脉冲GTAW动态过程中使用DIDO Hammerstein识别轻微钢焊接池
DIDO Hammerstein Identification of Mild Steel Welding Pool in Pulsed GTAW Dynamic Process with Wire Filler
AI总结：
本文分析了焊接动态过程的非线性特性，采用MIMO Hammerstein模型近似描述过程，并开发了识别算法，通过焊接实验获取输入输出数据以识别焊接池的Hammerstein模型。
摘要：
本文分析了焊接动态过程的非线性特性，并采用MIMO Hammerstein模型近似描述该过程。开发了一种识别算法，并采用伪随机信号作为模型输入。通过焊接实验获取输入输出数据，从而识别出焊接池的Hammerstein模型。
英文摘要：
This paper analyzed the nonlinearity of welding dynamic process, and then adopted MIMO Hammerstein model to describe approximately the process. An identification algorithm was developed and pseudo random signals were adopted as model input. Through a welding experiment, input-output data were obtained and the Hammerstein model of welding pool was identified
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
