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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。
With the damage parameter identification as the target, the local optimization of the sensor based on the traditional Fisher information criterion will lead to the phenomenon of local aggregation of measurement points, resulting in redundant information and not conducive to damage localization. In order to solve this problem, the Fisher information matrix of candidate degrees of freedom is firstly weighted by the distance coefficient which reflects the degree of independence of information. Then the maximization of the determinant of the effective information matrix is taken as the goal. By using the method of stepwise accumulation, Sensor Optimization Arrangement for Fisher Information Criteria. A 16-DOF shear-spring mass model was optimized by this method. The results show that this method can effectively avoid the aggregation of measuring points and solve the problem of information redundancy.