Artificial Neural Network for Vibration Frequency Measurement Using Kinect V2

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 sti...

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Main Authors: Jiantao Liu, Xiaoxiang Yang
Format: Article
Language:English
Published: Wiley 2019-01-01
Series:Shock and Vibration
Online Access:http://dx.doi.org/10.1155/2019/9064830
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author Jiantao Liu
Xiaoxiang Yang
author_facet Jiantao Liu
Xiaoxiang Yang
author_sort Jiantao Liu
collection DOAJ
description 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.
format Article
id doaj-art-3cba3dee5b9241e19d2c30fa1bb0d5ac
institution Kabale University
issn 1070-9622
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language English
publishDate 2019-01-01
publisher Wiley
record_format Article
series Shock and Vibration
spelling doaj-art-3cba3dee5b9241e19d2c30fa1bb0d5ac2025-02-03T01:29:12ZengWileyShock and Vibration1070-96221875-92032019-01-01201910.1155/2019/90648309064830Artificial Neural Network for Vibration Frequency Measurement Using Kinect V2Jiantao Liu0Xiaoxiang Yang1School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, ChinaSchool of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, ChinaOptical 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.http://dx.doi.org/10.1155/2019/9064830
spellingShingle Jiantao Liu
Xiaoxiang Yang
Artificial Neural Network for Vibration Frequency Measurement Using Kinect V2
Shock and Vibration
title Artificial Neural Network for Vibration Frequency Measurement Using Kinect V2
title_full Artificial Neural Network for Vibration Frequency Measurement Using Kinect V2
title_fullStr Artificial Neural Network for Vibration Frequency Measurement Using Kinect V2
title_full_unstemmed Artificial Neural Network for Vibration Frequency Measurement Using Kinect V2
title_short Artificial Neural Network for Vibration Frequency Measurement Using Kinect V2
title_sort artificial neural network for vibration frequency measurement using kinect v2
url http://dx.doi.org/10.1155/2019/9064830
work_keys_str_mv AT jiantaoliu artificialneuralnetworkforvibrationfrequencymeasurementusingkinectv2
AT xiaoxiangyang artificialneuralnetworkforvibrationfrequencymeasurementusingkinectv2