摘要
模态参数的准确辨识是对在线结构进行损伤诊断和状态监测的难点和核心之一。以二滩高拱坝原型测试为背景，结合随机子空间算法与改进的稳定图对泄流激励下的拱坝模态参数进行辨识，并实现对高坝振动状态的长期在线监测，为结构的安全评估提供依据。针对时域法所面临的模型定阶困难和噪声干扰以及由它们所引起的虚假模态辨识与剔除问题，利用改进的稳定图方法对模态参数进行更为精确辨识，并与ERA算法的识别结果进行对比。研究表明，该方法具有良好的品质与较高的计算精度，具有良好的工程应用前景。
Abstract
Correct modal parameter identification is one of the difficulties and cores for online structural damage diagnosis and health monitoring. Based on the prototype test of Ertan arc dam, combined with stochastic subspace identification algorithm and improved stabilization diagram, the modal parameters of arc dam under flow discharge are identified effectively, and also long-term online monitoring of the high dam is realized, so it offers evidence for structural health evaluation. Aimed at noise problem and the consequent identification and elimination of false modal parameters, and the order-determined problem as well in time domain, improved stabilization diagram is put forward to make more precise results, and the results is compared with the results with ERA method . Study shows that the new approach has excellent character and fine precision, and also has good prospect applied to engineering.
关键词
模态参数辨识 /
随机子空间 /
稳定图 /
动态监测
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Key words
modal parameter identification /
stochastic subspace identification algorithm /
stabilization diagram /
Dynamic Monitoring
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张建伟;康迎宾;张翌娜;赵 瑜.
基于泄流响应的高拱坝模态参数辨识与动态监测[J]. 振动与冲击, 2010, 29(9): 146-150
ZHANG Jian-wei;Kang Ying-bing;Zhang Yi-na;ZHAO Yu.
Modal Parameter Identification and Dynamic Monitoring of High Arc Dam under Response of Flow Discharge[J]. Journal of Vibration and Shock, 2010, 29(9): 146-150
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