RMS Value Measurement Using a Meter Based on ARM Cortex-MO Microprocessor

Ajakida Eski, Orion Zavalani and Denald Komici

European Journal of Electrical Engineering and Computer Science, 2017, vol. 1, issue 2

Abstract: In an electrical grid at the transmission and distribution system level, to guarantee the system security and the power quality, the RMS value of voltage and current is an important issue. We calculate the RMS value by processing the samples of a signal in the time domain. A software based explicit RMS converter is presented to transform the alternating voltage and current waveforms into their RMS values. This paper briefly covers the mathematics of RMS and offers an algorithm of RMS measurements based in FIR digital filter, which are more versatile when compared to the analogue filters in their characteristics such as programming flexibility, ability to handle both low as well as high frequency signals accurately. The measurement system is designed using ARM Cortex MO, PSoC4, CY8C4245AXI-483 architecture which is responsible for executing algorithms required for the calculation and ensures high performances and low cost. To check the accuracy of the metering system, the proposed metering values are compared to the readings of a standard FLUKE metering and it is concluded that the meter has been successfully completed. Since the proposed approach provides low cost solution for true RMS metering, it can be used in industrial and commercial applications especially as Digital panel meters and harmonic detectors.Â

Keywords: Algorithm; Digital Filter; RMS Value (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations:

Downloads: (external link)
https://eu-opensci.org/index.php/ejece/article/view/19006 Abstract page (text/html)
https://eu-opensci.org/index.php/ejece/article/download/19006/10990 Full text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:epw:ejece0:v:1:y:2017:i:2:id:19006

DOI: 10.24018/ejece.2017.1.2.6

Access Statistics for this article

More articles in European Journal of Electrical Engineering and Computer Science from European Open Science
Bibliographic data for series maintained by support ().