Skip to main content
SpringerLink
Log in

Study of detecting impact damage for composite material based on intelligent sensor

  • Published:
Journal of Wuhan University of Technology-Mater. Sci. Ed. Aims and scope Submit manuscript

Abstract

A system of impact damage detection for composite material structures by using an intelligent sensor embedded in composite material is described. In the course of signal processing, wavelet transform has the exceptional property of temporal frequency localization, whereas Kohonen artificial neural networks have excellent characteristics of self-learning and fault-tolerance. By combining the merits of abstracting time-frequency domain eigenvalues and improving the ratio of signal to noise in this system, impact damage in composite material can be properly recognized.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Miller G E. Fiber Optic Sensors for Aircraft.SPIE Fiber Optic Smart Structures and Skins IV, 1991, 1538: 178–181

    Google Scholar 

  2. Lee C K. Theory of Laminated Piezoelectric Plates for the Design of Distributed Sensors/Actuators. Part I: Governing Equations and Reciprocal Relationships.J. Acoust Soc. Am., 1990, 87 (3): 1144–1158

    Article  Google Scholar 

  3. Salzano T B, Calder C A. Vibration Measurement in Composite Members Using Embedded Constantan Wire.J. of Intelligent Materials and Structures, 1992, 3 (3): 536–546

    Article  Google Scholar 

  4. Brignell J, White N.Intelligent Sensor Systems. Bristol: IOP Publishing Inc, 1994

    Google Scholar 

  5. Xue Q, Reddy RBS. Late Potential Recognition by Artificial Neural Networks.IEEE Trans, on Biomed. Eng., 1997, 44: 132–143

    Article  CAS  Google Scholar 

  6. Lei Wang, Meir Klein, Solomon Yirga, Prabha Kundur. Dynamic Reduction of Large Power Systems for Stability Studies.IEE transactions on PS, 1997, 12 (2): 2103–2108

    Google Scholar 

  7. Qin Qianqing, Yang Zhongkai.Practicality Wavelet Analysis. Xi-An: XiAn University Press of Electron Technology, 1994

    Google Scholar 

  8. Liu Wei,et al. The Compression of IR Spectra by Using Wavelet Neural Network.Chinese Science Bulletin, 1997, 10: 822–825

    Google Scholar 

  9. Lu Baiquan,et al. Wavelet Neural Network for Function Leaming.Automatic Sinice. 1998, 24 (4): 548–551

    Google Scholar 

  10. Yu Yong, Wan Dejun. Simulation Research on an Approach of Fault Detection Using Wavelet Neural Networks.Computer Simulation. 2000, 17 (1): 24–27

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Wuhan University of Technology, 430070, Wuhan, China

    Zhou Zu-de (Prof., President), Liu Quan & Jiang Xue-mei

Authors
  1. Zhou Zu-de
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Liu Quan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jiang Xue-mei
    View author publications

    You can also search for this author in PubMed Google Scholar

Additional information

ZHOU Zu-de: Born in 1946

Funded by Hubei Natural Science Foundation (No. 2000J161)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Zu-de, Z., Quan, L. & Xue-mei, J. Study of detecting impact damage for composite material based on intelligent sensor. J. Wuhan Univ. Technol.-Mat. Sci. Edit. 17, 54–57 (2002). https://doi.org/10.1007/BF02852636

Download citation

  • Received:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02852636

Key words

Search

Navigation