Laser & Optoelectronics Progress, Volume. 58, Issue 7, 0706006(2021)
Feature Extraction Method Based on FDM Energy Entropy and its Application on Optical Fiber Vibration Recognition
Traditional signal-decomposition methods require manual setting of the basis function, which cause uncertainty and other problems. Accordingly, a self-driven Fourier decomposition method (FDM) can be used for signal processing and a feature extraction and recognition method based on FDM energy entropy is proposed in this paper. First, FDM decomposition is performed on the vibration signal to obtain several Fourier intrinsic band functions. The signal is then reconstructed based on the autocorrelation principle, and the signal FDM energy entropy feature is extracted. Finally, the fused feature vectors are sent to a support vector machine for training, and damaging vibrations are identified. Experimental results show that the proposed method can correctly identify different types of vibration signals with high accuracy. This method will enable improved recognition of damaging vibrations in optical fiber prewarning systems, thus aiding the development of pipeline protection technology.
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Hongquan Qu, Bingbing Wei, Zheng Zhang, Zhiyong Sheng. Feature Extraction Method Based on FDM Energy Entropy and its Application on Optical Fiber Vibration Recognition[J]. Laser & Optoelectronics Progress, 2021, 58(7): 0706006
Category: Fiber Optics and Optical Communications
Received: Jul. 13, 2020
Accepted: Sep. 18, 2020
Published Online: Apr. 25, 2021
The Author Email: Sheng Zhiyong (szy1183@ncut.edu.cn)