Vibration signals recognition for stay cables based on EMD with binary image and modified LeNet-5

Zicong Cao; Zhennan You; Youliang Jiang; Yan Wang

doi:10.1117/12.2659677

30 November 2022 Vibration signals recognition for stay cables based on EMD with binary image and modified LeNet-5

Zicong Cao, Zhennan You, Youliang Jiang, Yan Wang

Proceedings Volume 12456, International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP 2022); 124562I (2022) https://doi.org/10.1117/12.2659677
Event: International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP 2022), 2022, Qingdao, China

Abstract

Because the vibration signals of cable reflect the dynamic characteristics of the cable-stayed cable, it is vital to identify and analyze the vibration signals of cable in bridge health monitoring. Currently, there is little research on the vibration signals of stay cables using pattern recognition algorithms. In this work, we proposed a pattern recognition algorithm combining empirical mode decomposition (EMD) with binary image and modified LeNet-5 to analyze cable vibration signals. Experimental results show that this method has good anti-noise performance and is effective for vehicle load identification.

Citation Download Citation

Zicong Cao, Zhennan You, Youliang Jiang, and Yan Wang "Vibration signals recognition for stay cables based on EMD with binary image and modified LeNet-5", Proc. SPIE 12456, International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP 2022), 124562I (30 November 2022); https://doi.org/10.1117/12.2659677

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