Experimental study on monitoring the bolt group looseness in a clamping support structure model

In this article, bolt group looseness monitoring in a clamping support structure model, which is under environmental random excitation, is experimentally investigated. The bolt group has 12 bolts, providing an essential clamping force to fix cargo during transportation. Seven kinds of bolt group loo...

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Main Authors: Guangming Dong, Fagang Zhao, Xiaoke Zhang
Format: Article
Language:English
Published: SAGE Publishing 2017-03-01
Series:Advances in Mechanical Engineering
Online Access:https://doi.org/10.1177/1687814017695046
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spelling doaj-b331754fb90e458e97f1f5c2082952172020-11-25T03:44:32ZengSAGE PublishingAdvances in Mechanical Engineering1687-81402017-03-01910.1177/1687814017695046Experimental study on monitoring the bolt group looseness in a clamping support structure modelGuangming Dong0Fagang Zhao1Xiaoke Zhang2Institute of Vibration, Shock & Noise, Shanghai Jiao Tong University, Shanghai, ChinaShanghai Institute of Satellite Engineering, Shanghai, ChinaShanghai Institute of Satellite Engineering, Shanghai, ChinaIn this article, bolt group looseness monitoring in a clamping support structure model, which is under environmental random excitation, is experimentally investigated. The bolt group has 12 bolts, providing an essential clamping force to fix cargo during transportation. Seven kinds of bolt group looseness degree developed gradually are simulated in experiment. From an economic point of view, vibration transducer of accelerometer is used for monitoring. Time series analysis of Auto-Regressive with eXogenous model with input known and Auto-Regressive–Auto-Regressive with eXogenous model with input unknown are constructed, and the statistical indices of the model residual error are defined as the damage characteristic parameter indicating the bolt group looseness degree. The experimental analysis shows the effectiveness of the proposed method in monitoring the bolt group looseness at early stage, while the variation of structural resonance frequency can only be used to monitor large bolt group looseness degree. The experimental analysis also shows that under a stationary, broadband random excitation, the Auto-Regressive–Auto-Regressive with eXogenous model has the same bolt group looseness monitoring capability with the Auto-Regressive with eXogenous model.https://doi.org/10.1177/1687814017695046
collection DOAJ
language English
format Article
sources DOAJ
author Guangming Dong
Fagang Zhao
Xiaoke Zhang
spellingShingle Guangming Dong
Fagang Zhao
Xiaoke Zhang
Experimental study on monitoring the bolt group looseness in a clamping support structure model
Advances in Mechanical Engineering
author_facet Guangming Dong
Fagang Zhao
Xiaoke Zhang
author_sort Guangming Dong
title Experimental study on monitoring the bolt group looseness in a clamping support structure model
title_short Experimental study on monitoring the bolt group looseness in a clamping support structure model
title_full Experimental study on monitoring the bolt group looseness in a clamping support structure model
title_fullStr Experimental study on monitoring the bolt group looseness in a clamping support structure model
title_full_unstemmed Experimental study on monitoring the bolt group looseness in a clamping support structure model
title_sort experimental study on monitoring the bolt group looseness in a clamping support structure model
publisher SAGE Publishing
series Advances in Mechanical Engineering
issn 1687-8140
publishDate 2017-03-01
description In this article, bolt group looseness monitoring in a clamping support structure model, which is under environmental random excitation, is experimentally investigated. The bolt group has 12 bolts, providing an essential clamping force to fix cargo during transportation. Seven kinds of bolt group looseness degree developed gradually are simulated in experiment. From an economic point of view, vibration transducer of accelerometer is used for monitoring. Time series analysis of Auto-Regressive with eXogenous model with input known and Auto-Regressive–Auto-Regressive with eXogenous model with input unknown are constructed, and the statistical indices of the model residual error are defined as the damage characteristic parameter indicating the bolt group looseness degree. The experimental analysis shows the effectiveness of the proposed method in monitoring the bolt group looseness at early stage, while the variation of structural resonance frequency can only be used to monitor large bolt group looseness degree. The experimental analysis also shows that under a stationary, broadband random excitation, the Auto-Regressive–Auto-Regressive with eXogenous model has the same bolt group looseness monitoring capability with the Auto-Regressive with eXogenous model.
url https://doi.org/10.1177/1687814017695046
work_keys_str_mv AT guangmingdong experimentalstudyonmonitoringtheboltgrouploosenessinaclampingsupportstructuremodel
AT fagangzhao experimentalstudyonmonitoringtheboltgrouploosenessinaclampingsupportstructuremodel
AT xiaokezhang experimentalstudyonmonitoringtheboltgrouploosenessinaclampingsupportstructuremodel
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