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  • 标题:Structural damage detection using MAC-Fast Multi Swarm Optimization technique (MAC-FMSO)
  • 本地全文:下载
  • 作者:Richard Frans ; Yoyong Arfiadi
  • 期刊名称:MATEC Web of Conferences
  • 电子版ISSN:2261-236X
  • 出版年度:2017
  • 卷号:138
  • 页码:1-10
  • DOI:10.1051/matecconf/201713802020
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:Damage detection of structures is important to ensure the service of civil engineering infrastructures. Many techniques have been developed for damage detection of structures in the literature. In this paper a new technique, a so called MAC-FMSO technique, is developed by using a combination of Modal Assurance Criterion (MAC) and Fast Multi Swarm Optimization (FMSO) techniques. By using this method, not only the damage location can be assured, but also the loss of strength and loss of stiffness of structures might be quantified. The first stage is to obtain the damaged member’s location by using second level of damage detection techniques, such as mode shape curvature method, damage locating vector, or strain energy method. After obtaining the damaged member, the MACFMSO technique is used to obtain the loss of stiffness from the candidate of damaged members. The results show that the MAC-FMSO algorithm has the ability to predict the loss of stiffness in the damaged members. In this case, the MAC-FMSO technique can be considered as an efficient and effective tool at the third level of damage detections. This is because this technique successfully measures the loss of strength or loss of stiffness of the damage member or part of structures. At the end of the paper, the MAC-FMSO technique is applied to predict the location of damage and loss of stiffness of three different structures. The first application is a simply supported beam with three different damage scenarios; the second application is a 13-bar plane truss structure with two different scenarios, and the third application is a shear building structure with three different scenarios. The results of simulation show that the MAC-FMSO technique can accurately predict the loss of stiffness of the damaged member as well as the location of the damage.
  • 关键词:endamage identificationloss of stiffnessfast multi swarm optimizationmodal assurance criterionMAC-FMSO
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