Partial discharge pattern analysis using PCA and back-propagation artificial neural network for the estimation of size and position of metallic particle adhering to spacer in GIS

Electrical Engineering

Volumn 98, Issue 1, 2016, Pages 29-42

  Khan, Yasin ^a  

^a KING SAUD UNIVERSITY   (Saudi Arabia)

Author keywords

Artificial neural network (ANN); GIS; Partial discharge; Particle size and position estimation; Principal component analysis (PCA)

Indexed keywords

BACKPROPAGATION; DATA HANDLING; GEOGRAPHIC INFORMATION SYSTEMS; METALLIC COMPOUNDS; NEURAL NETWORKS; PARTIAL DISCHARGES; PARTICLE SIZE; PARTICLE SIZE ANALYSIS; PATTERN RECOGNITION;

BACK PROPAGATION ARTIFICIAL NEURAL NETWORK (BPANN); BACK-PROPAGATION ARTIFICIAL NEURAL NETWORK; GAS INSULATED SUBSTATIONS; METALLIC PARTICLES; PARTIAL DISCHARGE (PDS); PARTIAL DISCHARGE PATTERN; RELIABILITY IMPROVEMENT; SIZE AND POSITION;

PRINCIPAL COMPONENT ANALYSIS;

EID: 84957438471     PISSN: 09487921     EISSN: 14320487     Source Type: Journal    
DOI: 10.1007/s00202-015-0343-4     Document Type: Article

References (25)

1. Anis H (1990) Gas-insulated switchgear. In: Khalifa M (ed) High voltage engineering: theory and practice. Marcel Dekker Inc, New York, pp 243–273
2. Bolin P (2007) Gas-insulated substations. In: McDonald JD (ed) Electric power substations engineering. Taylor & Francis Group, LLC, Boca Raton
3. Jain HS (2007) Gas-insulated sub-station/switchgear (GIS). In: Limited BHE (ed) Handbook of switchgears. McGraw-Hill, New York
4. Morcos MM et al (2000) Insulation integrity of GIS/GITL systems and management of particle contamination. IEEE Electr Insul Mag 16(5):25–37
5. Okubo H et al (2008) Partial discharge detection techniques under the condition of metallic particle adhering to solid spacer in SF6. In: Annual report conference on electrical insulation and dielectric phenomena (CEIDP), 26–29 Oct, pp 395-399
6. Kanako N et al (2008) Particle size identification in GIS by ultra high speed measurement of partial discharge. In: International conference on condition monitoring and diagnosis (CMD), 21–24 April, pp 443–447
7. Hayakawa N et al (2008) Dependence of partial discharge characteristics at spacer surface on particle size in SF6 gas insulated system. In: International conference on condition monitoring and diagnosis (CMD), 21–24 April, pp 46–50
8. Negara Y et al (2007) AC particle-triggered corona discharge in low pressure SF6 gas. IEEE Trans Dielectr Electr Insul 14(1):91–100
9. Sahoo NC, Salama MMA, Bartnikas R (2005) Trends in partial discharge pattern classification: a survey. IEEE Trans Dielectr Electr Insul 12(2):248–264
10. Kreuger FH, Gulski E, Krivda A (1993) Classification of partial discharges. IEEE Trans Electr Insul 28(6):917–931
11. Hozumi N, Okamoto T, Imajo T (1992) Discrimination of partial discharge patterns using a neural network. IEEE Trans Electr Insul 27(3):550–556
12. Suzuki H, Endoh T (1992) Pattern recognition of partial discharge in XLPE cables using a neural network. IEEE Trans Electr Insul 27(3):543–549
13. Kranz HG (1993) Diagnosis of partial discharge signals using neural networks and minimum distance classification. IEEE Trans Electr Insul 28(6):1016–1024
14. Gulski E, Krivda A (1993) Neural networks as a tool for recognition of partial discharges. IEEE Trans Electr Insul 28(6):984–1001
15. Jung SY et al (2007) Discrimination of insulation defects in a gas insulated switchgear (GIS) by use of a neural network based on a chaos analysis of partial discharge (CAPD). J Electr Eng Technol 2(1):118–122
16. Khan Y, Budiman FN, Beroual A, Malik NH, Al-Arainy AA (2013) The estimation of size and position of contaminating particle adhering to the insulating spacer surface in gas insulated systems. Eur Phys J Appl Phys 62:20801p1–20801p11
17. Budiman FN, Khan Y, Beroual A, Malik NH, Al-Arainy AA (2013) Utilization of artificial neural network for the estimation of size and position of metallic particle adhering to spacer in GIS. IEEE Trans Dielectr Electr Insul 20(6):2143–2151
18. Danikas MG, Gao N, Aro M (2003) Partial discharge recognition using neural networks: a review. Electr Eng (Archiv fur Elektrotechnik) 85(2):87–93
19. Gulski E, Kreuger FH (1992) Determination of discharge sources by analysis of discharge quantities as a function of time. In: Conference record of the IEEE international symposium on electrical insulation, 7–10 Jun, pp 397–400
20. Karhunen J, Joutsensalo J (1995) Generalizations of principal component analysis, optimization problems and neural networks. Neural Netw 8(4):549–562
21. Babnik T, Aggarwal R, Moore P (2007) Data mining on a transformer partial discharge data using the self-organizing map. IEEE Trans Dielectr Electr Insul 14(2):444–452
22. Lai KX, Phung BT, Blackburn TR (2007) Partial discharge analysis using PCA and SOM. In: IEEE Lausanne Power Tech, 1–5 July, pp 2133–2138
23. Nguyen D, Widrow B (1990) Improving the learning speed of 2-layer neural networks by choosing initial values of the adaptive weights. In: International joint conference on neural networks, vol 3, pp 21–26
24. Yu H, Wilamowski BM (2011) Levenberg–Marquardt training. In: Industrial electronics handbook, vol. 5—intelligent systems. CRC Press, Boca Raton pp 12-1–12-15
25. Khan Y, Khan AA, Budiman FN, Beroual A, Malik NH, Al-Arainy AA (2014) Partial discharge pattern analysis using support vector machine for the estimation of size and position of metallic particle adhering to spacer in GIS. Electr Power Syst Res 116:391–398