Random Error Characteristics and Evaluation Method of Optical Voltage Sensor

DOI

10.2991/mmsa-18.2018.77How to use a DOI?

Keywords

optical voltage sensor; frequency domain stability component; random error; style; noise; evaluation

Abstract

The random error characteristics of optical voltage sensors (OVS) directly affect the measurement accuracy. Sequence variance is a commonly used method to evaluate the characteristics of the OVS random error. However, sequence variance does not model the OVS noise itself and does not identify the noise coefficient in terms of OVS noise signature analysis. Based on sequence variance method, the improved sequential analysis of variance method is proposed to analyze the random error characteristics of OVS. After the OVS test data is processed by the improved sequential analysis of variance method, the least square fitting is performed, and the coefficients of each random error term are accurately solved. With the coefficients, the influencing factors are identified, and the corresponding error suppression measures are proposed. The experiments results demonstrate that the improved sequential analysis of variance method is different from the sequence variance method, the sequence variance method fluctuates and gradually increases when the correlation time is more than half of the total measurement duration, while the improved sequential analysis of variance method always remains relatively stable.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Cong Lin
AU  - Min Cao
AU  - Bo Li
AU  - Qingchan Liu
AU  - Quancong Zhu
AU  - Lihui Wang
PY  - 2018/03
DA  - 2018/03
TI  - Random Error Characteristics and Evaluation Method of Optical Voltage Sensor
BT  - Proceedings of the 2018 International Conference on Mathematics, Modelling, Simulation and Algorithms (MMSA 2018)
PB  - Atlantis Press
SP  - 349
EP  - 352
SN  - 1951-6851
UR  - https://doi.org/10.2991/mmsa-18.2018.77
DO  - 10.2991/mmsa-18.2018.77
ID  - Lin2018/03
ER  -