首页> 外文期刊>Optical fiber technology >Fiber grating loop ring-down strain sensors using overlap spectrum demodulation and machine learning algorithm
【24h】

Fiber grating loop ring-down strain sensors using overlap spectrum demodulation and machine learning algorithm

机译:Fiber grating loop ring-down strain sensors using overlap spectrum demodulation and machine learning algorithm

获取原文
获取原文并翻译 | 示例
           

摘要

The fiber grating loop ring-down (FGLRD) can be used in strain sensors to reduce costs and enhance system sensitivity. Introducing the overlap spectrum demodulation technology in the FGLRD can improve the system's linearity and expand the measurement range. However, there is always strong amplified spontaneous emission (ASE) noise owing to erbium-doped fiber amplifiers (EDFAs) in the FGLRD structure. The noise increases the difficulty of detecting the output ring-down spectrum and reduces the detection accuracy. This study proposes a machine learning algorithm for data processing of chirped FGLRD strain sensors based on overlap spectrum demodulation. It uses a global average pooling one-dimensional convolutional neural network algorithm to construct a data recognition model. The experimental results show that the method can improve the recognition accuracy and reduce the recognition errors caused by ASE noise compared to the conventional ring-down spectral peak detection method. The model accuracy was 100 for the training and test sets and 98 for the validation set. The loss value was close to 0.06, and the recognition time was approximately 0.5 ms.

著录项

获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号