Development of monitoring system for laser welding system of thin stainless steel sheets by waveform analysis

2007 ◽  
Author(s):  
Naoki Kawada ◽  
Masashi Oikawa ◽  
Syunichi Iwaki ◽  
Hiroyuki Kumehara
Keyword(s):  
Stainless Steel ◽  
Laser Welding ◽  
Monitoring System ◽  
Waveform Analysis ◽  
Steel Sheets ◽  
Welding System

scholarly journals Development of Condition Monitoring System for Laser Welding System of Stainless Steel Sheets

2009 ◽  
Vol 75 (5) ◽  
pp. 629-633
Author(s):  
Naoki KAWADA ◽  
Masashi OIKAWA ◽  
Yosuke OTSUKA ◽  
Syunichi IWAKI ◽  
Hiroyuki KUMEHARA
Keyword(s):  
Stainless Steel ◽  
Laser Welding ◽  
Monitoring System ◽  
Condition Monitoring ◽  
Steel Sheets ◽  
Condition Monitoring System ◽  
Welding System

scholarly journals Development of Condition Monitoring System for Electric Resistance Spot Welding Used to Manufacture Railway Car Bodies

2021 ◽  
Vol 33 (2) ◽  
pp. 421-431
Author(s):  
Masashi Oikawa ◽  
Kentaro Atsumi ◽  
Yosuke Otsuka ◽  
Naoki Kawada ◽  
◽  
...  
Keyword(s):  
Stainless Steel ◽  
Laser Welding ◽  
Monitoring System ◽  
Condition Monitoring ◽  
Resistance Spot Welding ◽  
Spot Welding ◽  
Car Body ◽  
Resistance Spot ◽  
Condition Monitoring System ◽  
Welding System

Stainless steel railway car bodies are assembled by joining the outer plates and the pillar materials using resistance spot welding. In recent years, more and more car bodies are being assembled using laser welding in addition to the resistance spot welding. For this laser welding system, we developed a condition monitoring system considering the processes before and after laser welding as a single system, and obtained and put into practical use an appropriate condition that suppresses spatter generation during laser welding. On the other hand, in resistance spot welding, the current, weld time, electrode load, and electrode tip shape are the main factors that determine the welding quality. Therefore, the configuration of the equipment is less complicated than that of laser welding system, and the condition monitoring is easier than that of the laser welding. In this study, by transferring the concept of the condition monitoring system developed for laser welding to resistance spot welding, we achieved a reduction of more than 60% in terms of electricity consumption and improved the appearance of the car body by optimizing the indentation shape. In addition to this technical achievement, we also present in this paper a case study showing the opportunity for innovation by restructuring the technological paradigm of the resistance spot welding in the production of stainless steel car body shells.

scholarly journals Analysis of Acoustic Emission (AE) Signals for Quality Monitoring of Laser Lap Microwelding

2021 ◽  
Vol 11 (15) ◽  
pp. 7045
Author(s):  
Ming-Chyuan Lu ◽  
Shean-Juinn Chiou ◽  
Bo-Si Kuo ◽  
Ming-Zong Chen
Keyword(s):  
Stainless Steel ◽  
Acoustic Emission ◽  
Frequency Domain ◽  
Monitoring System ◽  
Welding Quality ◽  
Steel Sheets ◽  
Signal Features ◽  
Ae Signal ◽  
Laser Microwelding ◽  
Ae Signals

In this study, the correlation between welding quality and features of acoustic emission (AE) signals collected during laser microwelding of stainless-steel sheets was analyzed. The performance of selected AE features for detecting low joint bonding strength was tested using a developed monitoring system. To obtain the AE signal for analysis and develop the monitoring system, lap welding experiments were conducted on a laser microwelding platform with an attached AE sensor. A gap between the two layers of stainless-steel sheets was simulated using clamp force, a pressing bar, and a thin piece of paper. After the collection of raw signals from the AE sensor, the correlations of welding quality with the time and frequency domain features of the AE signals were analyzed by segmenting the signals into ten 1 ms intervals. After selection of appropriate AE signal features based on a scatter index, a hidden Markov model (HMM) classifier was employed to evaluate the performance of the selected features. Three AE signal features, namely the root mean square (RMS) of the AE signal, gradient of the first 1 ms of AE signals, and 300 kHz frequency feature, were closely related to the quality variation caused by the gap between the two layers of stainless-steel sheets. Classification accuracy of 100% was obtained using the HMM classifier with the gradient of the signal from the first 1 ms interval and with the combination of the 300 kHz frequency domain signal and the RMS of the signal from the first 1 ms interval.

scholarly journals Development of Quality Control System for Laser Spot Welding System of Stainless Steel Sheets

2009 ◽  
Vol 75 (8) ◽  
pp. 973-978 ◽  
Author(s):  
Naoki KAWADA ◽  
Shinich SHIRAISHI ◽  
Masashi OIKAWA ◽  
Yousuke OTSUKA ◽  
Syunichi IWAKI ◽  
...  
Keyword(s):  
Quality Control ◽  
Stainless Steel ◽  
Control System ◽  
Spot Welding ◽  
Quality Control System ◽  
Laser Spot ◽  
Steel Sheets ◽  
Laser Spot Welding ◽  
Welding System

Laser absorption in high-power fiber laser welding of stainless steel and aluminum alloy

2008 ◽  
Author(s):  
Naoyuki Matsumoto ◽  
Yousuke Kawahito ◽  
Masami Mizutani ◽  
Seiji Katayama
Keyword(s):  
Stainless Steel ◽  
Aluminum Alloy ◽  
Laser Welding ◽  
Fiber Laser ◽  
High Power ◽  
Fiber Laser Welding ◽  
Laser Absorption
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