Dynamic feature evaluation on streaming acoustic emission data for adhesively bonded joints for composite wind turbine blade

Author:

Xu Dong1,Liu Pengfei2ORCID,Chen Zhiping1,Cai Qimao3,Leng Jianxing2

Affiliation:

1. Institute of Chemical Machinery and Process Equipment, College of Energy Engineering, Zhejiang University, Hangzhou, China

2. Ocean College, Zhejiang University, Zhoushan, China

3. School of Civil Engineering and Architecture, Zhejiang Sci-Tech University, Hangzhou, China

Abstract

Damage mode identification and premature failure prevention for composite structures by acoustic emission have drawn a great deal of attention. Feature evaluation on streaming acoustic emission data is one of the significant issues in research of acoustic emission signal processing. This work conducts dynamic feature evaluation on 15 conventional acoustic emission features so as to seek a deeper insight into different features with damage accumulation. First, the procedure of dynamic feature evaluation is presented based on three basic algorithms. Second, the streaming acoustic emission data are collected from the adhesively bonded composite single-lap joint subjected to quasi-static tensile loads. Third, further efforts are made so as to explore the information contained as well as to interpret the effect of damage accumulation. It is found that different conventional acoustic emission features show distinctive functions, including damage mode identification, damage process indication, and both of them. Informative features for damage pattern recognition are independent on damage accumulation. Useful features for damage process description show sensitive dynamic characteristics with damage accumulation, especially before the complete failure of the specimen. Furthermore, dynamic feature evaluation can be used to detect singular signals.

Funder

National Natural Science Foundation of China

fundamental research funds for the central universities

Publisher

SAGE Publications

Subject

Mechanical Engineering,Biophysics

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