Análise de sensibilidade do método dos vetores de energia dos centroides das sub-bandas espectrais aplicado ao monitoramento de isoladores poliméricos.

Abstract

In this work, a sensitivity analysis applied to a monitoring and predicting technique of the operational condition polymeric insulators is proposed. The technique is based on the acoustic inspection of ultrasonic noises coming from the electrical discharges on the surface of insulators. For this purpose, tests were carried out in the laboratory with 230 kV polymeric insulators, extracted from a transmission line and with different degradation levels. The Spectral Subband Centroid Energy Vectors algorithm was used to extract attributes and process the ultrasonic noise signals. This algorithm splits the frequency spectrum into a number of overlapping subbands, locates the centroids of each subband and calculates the energy in the proximity of each centroid. Aiming to support the decision-making, was employed an artificial neural network capable of separating into classes the insulators degradation levels. Thus, it made possible to identify and distinguish accurately the energy vectors from cleaned insulators, polluted insulators and damaged insulators with success rates always above 80%. With these results, a sensitivity analysis was performed to choose which parameters and topologies of computational processes best suited to the proposed estimation of ultrasonic noise signals. The results form the basis for implementation of the method with a larger amount of samples insulators, making it possible to statistically evaluate its applicability in the field.