You are being redirected because this document is part of your ASTM Compass® subscription.
This document is part of your ASTM Compass® subscription.
Volume 46, Issue 6 (March 2018)
Characteristic Analysis of Welding Crack Acoustic Emission Signals Using Synchrosqueezed Wavelet Transform
(Received 25 October 2016; accepted 6 July 2017)
Published Online: 13 March 2018
CODEN: JTEVAB
X
.RIS
For RefWorks, EndNote, ProCite, Reference Manager, Zoteo, and many others.
.DOCX
For Microsoft Word
Abstract
The synchrosqueezed wavelet transform (SST) is introduced to conduct analysis and processing of the acoustic emission (AE) signal in the welding process. The energy distribution of the signal in the time-scale plane is compressed and reorganized by SST, which obtains the time-frequency diagram of the AE signal. Meanwhile, the correlation coefficient is introduced as the criterion for removing the undesirable frequency components, which can effectively eliminate the noise and retain the characteristics of the welding crack AE signal. The test experiment of the AE signals in the welding process is designed. The time-frequency distribution characteristics of the AE signals in the welding process are described and extracted by SST, which is characterized by high aggregation and prominent instantaneous frequency information. Experimental results are provided to confirm the effectiveness of this approach to extract the AE signal physical information related to the welding crack.
Author Information:
He, Kuanfang
Hunan Provincial Key Laboratory of Health Maintenance for Mechanical Equipment, Hunan University of Science and Technology, Xiangtan
Li, Qi
Hunan Provincial Key Laboratory of Health Maintenance for Mechanical Equipment, Hunan University of Science and Technology, Xiangtan
Yang, Qing
Hunan Provincial Key Laboratory of Health Maintenance for Mechanical Equipment, Hunan University of Science and Technology, Xiangtan
Stock #: JTE20170218
ISSN:0090-3973
DOI: 10.1520/JTE20170218
Author
Title Characteristic Analysis of Welding Crack Acoustic Emission Signals Using Synchrosqueezed Wavelet Transform
Symposium ,
Committee A01