RF-Ear+: A Mechanical Identification and Troubleshooting System Based on Contactless Vibration Sensing

Mechanical vibration monitoring plays a critical role in today's industrial Internet of Things (IoT) applications. Existing invasive solutions usually directly attach sensors to the target, which may affect the operations of delicate devices. Non-invasive video-based approaches incur poor performance in low light conditions, and laser-based ones have difficulties to monitor multiple objects simultaneously. In this work, we propose RF-Ear$^+$+, a contactless vibration sensing system using Commercial off-the-shelf (COTS) RFID. RF-Ear$^+$+ could accurately monitor the mechanical vibrations of multiple devices using a single tag: it can clearly tell which object is vibrating at what frequency without attaching tags on any device. RF-Ear$^+$+ can measure the vibration with a frequency up to 987 Hz at a mean error rate of $0.4\%$0.4%. We further employ each device's unique vibration fingerprint to identify and differentiate devices of exactly the same model. What's more, RF-Ear$^+$+ can detect the rotating machinery faults based on the constructed spectrogram, which achieves $98\%$98% accuracy on 6 types of states. To improve the computation efficiency, we optimize the input of model in both time and frequency domains, and thus enable deployment on low-cost edge devices successfully. Comprehensive experiments conducted in lab and wild demonstrate the effectiveness of our system.