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arXiv Machine Learning By Po-Heng Chou, Jen-Yu Chiu, Chun-Yu Yeh, Wei-Lung Mao, Walid Saad

Lightweight Time-Frequency Vibration Sensing for Consumer Device Condition Monitoring

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The paper introduces a lightweight AI framework for vibration-based condition monitoring of consumer rotating devices. It transforms 1‑D vibration signals into 2‑D time‑frequency maps using continuous wavelet transform and Hilbert‑Huang transform, then applies compact deep learning models such as MobileNetV3‑Small, ConvNeXt‑Tiny, and YOLOv11‑cls. Experiments on public bearing datasets show that CWT with YOLOv11‑cls delivers high diagnostic accuracy, while MobileNetV3‑Small offers a low‑latency alternative suitable for edge deployment, and the study emphasizes the need to avoid data leakage in model evaluation.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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