Research on Thermal Image Enhancement for Detecting Early Mechanical Damage in Apple

Zhou, Jianmin; Zhou, Qing; Shu, Lili; Xu, Dongdong

doi:10.1166/sl.2011.1379

Cited by 2 publications

(1 citation statement)

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“…However, the above requirements and the adaptation to the composite materials reduce the number of methods that can be used. Currently, the adapted methods are based on infrared thermography, acoustical emission, EMIR (ElectroMagnetic InfraRed) or microwave imagery [1][2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Damage in Composite Material: A Microwave Detection

Rossignol

Thionnet

2014

KEM

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In the field of the transport, the increase of the security rule recommends to a periodic control of the structure to detect damage due to mechanical loadings. Now, current materials, used in the case of transport applications, are the composite materials. The methods, to control these materials or composite structures, need to be low cost, non-destructive, in-situ and swiftness as far as possible. The scientific literature reports many methods to control the damage in composite materials and structures. However the above requirements and the adaptation to composite materials reduce the number of methods that can be used. Currently, the adapted methods are based on infrared thermography, acoustical emission, EMIR (ElectroMagnetic InfraRed) or microwave imagery. We present an innovative non-destructive method of detecting damages in composite materials. The method is based on the observation and analysis of the modification in dielectric material resulting from damage. The originality of this method is that the diagnostic is obtained by using a microstrip resonator at microwave frequencies. The feasibility of the method is demonstrated by the detection of a fibre break into an unidirectional composite submitted to a flexural loading. The fibre break is the damage to detect. The perspective of this work is to develop a quantification and a localization of damages.

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Section: Introductionmentioning

confidence: 99%