Damage Mode Identification for the Clustering Analysis of AE Signals in Thermoplastic Composites

  • Bi-Ling Yang
  • Xing-Min Zhuang
  • Tong-Hua Zhang
  • Xiong Yan


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.

Self-reinforced polyethylene composites Thermoplastic Acoustic emission Pattern recognition Failure mechanisms Damage mode 


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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Bi-Ling Yang
    • 1
    • 2
    • 3
  • Xing-Min Zhuang
    • 1
    • 2
  • Tong-Hua Zhang
    • 4
  • Xiong Yan
    • 1
    • 2
  1. 1.College of TextilesDonghua UniversityShanghaiChina
  2. 2.The Key Laboratory of Textile Science & TechnologyMinistry of EducationShanghaiChina
  3. 3.Textile DepartmentGuangdong Institute of Textile TechnologyFoshanChina
  4. 4.College of Textiles & GarmentsSouthwest UniversityChongqingChina

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