Real-time classification for Φ-OTDR vibration events in the case of small sample size datasets

Yang N.; Zhao Y.; Wang F.Chen J.

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Real-time classification for Φ-OTDR vibration events in the case of small sample size datasets

机译：Real-time classification for Φ-OTDR vibration events in the case of small sample size datasets

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? 2022 The Author(s)Efficient classification of vibration signals detected by phase-sensitive optical time domain reflectometer (Φ-OTDR) based on small samples is an effective method to reduce the false alarm rate without GPU or large data sets. This paper proposes a fiber optic system vibration event recognition method based on a combination of image segmentation pre-processing, texture, statistical, morphological feature extraction, and weighted support vector machine (WSVM), which can effectively classify-five types of vibration events in high-speed railway perimeter intrusion detection with small sample data and no parallel processing units. Erosion and dilation operations are applied to vibration signal image feature enhancement in image pre-processing. The vibration signal region and background are separated by the maximum inter-class variance method, then 35 features of the vibration signal region are calculated and finally employed to construct a WSVM. Experiments show that the method achieves 99 FPS and 98.8 accuracy on the test set with 330 vibration images as the training set to build the model without GPU and in the presence of interference signals. It provides a generalized Φ-OTDR vibration event recognition method for small samples.

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《Optical fiber technology》 |2023年第3期|103217.1-103217.12|共12页
作者
Yang N.; Zhao Y.; Wang F.Chen J.;
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作者单位

Data and Target Engineering Institute PLA Strategic Support Force Information Engineering UniversityData and Target Engineering Institute PLA Strategic Support Force Information Engineering University||Zhengzhou Xinda Institute of Advanced Technology;

||Data and Target Engineering Institute PLA Strategic Support Force Information Engineering University;

Zhengzhou Xinda Institute of Advanced TechnologyResearch Institute for National Defense Engineering of Academy of Military Science PLA;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种英语
中图分类
关键词
Features extraction; Fiber optic system; Intrusion detection; Weighted support vector machine; Φ-OTDR;

Real-time classification for Φ-OTDR vibration events in the case of small sample size datasets

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