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Open AccessArticle

Learning to See the Vibration: A Neural Network for Vibration Frequency Prediction

School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, China
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Sensors 2018, 18(8), 2530; https://doi.org/10.3390/s18082530
Received: 9 July 2018 / Revised: 26 July 2018 / Accepted: 1 August 2018 / Published: 2 August 2018
Vibration measurement serves as the basis for various engineering practices such as natural frequency or resonant frequency estimation. As image acquisition devices become cheaper and faster, vibration measurement and frequency estimation through image sequence analysis continue to receive increasing attention. In the conventional photogrammetry and optical methods of frequency measurement, vibration signals are first extracted before implementing the vibration frequency analysis algorithm. In this work, we demonstrate that frequency prediction can be achieved using a single feed-forward convolutional neural network. The proposed method is verified using a vibration signal generator and excitation system, and the result compared with that of an industrial contact vibrometer in a real application. Our experimental results demonstrate that the proposed method can achieve acceptable prediction accuracy even in unfavorable field conditions. View Full-Text
Keywords: vibration measurement; frequency prediction; deep learning; convolutional neural network; photogrammetry; computer vison; non-contact measurement vibration measurement; frequency prediction; deep learning; convolutional neural network; photogrammetry; computer vison; non-contact measurement
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Liu, J.; Yang, X. Learning to See the Vibration: A Neural Network for Vibration Frequency Prediction. Sensors 2018, 18, 2530.

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