Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.632329
Title: Three-dimensional imaging and analysis of electrical trees
Author: Schurch Brandt, Roger
ISNI:       0000 0004 5360 4043
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 2014
Availability of Full Text:
Access from EThOS:
Access from Institution:
Abstract:
Electrical trees are micrometre-size tubular channels of degradation in high voltage polymeric insulation, a precursor to failure of electrical power plant. Hence, electrical trees critically affect the reliability of power systems and the performance of new insulation designs. Imaging laboratory-grown electrical trees has been an important tool for studying how trees develop. Commonly, electrical trees prepared in transparent or translucent polymers are imaged using traditional optical methods. Consequently, most of the analysis has been based on two-dimensional (2D) images of trees, thus, valuable information may be lost. However, electrical trees are complex interconnected structures that require a tree-dimensional (3D) approach for more complete analysis. This thesis investigates a method for imaging and analysis of electrical trees to characterise their 3D structure and provide a platform for further modelling. Laboratory created electrical trees were imaged using X-ray Computed Tomography (XCT) and Serial Block-Face Scanning Electron Microscopy (SBFSEM), 3D imaging techniques that provide sub-micrometre spatial resolution. Virtual replicas of the trees, which are the 3D geometrical models representing the real electrical trees, were generated and new indices to characterise the 3D structure of electrical trees were developed. These parameters were indicative of differences in tree growth and thus, they can be used to investigate patterns and classify the structure of electrical trees. The progression of the tree was analysed using cross-sections of the tree that are orthogonal to the growth: the number of tree channels and area covered by them were measured. The fractal dimension of the tree was calculated from the 3D model and from the 2D projections, the latter being lower for all the tree-type structures studied. Parameters from the skeleton of the tree such as number of nodes, segment length, tortuosity and branch angle were measured. Most of the mean segment lengths ranged 6-13 µm, which is in accordance to the 10µm proposed by various tree-growth models. The capabilities of XCT and SBFSEM imaging techniques were evaluated in their application to electrical trees. Bush and branch trees, including early-growth electrical trees (of length 20-40 µm), were analysed and compared using the comprehensive tool of visualisation and characterisation developed. A two-stage tree-growth experiment was conducted to analyse the progression and development of tree branches using XCT: tree channels after the second stage of growth were wider than after the first, while the fractal dimension remained the same. The capabilities of XCT and SBFSEM were tested for imaging electrical trees in optically-opaque materials such as micro and nano-filled epoxy compounds. The general structure of trees in epoxy filled up to 20 wt% micro-silica was observed using both techniques. The use of a virtual replica as the 3D geometrical model for the simulation of the electric field distribution using Finite Element Analysis (FEA) was preliminary explored. A combination of the imaging techniques is proposed for a more complete structural analysis of trees. It is believed that a great impact towards understanding electrical treeing will be achieved using the 3D technical platform developed in this thesis.
Supervisor: Not available Sponsor: CONICYT, Chile ; Federico Santa Maria Technical University, Chile
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.632329  DOI: Not available
Keywords: Electrical trees ; Three-Dimensional ; 3D ; X-ray Computed Tomography ; CT ; Serial Block-Face Scanning Electron Microscopy ; SBFSEM ; Imaging
Share: