Artificial Neural Network for Vibration Frequency Measurement Using Kinect V2

Author:

Liu Jiantao1ORCID,Yang Xiaoxiang12ORCID

Affiliation:

1. School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, China

2. Quanzhou Normal University, Quanzhou, Fujian 362000, China

Abstract

Optical measurement can substantially reduce the required amount of labor and simplify the measurement process. Furthermore, the optical measurement method can provide full-field measurement results of the target object without affecting the physical properties of the measurement target, such as stiffness, mass, or damping. The advent of consumer grade depth cameras, such as the Microsoft Kinect, Intel RealSence, and ASUS Xtion, has attracted significant research attention owing to their availability and robustness in sampling depth information. This paper presents an effective method employing the Kinect sensor V2 and an artificial neural network for vibration frequency measurement. Experiments were conducted to verify the performance of the proposed method. The proposed method can provide good frequency prediction within acceptable accuracy compared to an industrial vibrometer, with the advantages of contactless process and easy pipeline implementation.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

Mechanical Engineering,Mechanics of Materials,Geotechnical Engineering and Engineering Geology,Condensed Matter Physics,Civil and Structural Engineering

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. İzotropik Plakaların Regressif Topluluk Öğrenmesi Kullanarak Serbest Titreşim Analizi;European Journal of Science and Technology;2022-07-28

2. Video-based Deep Learning for Pipe Vibration Frequency Visualization;Transactions of the Korean Society for Noise and Vibration Engineering;2022-02-20

3. RF-Vsensing: RFID-based Single Tag Contactless Vibration Sensing and Recognition;2021 17th International Conference on Mobility, Sensing and Networking (MSN);2021-12

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