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Impact Localization System by Using FBG Sensors and Extreme Learning Machine Algorithm

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Abstract:

Aluminum alloy structure impact localization system by using fiber Bragg grating (FBG) sensors and impact localization algorithm were investigated. The impact localization method was proposed based on Extreme Learning Machine (ELM). Cross-correlation analysis method was used to extract the impact signal time difference. And ELM was used to realize impact localization. ELM model’s input was signal time difference and the output was the impact location. At last, FBG impact localization system was established. In aluminum alloy plate’s 500mm*500mm*2mm experiment area, the FBG impact localization system was used to identify the impact location. The experimental results showed that the impact location abscissa and ordinate localization errors were both less than 10mm. The research results provided an alternative method for the aluminum alloy material structure impact localization.

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Info:

Periodical:

Applied Mechanics and Materials (Volume 740)

Pages:

664-667

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.740.664

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Online since:

March 2015

Authors:

Ming Shun Jiang*, Xiang Yang Li, Shi Cheng Wang, Shi Zeng Lu, Yin Qing, De Hua Shu, Yuan Ming Yuan, Yu Lei Zhao, Qing Mei Sui

Keywords:

Cross-Correlation Analysis, Extreme Learning Machine, Fiber Bragg Grating, Impact Localization

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© 2015 Trans Tech Publications Ltd. All Rights Reserved

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