DocumentCode
2791945
Title
Estimating the maximum length of water trees using extreme value statistics
Author
Ildstad, E. ; Sletbak, J. ; Bruaset, A.
Author_Institution
Norwegian Inst. of Technol., Trondheim, Norway
fYear
1991
fDate
8-12 Jul 1991
Firstpage
226
Abstract
The authors discuss a statistical evaluation method for water tree analysis, where only the maximum tree length found in any particular cable sample is measured. The physical justification for the use of extreme value statistics is presented. By treating the maximum tree length as a stochastic variable it is possible to estimate the most probable length of the longest tree in a given length of a cable. The validity of this method was tested on results from water-tree examination of both service and laboratory aged XLPE (cross-lined polyethylene) cables. It is stressed that, in order to obtain stochastic variables of extreme tree lengths, the examined length of a cable has to be adjusted in accordance with the width and density of the water trees. The first asymptotic and the Weibull type distribution functions have been examined. In the case when the water trees exceed about 75% of the insulation wall, the limited Weibull type of distribution may give a better extrapolation than the unlimited first asymptotic distribution function
Keywords
cable insulation; electric breakdown of solids; organic insulating materials; polymers; power cables; statistical analysis; Weibull type distribution functions; asymptotic distribution function; extreme value statistics; laboratory aged XLPE; maximum tree length; power cable insulation; service aged XLPE; stochastic variable; water tree analysis; Aging; Distribution functions; Laboratories; Length measurement; Particle measurements; Power cables; Statistics; Stochastic processes; Testing; Trees - insulation;
fLanguage
English
Publisher
ieee
Conference_Titel
Properties and Applications of Dielectric Materials, 1991., Proceedings of the 3rd International Conference on
Conference_Location
Tokyo
Print_ISBN
0-87942-568-7
Type
conf
DOI
10.1109/ICPADM.1991.172022
Filename
172022
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