In the high voltage domain, the Corona discharge represents one of the most disturbing problems for the companies that transport electricity. Corona discharge is an electrical discharge brought on by the ionization of a fluid surrounding a conductor that is electrically energized. To combat this phenomenon it is necessary to keep high voltage power lines under surveillance and try to maintain losses at a reasonable value. The best manner to do this thing is by using a fixed-wing unmanned aircraft vehicle having on board the necessary sensors for detecting Corona discharge. In this paper we will focus on extracting and detecting high voltage lines from the images received from an UAV which will be analyzed using a number ofMATLAB functions. To detect lines into an image the Radon transformwill be used which is an integral transform that maps a function to its integrals over lines.
This paper describes the implementation and experimental validation of a new 3D miniaturized inertial navigator developed for human indoor and outdoor monitoring applications. Accuracy is a major concern, especially during GPS outages and indoor applications. In order to increase the inertial navigation system (INS) standalone operation period with acceptable accuracy during the GPS absence, signals received from sensors are filtered for reducing positioning errors. For validation, data achieved from the proposed navigator was compared with data achieved from a GPS/INS integrated navigator, both devices being used as remote systems. Unlike in our previous research, the case of the bi-dimensional model, when we managed to develop an optimizing tuning method for achieving the optimum level of decomposition of the Wavelet filter for data achieved from two channels, the attitude channel and the position channel, but not simultaneously, we are currently extending our research aiming to tune simultaneously data achieved from six detection channels, three accelerometers and three gyros.
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