Laurent Rippert

Optical and acoustic damage detection in laminated CFRP composite materials

Composite materials would gain substantial added value if it were possible to equip them with a system that could continuously monitor their damage state. In this approach, fibre-optic sensors could offer an alternative to the robust piezoelectric transducers used for acoustic emission (AE) monitoring. An intensity-modulated sensor based on the microbending concept was built and used to detect damage in laminated CFRP composite materials. Pencil lead break tests and tensile tests have been performed. The short-time Fourier Transform (STFT) has been computed and noise-reduction algorithms (adaptive filtering and spectral subtraction filtering) have also been used. The specimen final fracture can clearly be seen but transient signals were also detected before this final event. They can be correlated with the acoustic emission signals, analysed by a classical AE parameter study and with a modal acoustic emission (MAE) system. It is thus shown that the optical signal contains information on the elastic energy released whenever damage is being introduced in the host composite. Hints are that time-frequency analysis could be used to characterise this damage in a way similar to what is done for MAE.

Fibre optic sensor for continuous health monitoring in CFRP composite materials

An intensity modulated sensor, based on the microbending concept, has been incorporated in laminates produced from a C/epoxy prepreg. Pencil lead break tests (Hsu-Neilsen sources) and tensile tests have been performed on this material. In this research study, fibre optic sensors will be proven to offer an alternative for the robust piezoelectric transducers used for Acoustic Emission (AE) monitoring. The main emphasis has been put on the use of advanced signal processing techniques based on time-frequency analysis. The signal Short Time Fourier Transform (STFT) has been computed and several robust noise reduction algorithms, such as Wiener adaptive filtering, improved spectral subtraction filtering, and Singular Value Decomposition (SVD) -based filtering, have been applied. An energy and frequency -based detection criterion is put forward to detect transient signals that can be correlated with Modal Acoustic Emission (MAE) results and thus damage in the composite material. There is a strong indication that time-frequency analysis and the Hankel Total Least Squares (HTLS) method can also be used for damage characterization. This study shows that the signal from a quite simple microbend optical sensor contains information on the elastic energy released whenever damage is being introduced in the host material by mechanical loading. Robust algorithms can be used to retrieve and analyze this information.