Abstract
This paper aims to analyze the quality of insulation in high voltage underground cables XLPE using a prototype which classifies the following usual types of patterns of partial discharge (PD): (1) internal PD, (2) superficial PD, (3) corona discharge in air, and (4) corona discharge in oil, in addition to considering two new PD patterns: (1) false contact and (2) floating ground. The tests and measurements to obtain the patterns and study cases of partial discharges were performed at the Testing Laboratory Equipment and Materials (LEPEM) of the Federal Electricity Commission of Mexico (CFE) using a measuring equipment LDIC and norm IEC60270. To classify the six patterns of partial discharges mentioned above a Probabilistic Neural Network Bayesian Modified (PNNBM) method having the feature of using a large amount of data will be used and it is not saturated. In addition, PNN converges, always finding a solution in a short period of time with low computational cost. The insulation of two high voltage cables with different characteristics was analyzed. The test results allow us to conclude which wire has better insulation.
Highlights
The analysis of partial discharges (PDs) is important to determining the quality of insulation in high voltage equipment
This paper aims to analyze the quality of insulation in high voltage underground cables XLPE using a prototype which classifies the following usual types of patterns of partial discharge (PD): (1) internal PD, (2) superficial PD, (3) corona discharge in air, and (4) corona discharge in oil, in addition to considering two new PD patterns: (1) false contact and (2) floating ground
The construction of a prototype is proposed to obtain the following patterns of partial discharges: (1) internal PD, (2) superficial PD, (3) corona discharge in air, and (4) corona discharge in oil, considering two new PD patterns: (1) false contact and (2) floating ground
Summary
The analysis of partial discharges (PDs) is important to determining the quality of insulation in high voltage equipment. It produces internal DPs using a filtering system that can introduce errors at the moment of classification and the DPs transform them into energy for the interpretation and evaluation [1] They perform different types of internal and external patterns: corona in oil, corona in air, superficial, and internal, but the results are not validated with actual measurements [3]. In reference [11] the authors present a type of sensor to determine the characteristics of PD using a prototype to classify (1) internal PD, superficial PD, corona in air, and corona in oil In this case in the present research work the quality of insulation in high voltage underground XLPE cables from different manufacturers was tested. The methodology was implemented in two different manufactures of XLPE cables which is able to determine the quality of the insulation in an acceptable way
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