Decomposition and Reconstitution of STDR Signals Using Wavelet Transform for Location Estimation of Cable Fault 


Vol. 50,  No. 1, pp. 134-141, Jan.  2025
10.7840/kics.2025.50.1.134


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  Abstract

In this paper, we propose decomposition and reconstitution techniques of STDR signals to improve the estimation performance of a fault location in live wire systems. The discrete wavelet transform is used for signal decomposition and the logistic regression is used for obtaining the reconstitution weights. The location of a cable fault is estimated using the correlation function of the reconstituted STDR signal and the injected sequence signal in time domain. The estimation performances of the fault location using the proposed wavelet-based methods are compared with those using the preceding EMD(empirical mode decomposition)-based methods in live wire systems. The results demonstrate that unnecessary components can be effectively removed and important components can be combined to increase the accuracy of location estimation by assigning appropriate weights to the detail components of the fault signals decomposed using the wavelet transform.

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[IEEE Style]

W. G. Kim, K. H. Park, S. H. Bang, S. R. Park, "Decomposition and Reconstitution of STDR Signals Using Wavelet Transform for Location Estimation of Cable Fault," The Journal of Korean Institute of Communications and Information Sciences, vol. 50, no. 1, pp. 134-141, 2025. DOI: 10.7840/kics.2025.50.1.134.

[ACM Style]

Woo Gyun Kim, Ki Hyun Park, Sang Hyuk Bang, and So Ryoung Park. 2025. Decomposition and Reconstitution of STDR Signals Using Wavelet Transform for Location Estimation of Cable Fault. The Journal of Korean Institute of Communications and Information Sciences, 50, 1, (2025), 134-141. DOI: 10.7840/kics.2025.50.1.134.

[KICS Style]

Woo Gyun Kim, Ki Hyun Park, Sang Hyuk Bang, So Ryoung Park, "Decomposition and Reconstitution of STDR Signals Using Wavelet Transform for Location Estimation of Cable Fault," The Journal of Korean Institute of Communications and Information Sciences, vol. 50, no. 1, pp. 134-141, 1. 2025. (https://doi.org/10.7840/kics.2025.50.1.134)
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pISSN : 1226 - 4717
eISSN : 2287 - 3880