study on microstructure and hardness properties of Inconel 625 alloy by resistance spot and seam welding methods

A comparative study on microstructure and hardness properties of Inconel 625 alloy by resistance spot and seam welding methods

Resistance spot welding of steel and aluminum with Cu/Zn bimetal interlayers: mechanical properties, microstructure and mechanisms

Resistance spot welding of steel and aluminum with Cu/Zn bimetal interlayers: mechanical properties, microstructure and mechanisms

Analysis of Resistance Spot Welding Characteristics with Flat Electrodes for Reducing Indentation in Excavator Exterior Parts

Resistance spot welding (RSW) inherently creates indentations on the material surface due to the applied pressure from the upper and lower electrodes. While indentations are not a major concern for internal components, they significantly affect the surface quality of external panels. To mitigate this issue, industrial practices involve increasing the diameter and curvature of the electrode tip; however, this approach cannot completely eliminate indentations, necessitating additional post-processing for their removal. Using large-area flat electrodes could theoretically prevent indentation, but this leads to excessive contact area, resulting in weakened joint strength and increased welding current requirements.In this study, a novel approach was proposed to minimize indentation by applying large-area flat electrodes to external components while maintaining conventional-sized electrodes for internal materials. Resistance spot welding was performed under various process conditions, and the weld strength and indentation depth were evaluated. Furthermore, the effects of different process parameters on weld quality and indentation formation were analyzed to determine optimal conditions that minimize indentation while maintaining sufficient joint strength.

Detection of Q235 Mild Steel Resistance Spot Welding Defects Based on EMD-SVM

Real-time detection of welding defects in resistance spot welding is a complex challenge. Dynamic resistance (DR) reflects nugget growth and varies with defect types, serving as a key indicator. This study presents an online quality evaluation and defect classification method for Q235 low-carbon steel welding. Welding current and voltage were collected in real-time, and DR signals were processed employing a second-order Butterworth low-pass filter featuring zero-phase processing to enhance accuracy. Empirical mode decomposition (EMD) decomposed these signals into intrinsic mode functions (IMFs) and residuals, which were classified by a support vector machine (SVM). Experiments showed the EMD-SVM method outperforms traditional approaches, including backpropagation (BP) neural networks, SVM, wavelet packet decomposition (WPD)-BP, WPD-SVM, and EMD-BP, in identifying four welding states: normal, spatter, false, and edge welding. This method provides an efficient, robust solution for online defect detection in resistance spot welding.

Optimization of Process Parameters for Resistance Spot Welding of 17-4PH Stainless Steel Using Response Surface Methodology

This study explores the resistance spot welding (RSW, resistance spot welding) characteristics of precipitation-hardened stainless steel 17-4PH with dissimilar thicknesses (0.3 mm and 0.66 mm) to optimize welding conditions. Widely used in aerospace applications for its high-temperature strength and corrosion resistance, 17-4PH requires precise welding methods to ensure consistent quality. A Central Composite Design (CCD, central composite design) was utilized to optimize process parameters, focusing on weld current (4-6 kA) and weld time (200-300 ms). The weldability was assessed through tensile shear strength, nugget size, and the occurrence of expulsion. Regression analysis produced models with coefficients of determination (R<sup>2</sup>) of 0.99 for both tensile strength and nugget size. ANOVA(analysis of variance) indicated weld current as the most significant factor, contributing 86.9% to tensile strength and 89.4% to nugget size. The optimal welding condition of 5.25 kA and 300 ms was verified experimentally, yielding prediction errors of 1.6% for tensile strength and 3.9% for nugget size. This research provides a robust framework for enhancing RSW processes for 17-4PH with dissimilar thicknesses, supporting its wider application in high-performance industries like aerospace.

Investigation of Re-Spot Effects on Mechanical Properties in Resistance Spot Welding of Low Carbon Steel

Resistance spot welding is a widely utilized method for joining metal sheets in the automobile industry. This research studied the mechanical and metallurgical features of welds made of low-carbon steel. Two methods were utilized in implementing welding, single-pulse and second-pulse, to improve the welds' mechanical features. The current of the second pulse was less than the current of the first pulse. The results also demonstrated that the fusion zone in the second pulse consisted of two regions: The primary fusion zone (PFZ) and the second fusion zone formed since the second pulse. The microstructure of the Primary fusion zone is composed of lath martensite and tempered martensite in the second fusion zone (SFZ). It was noticed that the ultimate tensile shear force was 4.36 in a single pulse compared to second-pulse welds, which were 7.46 KN. It was also demonstrated that the hardness magnitudes decreased with the increase of the second pulse current due to the increase in ductility, which negatively impacted the mechanical features.

Experiments and Simulations Study on Resistance Spot Welding of HSLA Steel Sheets: Process Parameters and Quality Analysis

Experiments and Simulations Study on Resistance Spot Welding of HSLA Steel Sheets: Process Parameters and Quality Analysis

Research on an Online Intelligent Monitoring System for Resistance Spot Welding Based on Wireless Communication.

Resistance spot welding (RSW) faces critical monitoring challenges in industrial applications due to nonlinear coupling characteristics and production line disturbances. This study developed a Zigbee-enabled real-time monitoring system to address the precision limitations of conventional methods in tracking RSW parameters. Using DP780/DP590 dual-phase steel specimens with thickness variations, we implemented a dedicated data acquisition system capturing welding current, voltage, and barometric pressure dynamics. The experimental results demonstrated measurement accuracies within ±0.49% for current, ±0.25% for voltage, and 3.72% average relative error for barometric pressure with stable operational deviations (0.017-0.024 MPa).

An Adaptive Multivariate Functional Control Chart

New data acquisition technologies allow one to gather amounts of data that are best represented as functional data. In this setting, profile monitoring assesses the stability over time of both univariate and multivariate functional quality characteristics. The detection power of profile monitoring methods could heavily depend on parameter selection criteria, which usually do not take into account any information from the out-of-control (OC) state. This work proposes a new framework, referred to as adaptive multivariate functional control chart (AMFCC), capable of adapting the monitoring of a multivariate functional quality characteristic to the unknown OC distribution by combining p-values of partial tests corresponding to Hotelling T 2 -type statistics calculated at different parameter combinations. Through an extensive Monte Carlo simulation study, the performance of AMFCC is compared with methods that have already appeared in the literature. Finally, a case study is presented in which the proposed framework is used to monitor a resistance spot welding process in the automotive industry. AMFCC is implemented in the R package funcharts, available on CRAN.

OPTIMIZATION OF WELDING PARAMETERS IN SPOT WELDING OF AISI 316L AND IF 7114 DISSIMILAR JOINTS

This study investigates the optimization of welding parameters in spot welding of dissimilar materials, AISI 316L stainless steel and IF 7114 steel. The objective is to enhance the mechanical properties of the welded joints, particularly the tensile shear strength, by optimizing welding parameters such as electrode force, welding current, and welding time. Using the Taguchi method, an experimental design was developed, and spot resistance welding was performed on 18 different parameter combinations. The results indicate that increased electrode force, welding current, and welding time led to a significant improvement in tensile shear strength. The highest tensile shear strength of 7.877[Formula: see text]N was achieved with 6[Formula: see text]kN electrode force, 9[Formula: see text]kA welding current, and 50 cycles of welding time. Additionally, the weld core diameter and depth increased with higher heat input, and significant grain coarsening was observed in the heat-affected zone of IF 7114 steel. The study concludes that optimizing welding parameters enhances the mechanical properties of dissimilar joints, with the Taguchi method providing an effective approach for determining the ideal welding conditions.

Liquid metal embrittlement susceptibility of galvanized advanced high strength steel with high manganese content

Abstract The galvanized advanced high strength steel (AHSS) with high manganese content tends to suffer the liquid metal embrittlement (LME) during the resistance spot welding (RSW) process. In this study, the LME susceptibility of one kind of galvanized AHSS with high manganese content was systematically evaluated based on the criterion of Auto/Steel Partnership (A/SP). The galvanized AHSS with high manganese content was welded at 16 groups of different welding currents from 7.0 kA to 14.5 kA with intervals of 0.5 kA. No evident LME cracks could be observed in the cross sections of those specimens below expulsion. However, numerous severe LME cracks could be clearly observed for the joints at or above expulsion. It was considered that the increase of the welding current aggravated the LME severity of this kind of steel. Additionally, the nugget size could be measured after the chemical etching. The nugget size gradually increased with increasing the welding current. Based on the A/SP criterion, the results revealed that this kind of galvanized AHSS with high manganese content exhibited high LME susceptibility, thus not meeting the requirements. Except for the large welding current, it was deemed that the high Mn content was the crucial factor to lead to high LME susceptibility of this steel.

Correction: Magnetically assisted resistance spot welding: a comprehensive review

Correction: Magnetically assisted resistance spot welding: a comprehensive review

PREPARATION OF Mg-6Zn AND A STUDY ON ITS RESISTANCE-SPOT WELDING MICROSTRUCTURE AND MECHANICAL PROPERTIES

This article investigates the effect of different welding currents on the microstructure, nugget diameter, and tensile strength of a 1.5-mm-thick Mg-6Zn magnesium alloy through resistance-spot welding. A detailed analysis is conducted using various experimental techniques, including tensile testing, microhardness testing, optical microscopy, and scanning electron microscopy. When the current is 16 kA, the hardness and peak value are 62.45 HV and 1.108 kN, respectively. Therefore, when the current is 16 kA, the hardness in the fusion zone is the smallest and the peak value and fusion diameter are the largest, which is the optimal spot-welding parameter. The welded joint is mainly composed of a fusion zone and a heat-affected zone. The microhardness of the fusion zone is the highest, significantly higher than that of the heat-affected zone and the base material. The fusion zone is mainly composed of equiaxed and columnar dendrites, and grain coarsening is observed in both the fusion zone and the heat-affected zone. There are two types of fracture modes for welded joints. When the size of the weld core is small, it is the joint surface fracture, and when the size of the weld core is large, it is the button fracture. We conducted in-depth research on the microstructure characteristics, fracture morphology, and microhardness distribution of the joint.

PREPARATION OF Mg-7Sn-1Ca MAGNESIUM ALLOY AND STUDY OF ITS RESISTANCE SPOT WELDING MICROSTRUCTURE AND MECHANICAL PROPERTIES

This paper investigated a 1.5-mm-thick Mg-7Sn-1Ca magnesium alloy through resistance spot welding, examining how the welding current affects the joint microstructure, nugget diameter and tensile strength. Various experimental techniques, including tensile tests, microhardness testing, optical microscopy, and scanning electron microscopy, were employed for a detailed analysis. The optimal mechanical performance was achieved under conditions of 14 kA current, 1 kN pressure, and 0.4 s welding time, with a tensile strength of 1.0295 kN and nugget diameter of 2.25 mm. The welded joints mainly consist of a nugget zone and a heat-affected zone. The nugget zone exhibits the highest microhardness, significantly exceeding that of the heat-affected zone and the base metal. The nugget zone is primarily composed of equiaxed dendrites and columnar dendrites, with grain coarsening observed in both the nugget and heat-affected zones. The microstructural features, fracture-surface morphology, and microhardness distribution of the joints were thoroughly investigated. These analyses provide valuable data on joint performance, aiding in the further understanding and optimization of the welding process.

Resistance spot welding insights: A dataset integrating process parameters, infrared, and surface imaging.

Resistance spot welding insights: A dataset integrating process parameters, infrared, and surface imaging.

Effects of welding current on microstructure evolution and mechanical behavior of WC-Co/X32 steel joints by resistance spot welding

Effects of welding current on microstructure evolution and mechanical behavior of WC-Co/X32 steel joints by resistance spot welding

Effect of loading configuration on tensile and fatigue behavior of dissimilar resistance spot welds of selective laser-melted maraging steels

Effect of loading configuration on tensile and fatigue behavior of dissimilar resistance spot welds of selective laser-melted maraging steels