基于粒子群-信赖域的金属极化曲线拟合算法  被引量:3

METAL POLARIZATION CURVE FITTING ALGORITHM BASED ON PARTICLE SWARM OPTIMIZATION-TRUST REGION

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作  者:孙峰 孙伟[1] Sun Feng;Sun Wei(School of Information Engineering,Shanghai Maritime University,Shanghai 201306,China)

机构地区:[1]上海海事大学信息工程学院

出  处:《计算机应用与软件》2019年第11期280-285,共6页Computer Applications and Software

摘  要:根据大气环境下腐蚀金属的极化行为特征,选择与之相适应的极化曲线方程,方程中包含7个电化学腐蚀动力学参数,如何求得高精度的参数至关重要.极化曲线拟合属于非线性最小二乘问题,而传统的非线性拟合方法来解决曲线拟合问题时有相当明显的缺陷,例如过分依赖参数初始值、拟合精度不高和结果陷入局部最优问题.对此提出基于粒子群-信赖域的极化曲线拟合算法来求得动力学参数,并通过实验证明该方法的有效性和鲁棒性.According to the polarization behavior of corrosive metals in the atmosphere,the polarization curve equation is selected.The equation contains seven electrochemical corrosion kinetic parameters.It is important to obtain high-precision parameters.Polarization curve fitting belongs to the nonlinear least squares problem,and the traditional nonlinear fitting method has obvious defects when solving the curve fitting problem,such as excessive dependence on the initial value of the parameter,low fitting precision and the result falls into local optimum.A polarization curve fitting algorithm based on particle swarm optimization and trust region was proposed to obtain the dynamic parameters.Experiments show the effectiveness and robustness of the method.

关 键 词:极化曲线 腐蚀动力学参数 曲线拟合 粒子群算法 信赖域算法 

分 类 号:TP399[自动化与计算机技术—计算机应用技术]

 

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