基于一种免疫算法的结构动态参数识别

Identification of structure dynamic parameter based on an immune algorithm

受生物免疫系统的启发提出了一些基于免疫概念的优化算法。该方法有效地避免了传统遗传算法易于出现早熟、搜索效率低及不能很好保持个体多样性等问题。本文将免疫算法应用于结构动态参数识别领域,通过其在VC环境下调用ANSYS有限元程序中的APDL语言,并在后期引入加速循环操作,从而实现了对结构动态参数快速而精确的识别,仿真算例表明其正确性、有效性和较好的抗观测噪声能力。该方法特别适合于对大型复杂结构的参数识别计算。

Inspired from the vertebrate immune system, a novel algorithm, the immune algorithm, is proposed. The algorithm avoids the problems of easily appeared precocity, low searching efficiency and low capability to maintain quite nicely the individual diversity, an immune algorithm is applied to the field of the dynamic parameter identification. By calling subprogram of the APDL language and using accelerated operation, the structure dynamic parameters are identified quickly and precisely. The effectiveness, correctness and better ability to resist measurement noises are proved by a numerical example, and the relative error of estimated results is less than 10% even if the relative error of measurement of frequency domain is 30%. The identification precision can satisfy the engineering demand. The method is particularly suitable for parameter identification of large and complex structure.