Three phase medium frequency direct current (DC) resistance spot welding (RSW) machine has a complex electrical structure. Because the structure included various electrical components, it is hard to establish an accurate and integrated numerical model to simulate the energy delivery and control process. This study employed a particle swarm optimization (PSO) algorithm to conduct an intelligent parameters measurement. The measurement process included three procedures, based on electrical and physical characteristics of the objective electrical system. To verify the accuracy and reliability of the measurement, another numerical model established by MATLAB Simulink was employed. The comparative results showed that the maximum error of all measured parameters was 1%, which meant that the proposed intelligent parameter measurement method was effective, and convinced measurement results can be obtained. This study can benefit to establish a full process numerical calculation or evaluation model of the medium frequency DC RSW system.

三相中频直流（DC）电阻点焊（RSW）机具有复杂的电气结构。由于该结构包含各种电气组件，因此很难建立一个准确而完整的数值模型来模拟能量输送和控制过程。本研究采用粒子群优化（PSO）算法进行智能参数测量。根据目标电气系统的电气和物理特性，测量过程包括三个过程。为了验证测量的准确性和可靠性，使用了MATLAB Simulink建立的另一个数值模型。比较结果表明，所有测量参数的最大误差为1％，这表明该智能参数测量方法是有效的，并获得可靠的测量结果。该研究有助于建立中频直流RSW系统的全过程数值计算或评估模型。