Online detection method for transient waves applied to continuous health monitoring of carbon-fiber-reinforced polymer composites with embedded optical fibers

It has been proven that the embedment of optical fibers into a composite material could offer an alternative to robust piezoelectric transducers used for Acoustic Emission (AE) monitoring. In this configuration optical fibers are used as intensity-modulated sensors. A set of propagating elastic waves is generated whenever damage occurs in the composite material. These waves locally modify the optical and geometrical properties of the optical fiber and hence can be detected by them as a transient signal that modulates the light intensity. In this paper a method for detecting the transients by on-line signal processing is presented. It is then applied to optical signals resulting from tensile tests performed on CFRP composites material with embedded optical fibers. By means of the Short-Time Fourier Transform (STFT), the level of the noise added to the signal is estimated by filtering the time trajectories. This filter is continuously adapted according to the principle of minimization of the mean squared error. Finally the detection is achieved by a constant false alarm rate power-law detector. This technique is fast and doesn't take into account neither the statistical distribution of the noise nor the frequency content of the transients as long as the frequency component distribution can be approximated by an exponential law. The detected transient features can be correlated with the AE results but an off-line analysis and classification is still needed.

[1]  Peter Vary,et al.  Noise suppression by spectral magnitude estimation —mechanism and theoretical limits— , 1985 .

[2]  R. Stephenson.  A and V , 1962, The British journal of ophthalmology.

[3]  Zhen Wang,et al.  A performance study of some transient detectors , 2000, IEEE Trans. Signal Process..

[4]  D. B. Preston.  Spectral Analysis and Time Series , 1983 .

[5]  Philippe Ravier.  Detection de transitoires par ondelettes adaptees , 1998 .

[6]  Sabine Van Huffel,et al.  Optical sensor for continuous damage monitoring in composite materials , 2000 .

[7]  Kevin Barraclough,et al.  I and i , 2001, BMJ : British Medical Journal.

[8]  Zhen Wang,et al.  All-purpose and plug-in power-law detectors for transient signals , 2001, IEEE Trans. Signal Process..

[9]  A. H. Nuttall.  Near-optimum detection of random signals of unknown location, structure, extent, and strength , 1995, 'Challenges of Our Changing Global Environment'. Conference Proceedings. OCEANS '95 MTS/IEEE.

[10]  Jan Kybic,et al.  Extended spectral subtraction , 1996, 1996 8th European Signal Processing Conference (EUSIPCO 1996).

[11]  John W. Fay,et al.  Power-law processors for detecting unknown signals in colored noise , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[12]  Sabine Van Huffel,et al.  Fiber optic sensor for continuous health monitoring in CFRP composite materials , 2002, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

[13]  J. W. Berthold,et al.  Historical review of microbend fiber-optic sensors , 1995 .

[14]  Rainer Martin,et al.  Spectral Subtraction Based on Minimum Statistics , 2001 .

[15]  Hynek Hermansky,et al.  Temporal processing of speech in a time-feature space , 1997 .

[16]  Martine Wevers,et al.  Optical and acoustic damage detection in laminated CFRP composite materials , 2000 .