Damage Identification Using Sensitivity-Enhancing Control and Identified Models
Damage Identification Using Sensitivity-Enhancing Control and Identified Models
复制标题
使用灵敏度增强控制和识别模型进行损伤识别
DOI：
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发表时间：
2006
期刊：
影响因子：
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通讯作者：
L. Ray
中科院分区：
文献类型：
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作者：
J. A. Solbeck;L. Ray
本文研究了一种利用观测器/卡尔曼滤波识别（OKID）从输入-输出数据中识别模态频率和传递函数参数来定位结构损伤的相干方法。使用这种正向方法进行自主损伤识别通常需要(i)一个结构模型，通过该模型将损伤引起的测量和预测的模态特性联系起来，以及（ii）模态参数变化对损伤状态的良好敏感性。利用相干性方法，使用识别或解析结构模型，对每种损伤情况假设一个由有限模态频率和传递函数参数组成的损伤参数向量。利用OKID从受损结构的实验输入输出数据中提取测量参数向量，并与假设进行比较，以确定最可能的损伤状态。由高质量的频率测量和低质量的传递函数参数组成的参数向量集的丰富度被评估，以确定唯一局部损伤的能力。用三自由度扭转系统和空间框架桁架对该方法进行了实验验证。在扭转系统中，通过系统辨识建立健康结构模型，生成损伤参数假设，并采用解析模型对桁架结构进行损伤假设。反馈控制律通过加入闭环模态频率来增强参数向量，以降低噪声敏感性，提高参数向量假设对每种损伤情况的唯一性。结果表明，即使在用于形成损伤参数向量假设的结构模型存在模型误差的情况下，使用由开环和闭环模态频率组成的损伤参数向量也能改善损伤识别。
This paper investigates a coherence approach for locating structural damage using modal frequencies and transfer function parameters identified from input-output data using Observer/Kalman filter identification (OKID). Autonomous damage identification using such forward methods generally require (i) a structural model by which to relate measured and predicted modal properties induced by damage, and (ii) good sensitivity of modal parameter changes to damage states. Using the coherence approach, a damage parameter vector comprised of a finite set of modal frequencies and transfer function parameters is hypothesized for each damage case using either identified or analytic structural models. Measured parameter vectors are extracted from experimental input-output data for a damaged structure using OKID and are compared to hypotheses to determine the most likely damage state. The richness of the parameter vector set, which is comprised of high-quality frequency measurements and lower-quality transfer function parameters, is evaluated in order to determine the ability to uniquely localize damage. The method is evaluated experimentally using a three-degree-of-freedom torsional system and a space-frame truss. Damage parameter hypotheses are generated from a model of the healthy structure developed by system identification in the torsional system, and an analytic model is used to generate damage hypotheses for the truss structure. Feedback control laws enhance the parameter vectors by including closed-loop modal frequencies in order to reduce noise sensitivity and improve uniqueness of parameter vector hypotheses to each damage case. Results show improvements in damage identification using damage parameter vectors comprised of open- and closed-loop modal frequencies, even when model error exists in structural models used to form damage parameter vector hypotheses.