Acoustic Emission System for Monitoring Mechanical Behavior During Ultrasonic Metal Welding

Author(s):  
Vijay Dodiya ◽  
Sarthak Bhavsar ◽  
Naman Kansara ◽  
Nikhil Murarka ◽  
Keyur P. Desai ◽  
...  
Author(s):  
Yu Sik Kong ◽  
Muralimohan Cheepu ◽  
Jin-Kyung Lee

Friction welding was chosen for its versatility in the joining of dissimilar materials with high quality. The aim of this study is to determine the optimal welding conditions for attaining quality joints by using online monitoring of acoustic emission system signals. During friction welding, the formation of cracks, defects, or any abnormalities in the joining process which have a detrimental effect on the joints quality was identified. The most widely used materials in the aerospace industry—Inconel 718 and molybdenum steel—were joined by friction welding. The precision of the joints, internal defects, and quality are major concerns for aerospace parts. The results of the present research determined the optimal welding conditions for high tensile strength by nondestructively inducing acoustic emission signals. During friction time and upset time periods, the typical waveforms and frequency spectrum of the acoustic emission signals were recorded, and their energy level, average frequency, cumulative count, and amplitude were analyzed. Both cumulative count and amplitude were found to be useful parameters for deriving the optimal welding conditions. In the initial stage of friction welding, a very high voltage of continuous form was generated with frequency characteristics of 0.44 MHz and 0.54 MHz. The signals generated during the upset stage had a low voltage, but a very high frequency of 1.56 MHz and 1.74 MHz with a burst-type signal. The amplitude of the signal generated for the optimally welded joints was about 100 dB at the friction time and about 45 dB at the upset time.


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

2021 ◽  
Vol 5 (1) ◽  
pp. 16
Author(s):  
David Jeronimo Busquets ◽  
Carlos Bloem ◽  
Amparo Borrell ◽  
Maria Dolores Salvador

The improvement of high temperature materials with lower heat transfer coefficients lead to the development of thermal barrier coatings (TBCs). One of the most widely used materials for thermal barrier coatings is Y2O3 stabilized ZrO2 (Y-TZP) because of its excellent shock resistance, low thermal conductivity, and relatively high coefficient of thermal expansion. The aim of this work is to study the TBCs mechanical behavior with the addition of SiC into the suspension of Y-TZP/Al2O3 by acoustic emission (AE). Additionally, a microstructural analysis and a finite elements model were carried out in order to compare results. The coatings were made by suspension plasma spray (SPS) on metal plates of 70 × 12 × 2 mm3. An intermetallic was deposited as a bond coating, followed by a coating of Y-TZP/Al2O3 with and without 15 wt.% SiC, with thicknesses between 87 and 161 μm. The AE becomes a fundamental tool in the study of the mechanical behavior of thermal barriers. The use of wavelet transforms streamlines the study and analysis of recorded sound spectra. The crack generation arises at very low stress levels.


Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2350 ◽  
Author(s):  
Jun Peng ◽  
Sheng-Qi Yang

High temperature treatment has a significant influence on the mechanical behavior and the associated microcracking characteristic of rocks. A good understanding of the thermal damage effects on rock behavior is helpful for design and stability evaluation of engineering structures in the geothermal field. This paper studies the mechanical behavior and the acoustic emission (AE) characteristic of three typical rocks (i.e., sedimentary, metamorphic, and igneous), with an emphasis on how the difference in rock type (i.e., porosity and mineralogical composition) affects the rock behavior in response to thermal damage. Compression tests are carried out on rock specimens which are thermally damaged and AE monitoring is conducted during the compression tests. The mechanical properties including P-wave velocity, compressive strength, and Young’s modulus for the three rocks are found to generally show a decreasing trend as the temperature applied to the rock increases. However, these mechanical properties for quartz sandstone first increase to a certain extent and then decrease as the treatment temperature increases, which is mainly attributed to the high porosity of quartz sandstone. The results obtained from stress–strain curve, failure mode, and AE characteristic also show that the failure of quartz-rich rock (i.e., quartz sandstone and granite) is more brittle when compared with that of calcite-rich rock (i.e., marble). However, the ductility is enhanced to some extent as the treatment temperature increases for all the three examined rocks. Due to high brittleness of quartz sandstone and granite, more AE activities can be detected during loading and the recorded AE activities mostly accumulate when the stress approaches the peak strength, which is quite different from the results of marble.


2018 ◽  
Vol 962 ◽  
pp. 012064
Author(s):  
S Bakhri ◽  
E Sumarno ◽  
R Himawan ◽  
T Y Akbar ◽  
M. Subekti ◽  
...  

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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