Version 1
: Received: 6 November 2023 / Approved: 7 November 2023 / Online: 7 November 2023 (11:17:15 CET)
How to cite:
Oancea, C. Using Linear Regression to Reduce Measurement Errors for Electric Power. Preprints2023, 2023110436. https://doi.org/10.20944/preprints202311.0436.v1
Oancea, C. Using Linear Regression to Reduce Measurement Errors for Electric Power. Preprints 2023, 2023110436. https://doi.org/10.20944/preprints202311.0436.v1
Oancea, C. Using Linear Regression to Reduce Measurement Errors for Electric Power. Preprints2023, 2023110436. https://doi.org/10.20944/preprints202311.0436.v1
APA Style
Oancea, C. (2023). Using Linear Regression to Reduce Measurement Errors for Electric Power. Preprints. https://doi.org/10.20944/preprints202311.0436.v1
Chicago/Turabian Style
Oancea, C. 2023 "Using Linear Regression to Reduce Measurement Errors for Electric Power" Preprints. https://doi.org/10.20944/preprints202311.0436.v1
Abstract
Although data acquisition is a very usual technique, there are several aspects not always considered, as synchronization of acquired measures and evaluation of the errors that derive from this fact. The paper hereby aims to point this thing out, by mathematical determination of the necessary correction and implementing the software meant to evaluate the performances of the acquisition system. As an example, a three-phased acquisition system has been developed in order to monitor the currents and voltages on the three phases. Also other measures have been calculated, such as power and phase. The components on each phase don’t have to be fully identified because a whole system calibration can be made in the first stage. Calibration consists in finding the weighting coefficients for each quantity. The implemented solution for three-phased measures data acquisition starts from the hypothesis of a sampling frequency that respects Shannon theorem. The distance between two samples is small enough to consider a linear evolution between two moments for the same measure. Errors that affect the above mentioned, due to the different moments of time when samples are acquired, are analyzed and brought to the minimum value.
Keywords
sampling error; improving accuracy; data acquisition
Subject
Engineering, Electrical and Electronic Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
