中文摘要：

利用有限元分析法计算钢绞线感应加热温度场数值,结果表明：电流密度和频率是影响感应加热效果的电气参数.改变电流密度和频率,计算出大量的感应加热温度场数值.通过对温度场数值回归分析,建立了表征感应加热效果的数学模型.遗传算法是一种可以解决多目标优化问题的新型算法,相对于其它方法,该方法通用性强,准确率高,更具科学性.依据所建立的数学模型,应用多目标遗传算法进行电气参数优化,求解出最优解.该最优解为感应加热器温度控制提供理论依据.

英文摘要：

The temperature field numerical value of steel strand induction heating was calculated by using finite element analysis method. The result shows that the current density and frequency are the main electrical parameters affecting the induction heating result. By changing the current density and frequency, a large number of induction heating temperature field numerical values were calculated. The mathematical models of steel strand induction heating result were found by the regression analysis of temperature field numerical values. As a new algorithm, Genetic algorithm can solve multi-objective optimization problem. Compared with other methods, the method is very universal, high accuracy and more scientific. Based on the established mathematical models, the electrical parameters were optimized by using multi-o 『bjective genetic algorithms, the optimal solution was solved. The optimal solution has provided a theoretical basis for controlling the induction heater temperature.