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:针对CO2 短路过渡气体保护焊的电弧特点 ,利用统计方法从电弧电压、电流中提取幅值和时域的 6个统计参数 ,作为焊接质量的评价依据。同时 ,针对CO2 气体保护焊常见的飞溅大和成型差等问题 ,设定焊接质量参数W ,并将神经网络技术引入质量评价系统 ,以求建立统计参数和质量参数之间的关系模型。通过实验 ,以神经网络估测的质量参数值W作为焊接生产过程质量控制的质量指标 ,绘制了中位数—极差控制图来实现对焊接过程的质量管理 ,初步构建了CO2 短路过渡气体保护焊质量控制系统
: According to the arc characteristics of short-circuit CO2 gas shielded arc welding, six statistical parameters of amplitude and time domain were extracted from the arc voltage and current by statistical method, which was used as the basis of welding quality evaluation. At the same time, the welding quality parameter W is set for the common problems such as large splashing and poor forming of CO2 gas shielded welding, and the neural network technology is introduced into the quality evaluation system to establish the relationship model between the statistical parameter and the quality parameter. Through experiment, taking the quality parameter value W estimated by neural network as the quality index of quality control in welding process, the median - difference control chart is drawn to realize the quality management of welding process. The CO2 short circuit transition gas protection Welding quality control system