Abstract

Static, quasi-static and low frequency electric fields are being used in many fields of science and engineering. They are utilized in research studies of fundamental properties of materials, exploration of high-energy physics, in biology and medicine, etc., but also in a multitude of practical applications such as precipitation, painting, xerography, to name a few. In all these endeavors it is a good practice to find out what the electric fields are in terms of value, direction, and temporal and spatial distribution. This information can be crucial for making the application successful. Electric fields are also being created by many naturally occurring and man-made phenomena. The aim of this paper is to present different options for electric field evaluation and measurement. Aside from traditional approaches, new concepts using machine learning in electric field assessment and interpretation are discussed. As technologies progress, electric field detection methods become a part of sensor fusion realm by providing additional capabilities in process, environmental and situational awareness monitoring. They can provide unique information enhancing our knowledge and understanding. Examples of such sensor integrations are shown and explained.

Full Text
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