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International Standard Serial Number:
ISSN 1001-4551
Sponsor:
Zhejiang University;
Zhejiang Machinery and Electrical Group
Edited by:
Editorial of Journal of Mechanical & Electrical Engineering
Chief Editor:
ZHAO Qun
Vice Chief Editor:
TANG ren-zhong,
LUO Xiang-yang
Tel:
86-571-87041360,87239525
Fax:
86-571-87239571
Add:
No.9 Gaoguannong,Daxue Road,Hangzhou,China
P.C:
310009
E-mail:
meem_contribute@163.com
Abstract: Bolting is widely used in complex equipment such as wind turbines. The working load and mechanical vibration of the equipment will cause bolt loosening, and lead to the failure of bolt connection, which will seriously affect the normal operation of the equipment. Therefore,the connection stiffness model of bolt joint surface was established by taking the connection bolts of offshore wind turbine tower barrel as the research object, and the loosening state prediction of the connection bolts of tower barrel flange was carried out. Firstly, a virtual material model was used to characterize the connection stiffness of the bolt joint surface, the influence of preload on the virtual material layer model was explored, and the parameters for the finite element simulation were provided. Then, a high precision finite element model was established by combining the force hammer experiment with the measured data. Finally, the first 10 torsional and bending natural frequencies of flange connectors were used, the square ratio of frequency change of any two modes and the relative change ratio of frequency before and after the preload change were respectively used as bolt quantitative indicators for bolt positioning and loosening prediction. The results show that with the increase of preload, the natural frequency of tower connection increases gradually, but the sensitivity of natural frequency decreases slightly. According to the statistics of the test results of bolt loosening, the identification accuracy of bolt loose positioning reaches 95.24%. The prediction accuracy of preload reduction degree of single bolt and multiple bolt is 93.4% and 90.2% respectively. The research of bolt loosening prediction based on virtual material model has the characteristics of high precision and strong universality, which can provide an important basis for real-time monitoring of digital twin.
Key words: bolt connection failure; loose positioning identification; hammering experiment; virtual materials characteristic; joint stiffness model; preload; natural frequency
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