传感器优化布置的距离系数-Fisher信息准则

以损伤参数识别为目标，基于传统Fisher信息准则的传感器优化布置会出现测点局部聚集现象，导致信息冗余，不利于损伤定位。针对此问题，首先以反映信息独立程度的距离系数对候选自由度的Fisher信息矩阵进行加权修正；然后以修正后的有效信息矩阵行列式最大化为目标，采用逐步累加的方法得到基于距离系数-Fisher信息准则的传感器优化布置方案。采用该方法对一个16自由度剪切型弹簧质量模型进行传感器优化布置。结果表明，该方法能有效避免测点聚集现象，解决信息冗余问题。

Distance coefficient-Fisher information criterion for optimal sensor placement

For damage parameters identification, when the traditional Fisher information criterion is used for optimal sensor placement, the measuring points are susceptible to gathering in a local sensitivity area, which results in information redundancy and this is not conducive to damage location. To avoid aggregation of the measuring points and improve the ability of the damage location, the distance coefficient, which reflects the degree of information independence, was used first to correct the Fisher information matrix, and then the measuring points were obtained by maximizing the determinant of the modified information matrix using a sequential algorithm. The method was employed to design the optimal sensor configuration for a simple 16-DOF chain mass-spring model. The results show the method can effectively avoid the aggregation of measuring points and solve the problem of information redundancy.