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  • 标题:標本検査と構造信頼性維持について
  • 本地全文:下载
  • 作者:板垣 浩 ; 石塚 鉄夫 ; 伊藤 誠一
  • 期刊名称:日本造船学会論文集
  • 印刷版ISSN:0514-8499
  • 电子版ISSN:1884-2070
  • 出版年度:1984
  • 卷号:1984
  • 期号:155
  • 页码:215-225
  • DOI:10.2534/jjasnaoe1968.1984.215
  • 出版社:The Japan Society of Naval Architects and Ocean Engineers
  • 摘要:

    Various structural inspection procedures are applied to detect environmental, accidental and fatigue damage in response to requirements on structural safety. A regular inspection program takes care of environmental deterioration and accidental damage. As fatigue damage most likely occurs in an aging structure, another inspection program is necessary to preserve a fatigue failure of the structure. It is said that a fleet leader sampling inspection is effective due to the fact that high-time structures corresponding to the fleet leaders might have fatigue cracks with high probability. Meanwhile, operators who have those structures are required to spend time and cost for the inspections. A rotational sampling inspection which was recently recommended consists of inspections of a fraction of candidate fleet until all candidate structures are inspected at least once. Therefore, as many operators participate in the program of inspecting candidate structures, the undesirable situation mentioned above is avoidable. This report is devoted to discuss the two sampling inspection methods with the aid of a model developed adequately to generate actual circumstances and the Monte Carlo technique. It is mentioned that a method such as the Bayesian method to estimate parameters from data obtained by inspections is not adopted in this model. The following results are remarked from the numerical example : 1) According to the proposed model that the secondary inspections are performed if the primary inspections detect fatigue cracks, the damage detection capability of the rotational inspection is better than that of the fleet leader inspection. 2) The number of failed airplanes is not affected by the shapes of the fleet time distribution governing number of service flights for each airplane. The distribution in this model is assumed to be represented by the Beta distribution.

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