Detección y análisis armónico en señales eléctricas usando sensado comprimido para evaluación de la calidad de energía
The measurement and analysis of harmonics are key parts of the evaluation of the quality of the energy; however, measuring the harmonics under the large-scale distributed measurement architecture faces the problem of obtaining measurements outside the sequence that brings latency into communication...
| Autor Principal: | Arciniega Calderón, Maricela Alexandra |
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| Formato: | bachelorThesis |
| Idioma: | spa |
| Publicado: |
Universidad Politécnica Salesiana. Carrera de Ingeniería Eléctrica. Sede Quito
2018
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| Acceso en línea: |
Arciniega Calderon, M. A. (2018). Detección y análisis armónico en señales eléctricas usando sensado comprimido para evaluación de la calidad de energía. Universidad Politécnica Salesiana. Carrera de Ingeniería Eléctrica. Sede Quito |
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| Sumario: |
The measurement and analysis of harmonics are key parts of the evaluation of the quality of the energy; however, measuring the harmonics under the large-scale distributed measurement architecture faces the problem of obtaining measurements outside the sequence that brings latency into communication and data fusion. For this reason, this article proposes as a solution to the problems of measurement and improvement of the resolution of harmonic signals, the compressed sensing (SC) as a technique for the recovery and estimation of signals, a technique that reduces the length of harmonic sampling and complexity of the data procedure compared to other theories. For this, we use restoration algorithms such as least squares (LQ), Basic Pursuit (BP), Orthogonal Matching Pursuit (OMP), performing experiments on three signals with different degree of total harmonic distortion (THD), obtaining as results the error of reconstruction in each algorithm to find the minimum percentage of compression in the recovery of harmonic signals. Finally, the results of the experiment show the accuracy of the detection and the system response can be improved without the need to increase the sampling points, showing the variation of the error as a function of the percentage of compression. |
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