|
|
Activation function dynamic averaging as a technique for nonlinear 2D data denoising in distributed acoustic sensors |
|---|---|
| Author: | Turov, Artem T.1,2; Barkov, Fedor L.2; Konstantinov, Yuri A.2; |
| Organizations: |
1General Physics Department, Applied Mathematics and Mechanics Faculty, Perm National Research Polytechnic University, Prospekt Komsomolsky 29, 614990 Perm, Russia 2Perm Federal Research Center of the Ural Branch of the Russian Academy of Sciences (PFRC UB RAS), 13a Lenin St., 614000 Perm, Russia 3S.P. Kapitsa Research Institute of Technology, Ulyanovsk State University, 42 Leo Tolstoy Street, 432970 Ulyanovsk, Russia
4Scientific Research and Advanced Studies Center of Ensenada (CICESE), Ensenada 22860, BC, Mexico
5Electromagnetism and Telecommunication Department, University of Mons, B-7000 Mons, Belgium 6Optoelectronics and Measurement Techniques Unit, University of Oulu, 90570 Oulu, Finland |
| Format: | article |
| Version: | published version |
| Access: | open |
| Online Access: | PDF Full Text (PDF, 6.4 MB) |
| Persistent link: | http://urn.fi/urn:nbn:fi-fe20231003138500 |
| Language: | English |
| Published: |
Multidisciplinary Digital Publishing Institute,
2023
|
| Publish Date: | 2023-10-03 |
| Description: |
AbstractThis work studies the application of low-cost noise reduction algorithms for the data processing of distributed acoustic sensors (DAS). It presents an improvement of the previously described methodology using the activation function of neurons, which enhances the speed of data processing and the quality of event identification, as well as reducing spatial distortions. The possibility of using a cheaper radiation source in DAS setups is demonstrated. Optimal algorithms’ combinations are proposed for different types of the events recorded. The criterion for evaluating the effectiveness of algorithm performance was an increase in the signal-to-noise ratio (SNR). The finest effect achieved with a combination of algorithms provided an increase in SNR of 10.8 dB. The obtained results can significantly expand the application scope of DAS. see all
|
| Series: |
Algorithms |
| ISSN: | 1999-4893 |
| ISSN-E: | 1999-4893 |
| ISSN-L: | 1999-4893 |
| Volume: | 16 |
| Issue: | 9 |
| Article number: | 440 |
| DOI: | 10.3390/a16090440 |
| OADOI: | https://oadoi.org/10.3390/a16090440 |
| Type of Publication: |
A1 Journal article – refereed |
| Field of Science: |
213 Electronic, automation and communications engineering, electronics |
| Subjects: | |
| Funding: |
Section 4 was performed as a part of state assignment No. 122031100058-3. Section 2.1 is supported by the Ministry of Science and Higher Education of the Russian Federation, grant number 075-15-2021-581 (experiment and raw data collection) and the Russian Science Foundation, grant number 23-79-30017 (master laser design and application, data interpretation). Section 1, Section 2.2, Section 3 and Section 5 were performed as a part of state assignment No. AAAA-A19-119042590085-2. A.A.F. is supported by the European Union’s Horizon 2020 research and innovation program (Individual Fellowship, H2020-MSCA-IF-2020, #101028712). |
| EU Grant Number: |
(101028712) HiFi Brilliancy - HIgh-speed FIbre-based BRILLouIn ANalyzer for endosCopY |
| Copyright information: |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
|
https://creativecommons.org/licenses/by/4.0/ |