Abstract

With the development of optical fiber distributed acoustic sensors (DAS), their application to seismic observation has become popular. We conducted DAS measurements from November 19 to December 2, 2019, using dark fiber of an ocean bottom cable seismic and tsunami observation system off the Sanriku coast in northeastern Japan and investigated seismic detection methods from the obtained strain rate data. We examined a new seismic detection method using a convolutional neural network, to the best of our knowledge, treating a frequency wavenumber spectrum of strain rate as an image. This method effectively captured a characteristic wave described as the T-phase in a sound fixing and ranging channel even with low signal-to-noise ratio data.

© 2023 Optica Publishing Group

Distributed fiber mountain seismic monitoring and steady-state analysis under natural earthquakes

Junqi Yang, Zhaoyong Wang, Jian Zhou, Xiuqing Song, Yifan Liu, Bingyan Wu, Luwei Shuai, Kang Ying, Lei Ye, Luqing Zhang, Qing Ye, and Haiwen Cai
Appl. Opt. 62(2) 342-347 (2023)

Pattern recognition in distributed fiber-optic acoustic sensor using an intensity and phase stacked convolutional neural network with data augmentation

Huan Wu, Bin Zhou, Kun Zhu, Chao Shang, Hwa-Yaw Tam, and Chao Lu
Opt. Express 29(3) 3269-3283 (2021)

Intensity and phase stacked analysis of a Φ-OTDR system using deep transfer learning and recurrent neural networks

Ceyhun Efe Kayan, Kivilcim Yuksel Aldogan, and Abdurrahman Gumus
Appl. Opt. 62(7) 1753-1764 (2023)

Fiber distributed acoustic sensing using convolutional long short-term memory network: a field test on high-speed railway intrusion detection

Zhongqi Li, Jianwei Zhang, Maoning Wang, Yuzhong Zhong, and Fei Peng
Opt. Express 28(3) 2925-2938 (2020)

Spectrum classification using convolutional neural networks for a mini-camera detection system

Chun Liu, Changming Zhao, Haiyang Zhang, Zilong Zhang, Zitao Cai, and Zhipeng Li
Appl. Opt. 58(33) 9230-9239 (2019)