On the applicability of acoustic sensors in the problem of road surface defects
- Authors: Gorodnichev M.G.1, Mkrtchian G.M.1, Polyantseva K.A.1
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Affiliations:
- Moscow Technical University of Communications and Informatics (MTUCI)
- Issue: Vol 12, No 4 (2025)
- Pages: 155-163
- Section: INFORMATICS AND INFORMATION PROCESSING
- URL: https://ogarev-online.ru/2313-223X/article/view/380196
- DOI: https://doi.org/10.33693/2313-223X-2025-12-4-155-163
- EDN: https://elibrary.ru/GEYDZN
- ID: 380196
Cite item
Abstract
The article is devoted to the development and substantiation of a multimodal methodology for non-destructive monitoring of the condition of the road surface based on acoustic data supplemented by visual observations. At the level of feature analysis, the study demonstrates that the spectrograms of signals recorded when driving over smooth and damaged surfaces contain stable differences in the time-frequency structure suitable for automatic classification and mapping of defects. The requirements for the type of microphone (sensitivity, bandwidth over 8 kHz, directivity) and placement conditions (height, distance to the source, shielding objects) are justified. A two-sensor architecture with time synchronization combining stereo video and acoustics is proposed; it is shown that the correlation of modalities increases the reliability of localization and the quality of defect classification in real traffic conditions. Taken together, the presented approach forms the basis for long-term, fault-tolerant monitoring systems for road infrastructure with early detection of risks, even with increased noise levels and reduced visibility.
About the authors
Mikhail G. Gorodnichev
Moscow Technical University of Communications and Informatics (MTUCI)
Author for correspondence.
Email: m.g.gorodnichev@mtuci.ru
Cand. Sci. (Eng.), Associate Professor, Dean, Faculty of Information Technology
Russian Federation, MoscowGrach M. Mkrtchian
Moscow Technical University of Communications and Informatics (MTUCI)
Email: g.m.mkrtchyan@mtuci.ru
ORCID iD: 0000-0002-5802-5513
SPIN-code: 3197-7234
senior lecturer, Department of Software Engineering
Russian Federation, MoscowKsenia A. Polyantseva
Moscow Technical University of Communications and Informatics (MTUCI)
Email: k.a.poliantseva@mtuci.ru
ORCID iD: 0000-0002-7102-4208
SPIN-code: 8112-8560
Cand. Sci. (Eng.), associate professor, Department of Data Mining
Russian Federation, MoscowReferences
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