0000000001000954
AUTHOR
G. Mirelli
PD recognition by means of statistical and fractal parameters and a neural network
A novel partial discharge (PD) defect identification method is described. Starting with PD data on different families of specimens, a suitable set of parameters are determined and then used as input variables to a neural network for the purpose of identifying the defects within the insulation. In this procedure the statistical Weibull analysis is performed on PD pulse amplitude histograms to obtain the scale parameter /spl alpha/ and the shape parameter /spl beta/. Thereafter, the two statistical operators (skewness and kurtosis) and two fractal parameters (fractal dimension and lacunarity) are evaluated from the PD phase on the discharge epoch histogram and from the 3 dimensional (pulse am…
Energy load Behaviours of Sicilian Hotel: methods for reducing the annual consumptions of bungalow hotels in the Mediterranean area
Starting from the analysis of the energy consumption of some typical Sicilian hotels, it has been possible to assess their annual energy load behaviours, by source type. In addition, it has been also developed a simple model of the annual consumption, by kind of energy load. This approach allowed the comparison of true load-type energy consumption with typical load-type benchmark values (e.g. lighting consumption). In turn, this allows the singling out of feasible methods for the reductions of the energy consumption; the found solutions take into account three fundamental issues: energy, economy and environment. Analysed buildings are represented by typical hotels of the Mediterranean area;…