基于灵敏度增强结构频率的统计损伤检测

Q4 Mathematics 计算力学学报 Pub Date : 2008-06-01 DOI:10.1142/S0219455408002636
Z. Wang, F. Au, Y. Cheng
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引用次数: 10

摘要

提出了一种利用控制下结构的频率进行损伤检测的统计方法。在该研究中,首先采用基于独立模态空间控制的反馈控制,对被测系统的极点进行有意的赋值。然后得到受控制结构对损伤更敏感的规定特征频率,并进一步构成灵敏度增强损伤指标(SEDI)。阐述了多自由度系统损伤检测的增敏反馈控制原理。为了克服测量噪声对模态频率的影响,采用包含SEDI的t检验的假设检验来估计损伤的发生,采用包含SEDI的特征向量的统计模式识别方法来定位损伤。基于微扰理论,对特征向量进行归一化,消除损伤程度对损伤定位的影响。通过三跨连续梁单单元损伤和IASC-ASCE基准结构单支撑损伤的算例验证了该方法的有效性。仿真结果表明,利用被控制结构的频率,所提出的损伤指标对损伤更加敏感,能够对结构的小损伤进行检测和定位。
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STATISTICAL DAMAGE DETECTION BASED ON FREQUENCIES OF SENSITIVITY-ENHANCED STRUCTURES
A statistical method using frequencies of structures under control is proposed for detecting damage. In the study, feedback control based on independent modal space control is first used to assign the pole of the system under detection intentionally. Then the prescribed characteristic frequencies of the structure under control, which may be more sensitive to damage, are obtained and further employed to constitute a sensitivity-enhanced damage indicator (SEDI). The principle of sensitivity-enhancing feedback control for damage detection of multi-degree-of-freedom systems is elaborated. To overcome the effect of measurement noise on modal frequencies, a hypothesis test involving the t-test that utilizes the SEDI is employed to estimate the occurrence of damage, while a statistical pattern recognition method that uses the feature vectors including the SEDI is employed to locate damage. Based on the perturbation theory, the feature vectors are normalized in order to eliminate the effect of damage extent on damage localization. The proposed method is verified by examples including a three-span continuous beam with a single damaged element and the IASC-ASCE benchmark structure with a single damaged brace. Simulation results show that, by using the frequencies of the structures under control, the proposed damage indicators are more sensitive to damage and are capable of detecting and locating small damage of structures.
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来源期刊
计算力学学报
计算力学学报 Engineering-Computational Mechanics
CiteScore
0.80
自引率
0.00%
发文量
3201
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