Projects per year
Nonlinear ultrasonic techniques rely on the measurement of nonlinear elastic effects caused by the interaction of ultrasonic waves with the material damage, and have shown high sensitivity to detect micro-cracks and defects in the early stages. This paper presents a nonlinear ultrasonic technique, here named nonlinear elastic multi-path reciprocal method, for the identification and localisation of micro-damage in composite laminates. In the proposed methodology, a sparse array of surface bonded ultrasonic transducers is used to measure the second harmonic elastic response associated with the material flaw. A reciprocal relationship of nonlinear elastic parameters evaluated from multiple transmitter-receiver pairs is then applied to locate the micro-damage. Experimental results on a damaged composite panel revealed that an accurate damage localisation was obtained using the normalised second order nonlinear parameter with a high signal-to-noise-ratio (∼11.2 dB), whilst the use of bicoherence coefficient provided high localisation accuracy with a lower signal-to-noise-ratio (∼1.8 dB). The maximum error between the calculated and the real damage location was nearly 13 mm. Unlike traditional linear ultrasonic techniques, the proposed nonlinear elastic multi-path reciprocal method allows detecting material damage on composite materials without a priori knowledge of the ultrasonic wave velocity nor a baseline with the undamaged component.
- Composite materials
- Nonlinear damage localization
- Structural health monitoring (SHM)
ASJC Scopus subject areas
- Acoustics and Ultrasonics
1/05/16 → 31/10/17
Project: Research council
EXTREME - EXTREME Dynamic Loading - Pushing the Boundaries of Aerospace Composite Material Structures
Meo, M. & Ciampa, F.
1/09/15 → 31/08/19
Project: EU Commission
Boccardi, S., Calla, D. B., Ciampa, F., & Meo, M. (2018). Nonlinear elastic multi-path reciprocal method for damage localisation in composite materials. Ultrasonics, 82, 239-245. https://doi.org/10.1016/j.ultras.2017.09.001