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基于模态曲率效用信息熵的梁结构损伤识别 被引量:16

Damage identification of beam structures based on modal curvature utility information entropy
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摘要 基于信息熵理论,结合现有的模态曲率指标在梁结构损伤识别中的优势,提出模态曲率效用信息熵指标。指标通过计算互重变化矩阵和权重-概率系数,综合地反映结构的损伤位置和损伤程度。采用简支梁算例对指标进行验证,结果表明:模态曲率效用信息熵充分利用了模态曲率对损伤位置较敏感的优势,且能有效地克服其不足之处,能够准确地定位结构的损伤位置,定性反应损伤程度且具有良好的抗噪性,为梁结构的损伤识别提供了有效的理论借鉴。最后,以试验室简支梁模型作为试验对象,对所提指标在工程中应用的可行性进行了验证。 Based on the information entropy theory,combined with the advantage of modal curvature index in the damage identification of beam structures,the modal curvature utility information entropy index is proposed.The index comprehensively reflects the damage state of the structure by calculating Mutual re-transformation matrix and the weight-probability coefficient.A simply-supported beam example is established to verify the index.The results show that the modal curvature utility information entropy index take advantage of the merits of the modal curvature index which is sensitive to damage and can overcome its shortcomings effectively.The index proposed can identify the damage location and damage degree accurately of structure and has certain noise immunity,which provides an effective damage identification method for beam structures.Finally,an actual simply-supported beam is taken as the experimental object to verify the effectiveness of the index in practical engineering.
作者 项长生 李凌云 周宇 原子 XIANG Changsheng;LI Lingyun;ZHOU Yu;YUAN Zi(College of Civil Engineering,Lanzhou University of Technology,Lanzhou 730050,China;Western Engineering Research Center of Disaster Mitigation in Civil Engineering,Ministry of Education,Lanzhou 730050,China;College of Civil Engineering,Anhui Jianzhu University,Hefei 230601,China)
出处 《振动与冲击》 EI CSCD 北大核心 2020年第17期234-244,共11页 Journal of Vibration and Shock
基金 国家自然科学基金项目(51868045) 兰州市科技计划项目(2014-1-181) 安徽省高校省级自然科学研究重点项目(KJ2019A0746) 安徽建筑大学博士启动基金项目(2019QDZ08)。
关键词 梁结构 损伤识别 模态曲率 效用信息熵 互重变化矩阵 权重-概率系数 beam structures damage identification modal curvature utility information entropy Mutual re-transformation matrix weight-probability coefficient
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