Distributed optical fiber vibration sensor based on Sagnac interference in conjunction with OTDR

Pan, Chao; Liu, Xiaorui; Zhu, Hui; Shan, X.; Sun, Xiaohan

doi:10.1364/oe.25.020056

Cited by 29 publications

(14 citation statements)

References 14 publications

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“…The main difference from MZI is that the light propagating in two fibres (reference arm and sensing arm) are respectively reflected by two mirrors at the fibre ends. (c) Sagnac interference (SI) fibre sensor [130][131][132]. An SI fibre sensor is formed by an optical fibre loop, as shown in Fig.…”

Section: Oi-based Fibre Vibration and Ultrasonic Sensormentioning

confidence: 99%

Review of optical fibre sensors for electrical equipment characteristic state parameters detection

et al. 2019

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Optical fibre sensing technology is a powerful method for long-term reliable sensing in harsh environments, which means it is particularly suitable for the detection of electrical equipment characteristic state parameters, including characteristic gases, abnormal vibration, ultrasonic produced by partial discharge, and abnormal temperature rise. This paper reviews several individual optical fibre sensors for different state parameters detection, discusses the advantages, limitations and possible improvement methods, and finally presents the most promising optical fibre sensor for each state parameter.

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Section: Oi-based Fibre Vibration and Ultrasonic Sensormentioning

confidence: 99%

Review of optical fibre sensors for electrical equipment characteristic state parameters detection

et al. 2019

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“…The distributed optical fiber vibration sensing (DVS) technique can continuously measure a vibration signal along with an optical fiber [1][2][3][4]. It has the advantages of simple structure, small volume, corrosion resistance, electromagnetic interference resistance, and high sensitivity.…”

Section: Introductionmentioning

confidence: 99%

High-Accuracy Event Classification of Distributed Optical Fiber Vibration Sensing Based on Time–Space Analysis

Zhao¹,

Wu²,

Zhao³

2022

Sensors

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Distributed optical fiber vibration sensing (DVS) can measure vibration information along with an optical fiber. Accurate classification of vibration events is a key issue in practical applications of DVS. In this paper, we propose a convolutional neural network (CNN) to analyze DVS data and achieve high-accuracy event recognition fully. We conducted experiments outdoors and collected more than 10,000 sets of vibration data. Through training, the CNN acquired the features of the raw DVS data and achieved the accurate classification of multiple vibration events. The recognition accuracy reached 99.9% based on the time–space data, a higher than used time-domain, frequency–domain, and time–frequency domain data. Moreover, considering that the performance of the DVS and the testing environment would change over time, we experimented again after one week to verify the method’s generalization performance. The classification accuracy using the previously trained CNN is 99.2%, which is of great value in practical applications.

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“…Of course, the above three methods can only realize the location of single point intrusion. Therefore, in order to realize simultaneous location of multi-point intrusion, a scheme combining Sagnac and OTDR based on pulse light is proposed in [22].…”

Section: Introductionmentioning

confidence: 99%

Intrusion Location Technology of Sagnac Distributed Fiber Optical Sensing System Based on Deep Learning

Zhuo

Wan

et al. 2021

IEEE Sensors J.

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For distributed fiber optical sensing based on Sagnac effect, the intrusion is usually located by notch frequency. However, the notch spectrum is the comprehensive result of the intrusion, so when multiple disturbances simultaneously intrude from different positions of the sensing fiber, it is impossible to establish a mathematical expression between the intrusion position and the notch frequency, this leads to the problem of multi-point intrusion localization. Therefore, in this paper, deep learning technology is used to locate multiple disturbing points in Sagnac distributed optical fiber sensing system, and the related specific technologies of deep learning appling to sagnac distributed optical fiber sensing are studied. First, according to the characteristics of the system, a network structure based on the regression probability distribution is proposed, second, a loss function is constructed. The results show that the trained model can realize the positioning of multiple and single intrusion points.

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Distributed optical fiber vibration sensor based on Sagnac interference in conjunction with OTDR

Cited by 29 publications

References 14 publications

Review of optical fibre sensors for electrical equipment characteristic state parameters detection

Review of optical fibre sensors for electrical equipment characteristic state parameters detection

High-Accuracy Event Classification of Distributed Optical Fiber Vibration Sensing Based on Time–Space Analysis

Intrusion Location Technology of Sagnac Distributed Fiber Optical Sensing System Based on Deep Learning

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