Open AccessArtificial Neural Network for Vibration Frequency Measurement Using Kinect V2
Author(s) -
Jiantao Liu,
Xiaoxiang Yang
Publication year - 2019
Publication title -
shock and vibration
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.418
H-Index - 45
eISSN - 1875-9203
pISSN - 1070-9622
DOI - 10.1155/2019/9064830
Subject(s) - vibration , robustness (evolution) , artificial neural network , computer science , process (computing) , laser doppler vibrometer , artificial intelligence , engineering , computer vision , acoustics , laser , laser beams , biochemistry , chemistry , physics , optics , gene , operating system
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.