A novel approach to the classification of the transient phenomena in power transformers using combined wavelet transform and neural network

IEEE Transactions on Power Delivery

Volumn 16, Issue 4, 2001, Pages 654-660

  Mao, Peilin L ^b   Aggarwal, Raj K ^a,b  

^a IEEE   (United Kingdom)

^b University of Bath   (United Kingdom)

Author keywords

Artificial neural network; Fault detection; Magnetizing inrush current; Power transformer; Wavelet transform

Indexed keywords

SPECTRAL ENERGIES;

ELECTRIC FAULT CURRENTS; ELECTRIC POWER DISTRIBUTION; FREQUENCY DOMAIN ANALYSIS; MAGNETIZATION; NEURAL NETWORKS; SIGNAL PROCESSING; SPECTRUM ANALYZERS; TIME DOMAIN ANALYSIS; TRANSFORMER PROTECTION; TRANSIENTS; WAVELET TRANSFORMS;

ELECTRIC TRANSFORMERS;

EID: 0035481582     PISSN: 08858977     EISSN: None     Source Type: Journal    
DOI: 10.1109/61.956753     Document Type: Article

References (13)

1. Digital relays improve protection of large transformers
2. A state-of-the-art review of transformer protection algorithms
3. Improved operation of differential protection of power transformers for internal faults
4. Design, implementation and testing of a micor-processor-based high-speed relay for detecting transformer winding faults
5. Neural-network-based algorithm for power transformer differential relays
6. Training an artificial neural network to discriminate between magnetizing inrush and internal fault
7. Improved operation of power transformer protection using artificial neural network
8. Experimental testing of the artificial neural network based protection of power transformers
9. Discrete wavelet analysis of power system transients
10. Transient power quality problems analyzed using wavelets
11. Multiresolution signal decomposition: A new tool for fault detection in power transformers during impulse tests
12. Analysis of transient phenomena in power transformers using wavelet transforms