基于嵌入分数维的树种算法的结构质量刚度识别
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摘要
采用改进的树种算法对结构进行质量和刚度的识别。基于加速度响应参数建立起目标函数,再利用融入分数维机制的树种算法(TSA)对于结构损伤进行反演。树种算法是一种新型的元启发式算法,具有结构简单,便于执行的特点。为了进一步改善算法的优化能力,引入一个全新的搜索阶段‘树的搜索’,在该阶段中引入分数维模型来改进算法后期的收敛能力,进入树种阶段,通过两种新的搜索模式来平衡此阶段的局部搜索和全局搜索能力。采用桁架结构作为数值算例进而得到识别结果。最终表明,在仅知道有限的时域参数,该算法能够有效地识别损伤参数,优于其他进化算法并且对测量噪声不敏感。
A modified tree seeds algorithm( TSA) was proposed to solve structural stiffness and mass damage identification problems. Firstly,a structure 's acceleration response parameters were used to establish an objective function,and then the TSA with fractional dimension embedded was used to do inversion of the structure's damages. TSA was a heuristic algorithm with a simple structure and easy to implement. In order to further improve its optimization capacity,a fully new search stage named " search with tree" was introduced. In this stage,a fractional dimension model was introduced to improve the convergence ability in later of TSA. After entering tree seeds stage,two new search modes were used to balance the local search ability and the global search one. A truss structure was taken as a numerical example to obtain its identification results. The results showed that the proposed method can effectively identify a structure 's damage parameters if only limited time domain parameters are known; it is superior to other algorithms and not sensitive to measuring noise.
A modified tree seeds algorithm( TSA) was proposed to solve structural stiffness and mass damage identification problems. Firstly,a structure 's acceleration response parameters were used to establish an objective function,and then the TSA with fractional dimension embedded was used to do inversion of the structure's damages. TSA was a heuristic algorithm with a simple structure and easy to implement. In order to further improve its optimization capacity,a fully new search stage named " search with tree" was introduced. In this stage,a fractional dimension model was introduced to improve the convergence ability in later of TSA. After entering tree seeds stage,two new search modes were used to balance the local search ability and the global search one. A truss structure was taken as a numerical example to obtain its identification results. The results showed that the proposed method can effectively identify a structure 's damage parameters if only limited time domain parameters are known; it is superior to other algorithms and not sensitive to measuring noise.
引文
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[13]YANG X S.Firefly algorithm,stochastic test functions and design optimization[J].International Journal of Bio-Inspired Commutation,2010,2(2):78-84.
[14]LI X T,YIN M H.Parameter estimation for chaotic systems by hybrid differential evolution algorithm and artificial bee colony algorithm[J].Nonlinear Dynamics,2014,77(1/2):61-71.
[15]GAO W,LIU S,HUANG L.A global best artificial bee colony algorithm for global optimization[J].Journal of Computational and Applied Mathematics,2012,236(11):2741-2753.
[16]LU X B,LIU J K,LU Z R.A two-step approach for crack identification in beam[J].Journal of Sound and Vibration,2013,332(2):282-293.
[17]KANG Fei.LI Junjie,XU Qing.Damage detection based on improved particle swarm optimization using vibration data[J].Applied Soft Computing,2012,12(8):2329-2335.
[2]LU Z R,LAW S S.Features of dynamic response sensitivity and its application in damage detection[J].Journal of Sound and Vibration,2007,303(1/2):305-329.
[3]DING Z H,HUANG M,LU Z R.Structural damage detection using artificial bee colony algorithm with hybrid search strategy[J].Swarm and Evolutionary Computation,2016,28:1-13.
[4]SINHA J K,FRISWELL M I,EDWARDS S.Simplified models for the location of cracks in beam structures using measured vibration data[J].Journal of Sound and Vibration,2002,251(1):13-38.
[5]SHEN M H H,TAYLOR J E.Identification problem for vibrating cracked beams[J].Journal of Sound and Vibration,1991,150(3):457-484.
[6]丁政豪,吕中荣,刘济科.基于差分人工蜂群算法的梁结构裂纹识别[J].振动与冲击,2016,35(11):74-78.DING Zhenghao,LZhongrong,LIU Jike.Crack identification for beams based on differential evolutionary ABC algorithm[J].Journal of Vibration and Shock,2010,35(11):74-78.
[7]丁政豪,徐浩杰,刘济科,等.基于混沌人工蜂群算法的结构损伤识别[J].中山大学学报,2015,54(5):39-42.DING Zhenghao,XU Haojie,LIU Jihe.Structural damage identification based on chaotic ABC algorithm[J].ACTA Scientiarum Naturalium Universities Sun Yan-Sen,2015,54(5):39-42.
[8]SUN H,LUS H,BETTI R.Identification of structural models using a modified Artificial Bee Colony algorithm[J].Computers and Structures,2013,116(1):59-74.
[9]GUO H Y,LI Z L.A two-stage method to identify structural damage sites and extents by using evidence theory and microsearch genetic algorithm[J].Mechanical System and Signal Processing,2011,23(3):769-782.
[10]DACKERMANN U I,SMITH W A,RANDALL R B.Damage identification based on response-only Measurements using cepstrum analysis and artificial neural network[J].Structural Health Monitoring,2014,13(4):430-444.
[11]GKDAGˇH.A crack identification approach for beam-like structures under moving vehicle using particle swarm optimization[J].Materials Testing,2014,55(2):114-120.
[12]KIRAN M S.TSA:tree-seed algorithm for continuous optimization[J].Expert Systems with Applications,2015,42(19):6686-6698.
[13]YANG X S.Firefly algorithm,stochastic test functions and design optimization[J].International Journal of Bio-Inspired Commutation,2010,2(2):78-84.
[14]LI X T,YIN M H.Parameter estimation for chaotic systems by hybrid differential evolution algorithm and artificial bee colony algorithm[J].Nonlinear Dynamics,2014,77(1/2):61-71.
[15]GAO W,LIU S,HUANG L.A global best artificial bee colony algorithm for global optimization[J].Journal of Computational and Applied Mathematics,2012,236(11):2741-2753.
[16]LU X B,LIU J K,LU Z R.A two-step approach for crack identification in beam[J].Journal of Sound and Vibration,2013,332(2):282-293.
[17]KANG Fei.LI Junjie,XU Qing.Damage detection based on improved particle swarm optimization using vibration data[J].Applied Soft Computing,2012,12(8):2329-2335.