摘要
基于宇宙大爆炸理论提出的大爆炸算法是一种高效的群智能优化算法,但存在容易陷入局部最优的缺点。提出的改进大爆炸算法,通过改进原算法的爆炸半径缩减形式、随机候选解的选取以及边界处理,能有效改善该算法易陷入局部最优的缺陷。运用改进的大爆炸算法,以频率和模态为物理量构造损伤识别问题的目标函数,对简支梁的局部损伤进行了识别。数值模拟结果表明:改进算法能准确地识别结构损伤,特别是能有效识别局部小损伤,并具有对模拟测量噪声不敏感的优点。
The Big Bang Big Crunch(BB BC)algorithm is an optimization technique of swarm intelligence based on the Big Bang theory.It runs efficiently and can be realized simply,but it is easily trapped in local optimal results.For the purpose of overcoming its shortages,an improved BB BC algorithm is put forward in this essay,with the changes of the reduced forms of blast radius,the distribution of the random variable,and the treatment of the boundary conditions.Besides,the improved algorithm is applied in damage detection of a simply supported beam with10and20elements respectively.The numerical simulations indicate that the identified results are excellent even in the great influence of noise,especially for successive elements with tiny damage.A conclusion can be drawn that the improved BB BC algorithm can precisely detect structure damage,and would not be easily trapped into local optimal.
作者
尹智毅
张艾迪
林楷钊
吕中荣
YIN Zhiyi;ZHANG Aidi;LIN Kaizhao;LU Zhongrong(Department of Applied Mechanics and Engineering, Sun Yat sen University, Guangzhou 510006,China)
出处
《中山大学学报（自然科学版）》
CAS
CSCD
北大核心
2017年第6期105-110,共6页
Acta Scientiarum Naturalium Universitatis Sunyatseni
基金
国家自然科学基金(11172333
11272361)
广东省科技计划项目(2016A020223006)
广东省自然科学基金(2015A030313126)
关键词
群智能
大爆炸算法
结构损伤识别
频域
swarm intelligence
BB BC
damage detection
frequency domain
作者简介
尹智毅(1994年生),男;研究方向:结构损伤识别;Email:yinzhy@mail2sysueducn;通信作者:吕中荣(1975年生),男;研究方向:结构损伤识别;Email:lvzhr@mailsysueducn
