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Fuzzy Similarity Classifier as Damage Index: Temperature Effect and Compensation

Abstract : The effects of ambient operational temperature variability on the measured dynamics response of structures have been addressed in several studies. It is intuitive that temperature variation may change the material/geometric properties or boundary conditions of a structure and therefore may affect the damage detection performance. Then we consider the ability of a Fuzzy similarity classifier as a feature when the temperature is changing, it will be shown that temperature change might have more significant effect rather than the simulated damage on this feature, which leads to false positive decisions. Therefore, it is vital to compensate the effect of temperature to achieve a desirable result. To do this, the temperature effect is compensated and it is shown the compensation increases the performance of damage detection using the Fuzzy similarity index. To support claims mentioned above, this work involves experiments with composite plate equipped with PZT transducers. To simulate the effect of temperature the specimen is subjected to temperature change between -25C and 60C.
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Submitted on : Wednesday, July 9, 2014 - 10:17:37 AM
Last modification on : Monday, November 16, 2020 - 3:56:17 PM
Long-term archiving on: : Thursday, October 9, 2014 - 11:19:20 AM


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  • HAL Id : hal-01021190, version 1



Fahit Gharibnezhad, Luis Eduardo Mujica, Jose Rodellar, Michael Todd. Fuzzy Similarity Classifier as Damage Index: Temperature Effect and Compensation. EWSHM - 7th European Workshop on Structural Health Monitoring, IFFSTTAR, Inria, Université de Nantes, Jul 2014, Nantes, France. ⟨hal-01021190⟩



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