MoiréVib: Micron-level Vibration Detection based on Moiré Pattern
Jingyi Ning, Zhihao Yan, Zhaowei Wu, Lei Xie, Chuyu Wang, Yingying Chen, Baoliu Ye, Sanglu Lu
Abstract
Detection and assessment of micro vibrations are crucial tasks in both industrial settings and daily life. However, vibration sensors attached to the target vibrator may introduce potential resonance, and wireless detection methods suffer from severe multipath interference. Fortunately, moiré-based sensing methods have gained recognition in recent years due to their ability to perceive micro motion changes. In this paper, we propose MoiréVib, a micro-vibration detection solution based on moiré patterns for dynamic and high-frequency environments. We attach a printed marker with periodic gratings to the surface of vibration devices to generate moiré patterns, which can amplify micro vibrations due to their lowfrequency magnification effect. However, moiré pattern's changes caused by micro vibrations are often overwhelmed by random pixel-level noises, and the limited frame rate of the camera fails to capture high-frequency moiré features. To deal with these problems, we propose a spectrum-based method to refine and enhance the dynamic and micro moiré features. Additionally, we propose a dual-frame-rate-based fusion mechanism to realize high-frequency reconstruction of moiré features. Extensive experimental results show that MoiréVib can realize a median amplitude detection error of 4.37 𝜇𝑚 and achieve frequency detection up to 300𝐻𝑧 with a frame rate range of 10∼30 fps.
• Human-centered computing → Ubiquitous and mobile computing.
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