Energy Meter Patch Resistance and Welding Spot Anomaly Detection Method Based on Machine Vision

Glass Product Defects Detection Method Based on Machine Vision

This paper develops the machine vision based detection method to detect glass products defects. The novel segmentation method based on unsupervised learning is proposed to segment the defect regions and background. The fuzzy support vector machine was adopted as classifiers for the extracted features. The experimental results indicated the accuracy rate can reach up to 96.7 % by using the metho...

Neural Network-Based Resistance Spot Welding Control and Quality Prediction

This paper describes the development and evaluation of neural network-based systems for industrial welding process control and weld quality assessment. The developed systems utilize recurrent neural networks for process control and both recurrent networks and static networks for quality prediction. The first section describes a system capable of both welding process control and real-time weld q...

Resistance Spot Welding of Steels: Modeling and Simulation

Resistance spot welding (RSW) includes many variables that can influence the weld properties. The purpose of this study is to develop an analytical model for prediction of thermal history and weld microstructure in RSW and to find the most important process parameters that influence the weld microstructure. A one dimensional model is proposed for prediction about thermal history during cooling ...

Resistance Spot Welding: A Heat Transfer Study

A heat transfer study of resistance spot welding has been conducted both theoretically and experimentally. A numerical solution based on a finite difference formulation of the heat equation has been developed to predict temperature distributions as a function of both time and position during the welding process. The computer model also predicts the temperature distribution through the copper el...

Review on Modeling of Resistance Spot Welding Process