摘要
基于超弹性形状记忆合金丝(SMA)的力学性能试验,分析影响SMA滞回特性的主要因素及变化规律,建立一种超弹性SMA的滞回参数模型。通过试验数据结果分析,应变幅值和加载速率是影响SMA滞回行为的两大主要因素;研究通过引入sinh函数和运用粒子群算法,提出了一种考虑了双因素影响的SMA滞回参数模型。基于试验数据进行模型的参数识别和确定关系,并对不同工况下的试验值和模型理论计算值进行比较分析,最终得出的对比结果吻合程度较好。证明了本文建立的滞回参数模型可以很好地模拟SMA在多影响因素下的应力-应变关系,及其滞回力学特性。
Based on mechanical tests of superelastic shape memory alloy wire, the main influence factors and chan- ging rules of the SMA hysteretic characteristics were demonstrated. A SMA hysteresis parameters model of super-e- lastic SMA was established. By analyzing the test data results, strain amplitude and loading rate are the two main factors influencing the SMA hysteresis behavior. By introducing the sinh function and using particle swarm optimi- zation （PSO） algorithm, this paper proposes a SMA hysteresis parameters model considering the influences of the two-factor. Identifying the parameters and determine the relationship based on the test data, and then comparing the model calculation value and the experimental value of different working conditions. Finally, it is concluded that the developed hysteresis parameters model can well simulate the stress-strain relationship of SMA and reflect its hystere- sis mechanical properties.
出处
《地震工程与工程振动》
CSCD
北大核心
2016年第6期79-85,共7页
Earthquake Engineering and Engineering Dynamics
基金
国家重点基础研究发展计划(973)(2015CB057702)
国家自然科学基金项目(51508185)
湖南科技大学研究生创新基金项目(S140015)~~
关键词
形状记忆合金丝
力学性能
滞回参数模型
粒子群算法
shape memory alloy
mechanical properties
hysteresis parameters model
particle swarm optimization
