Condition Monitoring of Instrumentation Cable Splices Using Kalman Filtering

Seung Jin Chang, Chun Ku Lee, Chun Kwon Lee, Yee Jin Han, Moon Kang Jung, Jin Bae Park, Yong June Shin

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)

Abstract

A linear chirp reflectometry with chirp stretching processing is used to detect and to locate low-voltage control and instrumentation cable splices and fault. Time delay information in the reflected signal is transformed to the instantaneous beat angular frequency by stretching process and the instantaneous beat angular frequency is estimated by Kalman smoother in order to obtain the high resolution time-frequency spectrum of the nonstationary signal. Based on the estimated instantaneous beat angular frequency, the magnitude and phase difference of the reflection coefficient are estimated by Kalman filtering. To verify the performance of the proposed method, comparative experiments are conducted to detect and to locate the splice under different conditions in comparison with traditional time-domain reflectometry method and the proposed method. In addition, to demonstrate the efficacy of the proposed method, the experiments are carried out for the assessment of state of the shunt and serial faults on cable under test. The location and reflection coefficient of a nominal, water submerged, an opened splice, shunt fault and serial fault (10Ω , 30 Ω , 50Ω , 70 Ω , 90 Ω , 1 kΩ) are estimated by the proposed method. The proposed method exhibits advantages in that it uses the pulse compression to improve the range resolution and SNR of reflectometer simultaneously, and the proposed technique can accurately assess the state of the fault, which is closed to short fault or open fault.

Original languageEnglish
Article number7226838
Pages (from-to)3490-3499
Number of pages10
JournalIEEE Transactions on Instrumentation and Measurement
Volume64
Issue number12
DOIs
Publication statusPublished - 2015 Dec 1

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

All Science Journal Classification (ASJC) codes

  • Instrumentation
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Condition Monitoring of Instrumentation Cable Splices Using Kalman Filtering'. Together they form a unique fingerprint.

Cite this