FATIGUE LIFE PREDICTION METHOD OF BRIDGE STRUCTURE BASED ON OPTIMIZED ADDITIVE POINT AGENT MODEL (MT)

To quickly evaluate the safety of damaged bridge structures in the service process of cranes, a real-time prediction method for the fatigue life of bridge structures based on the optimal additive agent model is proposed. Based on the measured load data, the randomness of the relevant parameters of t...

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Main Authors: DONG Qing, CHEN YuHao, LIU YongGang, QI QiSong
Format: Article
Language:zho
Published: Editorial Office of Journal of Mechanical Strength 2023-01-01
Series:Jixie qiangdu
Subjects:
Online Access:http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2023.03.031
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author DONG Qing
CHEN YuHao
LIU YongGang
QI QiSong
author_facet DONG Qing
CHEN YuHao
LIU YongGang
QI QiSong
author_sort DONG Qing
collection DOAJ
description To quickly evaluate the safety of damaged bridge structures in the service process of cranes, a real-time prediction method for the fatigue life of bridge structures based on the optimal additive agent model is proposed. Based on the measured load data, the randomness of the relevant parameters of the service conditions is characterized by the combination of the working cycle process. In line with the most unfavorable service conditions, the stress weak position of the bridge structure is determined through finite element statics analysis and failure case statistics. And the structure finite element model is established for fatigue damage and life prediction. The MSC. Fatigue′s S-N module and crack propagation module are employed to simulate the residual life of the structure under random working conditions, and the influence of different crack depths on the residual life of the structure is analyzed. The Kriging model for the life prediction of the bridge structure that is optimized by the Pelican Optimization Algorithm and additive point criterion is created by the Latin Hypercube Sampling method and the black box theory. The real-time fatigue life prediction of bridge structures during trolley movement with load by Miner linear cumulative damage theory. The bridge structure of QD20/10 t × 43 m × 12 m general bridge crane is taken as an example to verify the feasibility of the proposed method. Comparing the proposed method with the traditional fatigue life calculation method based on finite element simulation, the results show that it can accurately assess the remaining life of the damaged bridge structure with fewer simulation calls and shorter simulation time, which can provide some reference significance for crane maintenance cycle formulation and scrapping decisions.
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spelling doaj.art-eaa8059b105a43f9b4b533dfa54ccf5d2023-08-01T07:55:48ZzhoEditorial Office of Journal of Mechanical StrengthJixie qiangdu1001-96692023-01-0172974240373624FATIGUE LIFE PREDICTION METHOD OF BRIDGE STRUCTURE BASED ON OPTIMIZED ADDITIVE POINT AGENT MODEL (MT)DONG QingCHEN YuHaoLIU YongGangQI QiSongTo quickly evaluate the safety of damaged bridge structures in the service process of cranes, a real-time prediction method for the fatigue life of bridge structures based on the optimal additive agent model is proposed. Based on the measured load data, the randomness of the relevant parameters of the service conditions is characterized by the combination of the working cycle process. In line with the most unfavorable service conditions, the stress weak position of the bridge structure is determined through finite element statics analysis and failure case statistics. And the structure finite element model is established for fatigue damage and life prediction. The MSC. Fatigue′s S-N module and crack propagation module are employed to simulate the residual life of the structure under random working conditions, and the influence of different crack depths on the residual life of the structure is analyzed. The Kriging model for the life prediction of the bridge structure that is optimized by the Pelican Optimization Algorithm and additive point criterion is created by the Latin Hypercube Sampling method and the black box theory. The real-time fatigue life prediction of bridge structures during trolley movement with load by Miner linear cumulative damage theory. The bridge structure of QD20/10 t × 43 m × 12 m general bridge crane is taken as an example to verify the feasibility of the proposed method. Comparing the proposed method with the traditional fatigue life calculation method based on finite element simulation, the results show that it can accurately assess the remaining life of the damaged bridge structure with fewer simulation calls and shorter simulation time, which can provide some reference significance for crane maintenance cycle formulation and scrapping decisions.http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2023.03.031Fatigue life;Kriging agent model;Finite element simulation;Bridge structures;Work cycle
spellingShingle DONG Qing
CHEN YuHao
LIU YongGang
QI QiSong
FATIGUE LIFE PREDICTION METHOD OF BRIDGE STRUCTURE BASED ON OPTIMIZED ADDITIVE POINT AGENT MODEL (MT)
Jixie qiangdu
Fatigue life;Kriging agent model;Finite element simulation;Bridge structures;Work cycle
title FATIGUE LIFE PREDICTION METHOD OF BRIDGE STRUCTURE BASED ON OPTIMIZED ADDITIVE POINT AGENT MODEL (MT)
title_full FATIGUE LIFE PREDICTION METHOD OF BRIDGE STRUCTURE BASED ON OPTIMIZED ADDITIVE POINT AGENT MODEL (MT)
title_fullStr FATIGUE LIFE PREDICTION METHOD OF BRIDGE STRUCTURE BASED ON OPTIMIZED ADDITIVE POINT AGENT MODEL (MT)
title_full_unstemmed FATIGUE LIFE PREDICTION METHOD OF BRIDGE STRUCTURE BASED ON OPTIMIZED ADDITIVE POINT AGENT MODEL (MT)
title_short FATIGUE LIFE PREDICTION METHOD OF BRIDGE STRUCTURE BASED ON OPTIMIZED ADDITIVE POINT AGENT MODEL (MT)
title_sort fatigue life prediction method of bridge structure based on optimized additive point agent model mt
topic Fatigue life;Kriging agent model;Finite element simulation;Bridge structures;Work cycle
url http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2023.03.031
work_keys_str_mv AT dongqing fatiguelifepredictionmethodofbridgestructurebasedonoptimizedadditivepointagentmodelmt
AT chenyuhao fatiguelifepredictionmethodofbridgestructurebasedonoptimizedadditivepointagentmodelmt
AT liuyonggang fatiguelifepredictionmethodofbridgestructurebasedonoptimizedadditivepointagentmodelmt
AT qiqisong fatiguelifepredictionmethodofbridgestructurebasedonoptimizedadditivepointagentmodelmt