Transmission line fault classification under high noise in signal (Record no. 17518)

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fixed length control field a
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control field OSt
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control field 20220913151834.0
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fixed length control field 220913b xxu||||| |||| 00| 0 eng d
040 ## - CATALOGING SOURCE
Original cataloging agency AIKTC-KRRC
Transcribing agency AIKTC-KRRC
100 ## - MAIN ENTRY--PERSONAL NAME
9 (RLIN) 17888
Author Mukherjee, Alok
245 ## - TITLE STATEMENT
Title Transmission line fault classification under high noise in signal
Remainder of title : a direct PCA-threshold-based approach
250 ## - EDITION STATEMENT
Volume, Issue number Vol.103(1), Feb
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. New York
Name of publisher, distributor, etc. Springer
Year 2022
300 ## - PHYSICAL DESCRIPTION
Pagination 197-211p.
520 ## - SUMMARY, ETC.
Summary, etc. Transmission line faults are most common in long distance power transmission system. Classification of faults is crucial in removal of the faulted line from supply end in order to discontinue the unwanted flow of power through the fault point. The proposed work illustrates a simple method of classification of faults in transmission line using Principal Component Analysis- (PCA) based approach. The proposed method uses to extract fault features in terms of Principal Component Index (PCI), followed by a threshold-based analysis of the PCI values. Development of two threshold values helps in segregating the three different levels of fault disturbance in terms of the PCI values, thereby, developing fault signatures for classification. A 150 km transmission line has been modeled in EMTP for simulating the different fault prototypes, followed by analysis in MATLAB environment. Fault locations and fault resistances are also varied in order to enhance robustness in the classifier. Most importantly, noise level of the fault signals is varied in wide practical range; especially, signal to noise ratio (SNR) is increased to 15 dB to examine the robustness of the proposed classifier under severe noisy condition, where the same is found to produce 99.78% classifier accuracy using half cycle post-fault line currents only; thus, establishing the insensitivity of PCA toward noise.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
9 (RLIN) 4642
Topical term or geographic name entry element Humanities and Applied Sciences
700 ## - ADDED ENTRY--PERSONAL NAME
9 (RLIN) 17891
Co-Author Kundu, Palash Kumar
773 0# - HOST ITEM ENTRY
Title Journal of the institution of engineers (India): Series B
International Standard Serial Number 2250-2106
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URL https://link.springer.com/article/10.1007/s40031-021-00601-w
Link text Click here
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Koha item type Articles Abstract Database
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Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Permanent Location Current Location Shelving location Date acquired Barcode Date last seen Price effective from Koha item type
          School of Engineering & Technology School of Engineering & Technology Archieval Section 2022-09-13 2022-1586 2022-09-13 2022-09-13 Articles Abstract Database
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