Experimental investigation on ultrasonic metal welding of copper sheet with copper wire using Taguchi method

Author(s):  
V.P. Srinivasan ◽  
S. Balamurugan ◽  
B. Balakarthick ◽  
S. Devva Darshan ◽  
A.B. Dhanush Prabhu
Author(s):  
J. Pradeep Kumar ◽  
M.S. Arun Kumar ◽  
N. Gowsalya Devi ◽  
M. Naveen Kumar ◽  
S.M. Pavith Raja

Numerical stress analysis while joining an electrical contact comprising of copper wire and copper sheet using ultrasonic metal welding process is vital in many of the automotive applications. During ultrasonic metal welding, shear and normal force act at the interface between the welded specimens. These forces are the result of ultrasonic vibrations transmitted by Sonotrode onto the welded specimens. In this work, the distribution of the stress developed at the interface and the correlation of the developed stress with strength of joint are studied. The theoretical stress values are determined using various levels of ultrasonic metal welding process parameters such as clamping force, vibration amplitude and weld time to validate the results of stress obtained from finite element analysis. The results of stress from numerical analysis are found to be in good agreement with that of results obtained from the theoretical calculations.


2021 ◽  
Vol 62 ◽  
pp. 302-312
Author(s):  
Ninggang Shen ◽  
Avik Samanta ◽  
Wayne W. Cai ◽  
Teresa Rinker ◽  
Blair Carlson ◽  
...  

Author(s):  
Xinhua Shi ◽  
Lin Li ◽  
Suiran Yu ◽  
Lingxiang Yun

Abstract Ultrasonic metal welding is one of the key technologies in manufacturing lithium batteries, and the welding quality directly determines the battery performance. Therefore, an online welding process monitoring system is critical in identifying abnormal welding processes, detecting defects, and improving battery quality. Traditionally, the peak welding power is used to indicate abnormal process signals in welding process monitoring systems. However, since various factors have complex impacts on the electric power signals of ultrasonic welding processes, the peak power is inadequate to detect different types of welding defects. Therefore, a signal pattern matching method is proposed in this study, which is based on the electric power signal during the entire welding process and thus is capable of identifying abnormal welding processes in various conditions. The proposed method adopts isometric transformation and homogenization as signal pretreatment methods, and Euclidean distance is used to calculate the similarity metric for signal matching. The effectiveness and robustness of the proposed method are experimentally validated under different abnormal welding conditions.


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