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.
