Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.674476
Title: Water tree dynamics and their scaling with field and frequency by analysis of time-series population data
Author: Houlgreave, John A.
Awarding Body: University of Leicester
Current Institution: University of Leicester
Date of Award: 1996
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Abstract:
Water trees are a major form of degradation in solid organic electrical insulation subject to high AC voltages and water. The work is aimed at developing a more rigorous approach to analysing water tree data from ageing experiments on practical insulation geometries. Such data is in the form of tree length distributions and time-increasing tree number densities. Tree inception statistics are directly accessible from the data, but the effects of growth are convolved with those of inception. An approach is developed for analysing the data to quantify aspects of both inception and growth. In particular, mean growth rates and distributions of growth times can be estimated. The distribution of inception times seems to be close to exponential. Analysis shows that the effects of varying the field on the dynamics of inception depend upon whether the voltage or the insulation thickness is being varied. Increasing the frequency or decreasing thickness increases the number of possible water tree sites but decreases the inception rate from an average site. Frequency accelerates inception in a non-linear manner. Increasing the voltage both increases the number of sites and the inception rates. At frequencies close to 1 kHz, the mean length of a tree increases with the square root of growth time. Initial tree growth rates increase in a way that is consistent with a linear dependence on frequency. It is concluded that the approach developed can be applied to real data and is useful. It is expected that application of the approach to more extensive data sets would give rise to considerable advances in the empirical knowledge of the dependence of water treeing on various physical parameters which it is not possible to obtain using existing techniques.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.674476  DOI: Not available
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