This article presents the Analysis of Partial Discharges using Neural Techniques. Rotating machines used in industry tend to have insulation failures caused by lack of maintenance and ignorance of their status. It is important to carry out periodic tests and continuous evaluations of the state of the insulation to guarantee the correct operation of the machines. One of the methods used to detect these faults is Partial Discharge. Which consist of small discharges produced in a portion of gas that is dissolved in the oil or dielectric that constitutes the insulation of electrical machines. In this research work, an analysis of two works developed around partial discharges is carried out, where artificial intelligence techniques have been implemented. The results showed a high effectiveness of neural networks to achieve the classification ofpartial discharges and contribute to the maintenance of high-power electrical equipment.
Published on 01/01/2020
DOI: 10.47460/athenea.v1i2.7Licence: CC BY-NC-SA license
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