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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Format: | Article |
Language: | English |
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Wiley
2019-01-01
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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 1875-9203 |
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 |