An energy ratio feature extraction method for optical fiber vibration signal

Autor: Zhiyong Sheng, Xinyan Zhang, Yanping Wang, Weiming Hou, Dan Yang
Jazyk: angličtina
Rok vydání: 2017
Předmět:
Zdroj: Photonic Sensors, Vol 8, Iss 1, Pp 48-55 (2017)
Druh dokumentu: article
ISSN: 1674-9251
2190-7439
DOI: 10.1007/s13320-017-0478-1
Popis: Abstract The intrusion events in the optical fiber pre-warning system (OFPS) are divided into two types which are harmful intrusion event and harmless interference event. At present, the signal feature extraction methods of these two types of events are usually designed from the view of the time domain. However, the differences of time-domain characteristics for different harmful intrusion events are not obvious, which cannot reflect the diversity of them in detail. We find that the spectrum distribution of different intrusion signals has obvious differences. For this reason, the intrusion signal is transformed into the frequency domain. In this paper, an energy ratio feature extraction method of harmful intrusion event is drawn on. Firstly, the intrusion signals are pre-processed and the power spectral density (PSD) is calculated. Then, the energy ratio of different frequency bands is calculated, and the corresponding feature vector of each type of intrusion event is further formed. The linear discriminant analysis (LDA) classifier is used to identify the harmful intrusion events in the paper. Experimental results show that the algorithm improves the recognition rate of the intrusion signal, and further verifies the feasibility and validity of the algorithm.
Databáze: Directory of Open Access Journals
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