Distributed temperature detection of transformer windings with externally applied distributed optical fiber

Liu, Yunpeng; Yin, Junyi; Fan, Xiaozhou; Wang, Bowen

doi:10.1364/ao.58.007962

Cited by 10 publications

(5 citation statements)

References 19 publications

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“…A short-pulsed laser source of 1550 nm wavelength and pulse width 200 ns with 25 mW power is launched to the sensing fibre. The Brillouin and Rayleigh powers are calculated using Equations ( 4) and (5), respectively, at the input end of the sensing fibre, as represented in Figure 1. A constant white Gaussian noise of variance 10 −7 W is used in numerical simulation process for 70 km sensing range.…”

Section: Numerical Simulation and Resultsmentioning

confidence: 99%

“…One of the major advantages in distributed fibre sensor over traditional point sensor is that it can be used as a real-time and continuous measurement system for monitoring the measurands. It is a high-tech instrument for real-time measurement of temperature field [5][6][7]. In the field of public safety and industrial process monitoring, it has become a new detection method.…”

Section: Introductionmentioning

confidence: 99%

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Sensing accuracy enhancement of long‐range distributed fibre‐optic temperature sensor using hybrid algorithm

Pradhan

2021

IET Science Measure & Tech

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This paper presents a long-range distributed fibre-optic temperature sensor with high sensing accuracy to monitor temperature using Brillouin scattering mechanism. Fourier deconvolution, Fourier wavelet regularised deconvolution, dichotomised singular value decomposition and hybrid algorithms were employed to measure the temperature of proposed sensor. Optical time domain reflectometry technique is used to extract the temperature profile for 70, 60 and 50 km sensing ranges. The improvement of temperature accuracy using hybrid algorithm is achieved for 70 km sensing distance. In order to extract temperature information, the numerical simulation process has been incorporated in the proposed long-range sensing system. Moreover, the temperature accuracy of the proposed system is obtained using Fourier deconvolution, Fourier wavelet regularised deconvolution, dichotomised singular value decomposition and hybrid algorithms for 70, 60 and 50 km sensing ranges. The simulation results show that the temperature accuracy is observed as 4.8 • K using hybrid algorithm compared to Fourier deconvolution algorithm that shows temperature accuracy as 14 • K at 70 km. In the proposed sensor, a spatial resolution of 20 m is observed for a sensing range of 70 km using hybrid algorithm. In addition, the denoising competence of the proposed hybrid algorithm is validated using 50 km optical time domain reflectometry backscattered trace observed experimentally. Further, a peak dynamic range improvement of optical time domain reflectometry backscattered trace as 3.91 dB is observed using hybrid algorithm.

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Section: Numerical Simulation and Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Sensing accuracy enhancement of long‐range distributed fibre‐optic temperature sensor using hybrid algorithm

Pradhan

2021

IET Science Measure & Tech

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“…The equation indicates that BS-based fibre sensor can also be used to detect distributed strain along the sensing fibre. (c) RS-based fibre temperature sensor [160][161][162][163][164]: Since Anti-Stokes RS is much more sensitive to temperature than Stokes RS, the ratio of Anti-Stokes and Stokes Raman-scattered light intensities provides valuable information on temperature perturbations, according to the equation [159]:…”

Section: Ss-based Fibre Temperature Sensormentioning

confidence: 99%

“…(c) RS‐based fibre temperature sensor [160–164]: Since Anti‐Stokes RS is much more sensitive to temperature than Stokes RS, the ratio of Anti‐Stokes and Stokes Raman‐scattered light intensities provides valuable information on temperature perturbations, according to the equation [159]:

I_{as} / I_{normals} = false(ν_{as} / ν_{normals} false)^{4} {normale}^{- h true \frac{c v}{k T}}

where I as and I s represent the intensity of Anti‐Stokes and Stokes Raman‐scattered light, respectively, ν as and ν s represent the frequency of Anti‐Stokes and Stokes Raman‐scattered light, respectively, h is the Planck constant, k is the Boltzmann constant, T is the Kelvin temperature, c is the light velocity in vacuo, v is Raman shift.…”

Section: Review On Optical Fibre Sensors For Electrical Equipment Cmentioning

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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“…At present, many transformer fault diagnosis methods have been proposed and practically implemented [7]. For instance, the temperature measurement [8], dissolved gasin-oil analysis (DGA) [9], dielectric response analysis [10], vibration analysis [11], partial discharge analysis (electrical and acoustic) [12,13], transfer function measurement [14], ultrasonic method and online short circuit impedance (SCI) [15]. All of these methods are significant.…”

Section: Introductionmentioning

confidence: 99%

Improved Winding Mechanical Fault Type Classification Methods Based on Polar Plots and Multiple Support Vector Machines

Liu

Zhao

Pang³

et al. 2020

IEEE Access

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The accurate and fast diagnosis of transformer winding deformation faults is of significance to power suppliers and utilities. An improved winding mechanical deformation fault classification method is proposed. In this study, the transformer frequency response data is used to draw polar plots, and then its texture features are extracted for fault classification. The classification model constructed by multiple support vector machines is successfully obtained and shows good classification effect. Besides, this paper uses an improved genetic algorithm based on the Emperor-Selective mating scheme and catastrophic operation, to optimize the parameters of support vector machine. The feasibility and accuracy of the proposed method are verified with experimental data obtained from a model transformer, and the proposed method is demonstrated to exhibit better performance compared with the traditional method.

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Distributed temperature detection of transformer windings with externally applied distributed optical fiber

Cited by 10 publications

References 19 publications

Sensing accuracy enhancement of long‐range distributed fibre‐optic temperature sensor using hybrid algorithm

Sensing accuracy enhancement of long‐range distributed fibre‐optic temperature sensor using hybrid algorithm

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

Improved Winding Mechanical Fault Type Classification Methods Based on Polar Plots and Multiple Support Vector Machines

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