Journal of South China University of Technology (Natural Science Edition) ›› 2008, Vol. 36 ›› Issue (1): 76-80.

• Electronics, Communication & Automation Technology • Previous Articles     Next Articles

Feature Extraction of Acoustic Emission Signals Based on Fractal Dimension and Independent Component Analysis

Liu Guo-hua  Huang Ping-fie  Gong Xiang  Gu Jiang  Zhou Ze-kui   

  1. State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, Zhejiang, China
  • Received:2006-12-20 Online:2008-01-25 Published:2008-01-25
  • Contact: 黄平捷，副教授，主要从事无损检测方面的研究． E-mail:pjhuang@zju．edu．cn
  • About author:刘国华（1980-），男，博士生，主要从事材料声发射测试方面的研究．E-mail：ghliu@iipc．zju．edu．cn
  • Supported by:

    国家自然科学基金资助项目（50505045）

PDF

948

Abstract:

According to the effect of noises on the fractal dimension of acoustic emission （AE） signals, this paper proposes a method based on fractal dimension and independent component analysis （ICA） to extract the AE signal feature of construction material. In the investigation, the concept of fractal dimension is first introduced, and the effect of noises on the fractal dimension is theoretically analyzed. Then, the ICA is introduced to preprocess AE signals, and the fractal dimension is calculated from the independent signal after ICA process, with the AE source lead simulation being finally performed. The results show that the fractal dimensions in different AE sources and transmission media display distinct features, and that the fractal dimension after de-noising corresponds with the emission event number more precisely than that without de-noising. It is thus concluded that the fractal dimension can be used to identify the AE signal feature of construction materials because it is almost independent of the subjects of researchers and is easy to standardize.

Key words: acoustic emission, feature extraction, independent component analysis, fractal dimension