Work

High-Frequency Subpixel Vibration Measurement Based on Compressed Sensing

Year: 2025

Type: article

Abstract: High-speed camera measurement technology is widely employed in sound recovery, contactless structural monitoring, fault diagnosis, digital soil mapping and other fields. High-speed image sequences are utilized to recover minute high-frequency signals that would otherwise be ignored. However, high-speed image sequence also imposes significant pressure on data transmission and processing. In certain scenarios, achieving high-speed camera measurement with the limited bandwidth is nearly impossible. In this article, high-frequency sub-pixel vibration measurement based on compressed sensing (HSVM-CS) is introduced, which utilizes sparse samplings from the image sequence to extract vibration signals and reconstruct the complete high-frequency vibration signal. Through both simulation and experimentation, we demonstrate our ability to recover the original high frequency signal ranging from 0 to 499 Hz at a sampling ratio of 0.3 in both the X and Y directions. The peak signal-to-noise ratio of the recovered 3D signals reaches 21 dB. Furthermore, the adaptive sampling strategy based on signal entropy is employed to allocate samplings reasonably, thereby enhancing the accuracy of recovery signals at the consistent sampling rate.

Source: IEEE Sensors Journal

DOI: 10.1109/jsen.2025.3556247

Authors: Xingjian Li, Yuedong Zhang, Gaojin Wen, Xuguo Zhang, Limin Wu

Language: English

Topic: Sparse and Compressive Sensing Techniques

Subfield: Computational Mechanics

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $2,645

Funder: National Natural Science Foundation of China

Award: G6209144344