面向多类型传感器优化布置的结构响应重构
Structural response reconstruction oriented to optimal multi-type sensor placement
摘要点击 19  全文点击 21  投稿时间:2018-01-28  修订日期:2018-06-29
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DOI编号  10.7641/CTA.2018.80084
  2018,35(9):1339-1346
中文关键词  萤火虫算法  二进制编码  类卡尔曼滤波  传感器优化布置  响应重构
英文关键词  firefly algorithm  binary coding  excitation identification Kalman filter  optimal sensor placement  response reconstruction
基金项目  国家自然科学基金项目(61463028, 51768035)资助.
学科分类代码  460.1520
作者单位E-mail
董康立 兰州交通大学 1083797729@qq.com 
殷红 兰州交通大学  
彭珍瑞 兰州交通大学 pzrui@163.com 
中文摘要
      提出了利用逐步消去法(Backward sequential algorithm, BSA), 萤火虫算法(Firefly algorithm, FA) 分别和类 卡尔曼滤波算法(Excitation identification Kalman filter, EIKF) 结合, 以结构响应重构为目标, 对不同类型传感器同时 进行位置优化的方法. 通过对萤火虫算法进行二进制编码, 使其能够解决传感器优化布置问题; 以结构响应重构误 差方差平均值为目标, 以离散萤火虫算法和逐步消去法为求解方法实现传感器位置的优化; 利用预测的状态向量 值对激励和感兴趣位置处的结构响应进行重构. 用一个二维桁架模型来验证所提出方法的实用性和有效性. 数值 算例结果表明, 利用两种方法得到的优化位置处的测量信息求得的重构激励和响应与理论值能够很好地吻合, 对比 验证了两种方法的有效性.
英文摘要
      Optimal multi-type sensor placement for structure response reconstruction by using excitation identification Kalman filter (EIKF) is proposed, which is combined with the backward sequential algorithm (BSA) and the firefly algorithm (FA), respectively. A binary-coded firefly algorithm is proposed for optimal sensor placement; taking average theoretical reconstruction error variance as objective, the sensor location is optimized by using the backward sequential method and the binary firefly algorithm; the excitation and responses are reconstructed by using the predicted state vector values. Numerical example of a two-dimensional truss structure validates the feasibility and effectiveness of the proposed method. The result indicates that the reconstructed excitation and responses are in good agreement with the real ones, and the effectiveness of the methods is proved.