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Application of instantaneous frequency estimation of sweep signal for localizing faults in a power cable

In this paper, we introduce a reflectometry which is used as localizing faults in an underground power cable. To increase the resolution and SNR, time-frequency domain reflectometry (TFDR) adopts the Gaussian enveloped linear chirp signal and Wigner-Ville distribution (WVD) based time-frequency cros...

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Main Authors: Chun Ku Lee, Ki Seok Kwak, Tae Sung Yoon, Jin Bae Park
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Ki Seok Kwak
Tae Sung Yoon
Jin Bae Park
description In this paper, we introduce a reflectometry which is used as localizing faults in an underground power cable. To increase the resolution and SNR, time-frequency domain reflectometry (TFDR) adopts the Gaussian enveloped linear chirp signal and Wigner-Ville distribution (WVD) based time-frequency cross-correlation (TFCC) method. However, the nonlinearity of WVD and the computational burden of 2D cross-correlation hinder the TFDR from being a field testing implementation. In order to reduce the nonlinearity and computational burden, we derive the second order time-varying AR model of Gaussian enveloped linear chirp signal and estimate the instantaneous frequency (IF) by using the weighted robust least squares (WRLS) estimator. Based on the estimated IF, the fault distance can be calculated. Computer simulations are conducted to verify the proposed method. The simulation result shows that the proposed method reduces the computational burden of time-frequency cross-correlation and the nonlinearity of WVD.
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To increase the resolution and SNR, time-frequency domain reflectometry (TFDR) adopts the Gaussian enveloped linear chirp signal and Wigner-Ville distribution (WVD) based time-frequency cross-correlation (TFCC) method. However, the nonlinearity of WVD and the computational burden of 2D cross-correlation hinder the TFDR from being a field testing implementation. In order to reduce the nonlinearity and computational burden, we derive the second order time-varying AR model of Gaussian enveloped linear chirp signal and estimate the instantaneous frequency (IF) by using the weighted robust least squares (WRLS) estimator. Based on the estimated IF, the fault distance can be calculated. Computer simulations are conducted to verify the proposed method. The simulation result shows that the proposed method reduces the computational burden of time-frequency cross-correlation and the nonlinearity of WVD.</abstract><pub>IEEE</pub><tpages>4</tpages></addata></record>
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subjects cable fault
Chirp
Estimation
Gaussian enveloped chirp signal
instantaneous frequency
Mathematical model
Noise
Power cables
Reflectometry
Time frequency analysis
time-varying AR model
Uncertainty
weighted robust least squares
title Application of instantaneous frequency estimation of sweep signal for localizing faults in a power cable
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