Damage Mode Identification for the Clustering Analysis of AE Signals in Thermoplastic Composites |
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Authors: | Bi-Ling Yang Xing-Min Zhuang Tong-Hua Zhang Xiong Yan |
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Affiliation: | 1. College of Textiles, Donghua University, 2999 North Renmin Road, Songjiang District, Shanghai, 201620, China 2. The Key Laboratory of Textile Science & Technology, Ministry of Education, 2999 North Renmin Road, Songjiang District, Shanghai, 201620, China 3. Textile Department, Guangdong Institute of Textile Technology, 20 Lanshi II Road, Foshan, Guangdong, 528041, China 4. College of Textiles & Garments, Southwest University, 216 Tiansheng Road, Beibei District, Chongqing, 400715, China
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Abstract: | An objective analytical procedure for the investigation of damage mechanisms in the thermoplastic self-reinforced polyethylene (UHMWPE/PE) composites under quasi-static tensile load has been established, using Unsupervised Pattern Recognition (UPR) technique for the clustering task of Acoustic Emission (AE) signals. Focus is on the correlating between the obtained classes and their specific damage mechanisms. This was carried out by waveform visualization and Fast Fourier Transform analysis. Pure resin and fiber bundles were tested to collect typical waveforms of matrix cracking and fiber fracture respectively, in order to label the signal classes in the composites. The evolution process of various damage mechanisms in the composites revealed that the correlating method was effective. The AE characteristics of different damage modes found out in this study can be used as the reference for identifying unknown AE signals in the UHMWPE/PE composites. The established procedure is also potential in the investigation of failure mechanisms for composite materials with UPR technique. |
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