Issue |
MATEC Web Conf.
Volume 366, 2022
8th International BAPT Conference “Power Transmissions 2022”
|
|
---|---|---|
Article Number | 04004 | |
Number of page(s) | 6 | |
Section | Materials and Technological Processes | |
DOI | https://doi.org/10.1051/matecconf/202236604004 | |
Published online | 21 December 2022 |
Investigations for Development of Structures for Control of Fog Contaminations
1
Georgi Nadjakov Institute of Solid State Physics, Bulgarian Academy of Sciences, 72 Tzarigradsko Chaussee Blvd., 1784 Sofia, Bulgaria
2
Institute of Electronics, Bulgarian Academy of Sciences, 72 Tzarigradsko Chaussee Blvd., 1784 Sofia, Bulgaria
3
Escuela Politécnica Superior, Universidad de Alcalá, 28805 Alcalá de Henares, Madrid, Spain
4
Institute of Mechanics, Bulgarian Academy of Sciences, Block 4, Acad. G. Bonchev St., Sofia -1113, Bulgaria
Characterization of fogs is an important problem that does not have a good solution in real conditions. To investigate this problem, we chose the electromagnetic echo effect (EMEE) because it offers several advantages measurements are fast, accurate and can be contactless. Various concepts for the detection of impurities in the composition of fogs by implementing the EMEE were considered. An overview was made of the advantages and disadvantages of the proposed methods. An experimental setup was designed to conduct studies regarding the development of sensors for the control of fog contaminations. It has been experimentally proven that a change in the generated EMEE signal is observed when a change in the composition of the fog is present. The signal is also influenced by various conditions, e.g. solid interaction efficiency and laser beam intensity, modulation frequency, etc. Those parameters were optimized properly to achieve high sensitivity and accuracy. Research results indicate the possibility to use them for the detection of CBRN agents.
Key words: electromagnetic echo effect / sensors / fog / contamination / CBRN agents
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.