双脉冲自保护药芯焊丝电弧焊工艺稳定性
Stability of double pulse self-shielded flux-cored wire arc welding process
张恒铭 1金秀鹃 1苟宁年 1蒋小霞 1石玗 2周海 3刘伟4
作者信息
- 1. 宁夏大学,机械工程学院,银川,750000
- 2. 兰州理工大学,省部共建有色金属先进加工与再利用国家重点实验室,兰州,730050
- 3. 宁夏特种设备检验检测院,银川,750000
- 4. 天地宁夏支护装备有限公司,银川,750021
- 折叠
摘要
鉴于自保护药芯焊丝在野外焊接的重要性,尤其对于野外大型机械等关键零部件的应急修复,提高其焊接成形精度至关重要,因此研究了自保护药芯焊丝在双脉冲电弧模式下的工艺稳定性.为了实现电弧焊工艺稳定性的有效控制,采用单因素试验研究了双脉冲参数对焊接过程稳定性的影响,发现熔滴平均尺寸与电流变异系数关系密切,因此,选取强弱脉冲频率、占空比、强弱脉冲峰值和基值 7个双脉冲参数作为输入值,建立一种基于RBF-BP神经网络的熔滴平均尺寸预测模型,结果表明,该预测模型有效、可行,为控制熔滴过渡过程稳定性提供了技术支撑.
Abstract
In view of the importance of self-protected flux-cored wire welding in the field,especially for the emergency repair of large machinery and other key parts in the field,it is very important to improve its welding forming accuracy.Therefore,the process stability of self-protected flux-cored wire in double-pulse arc mode is studied.In order to control the stability of arc welding process effectively,the influence of double pulse parameters on the stability of arc welding process was studied by single factor experiment.It was found that the average droplet size was closely related to the current variation coefficient.Based on this,7 double pulse parameters,including strong and weak pulse frequency,duty cycle,peak current and base current of strong and weak pulses,were selected as input values,and a prediction model of the average droplet size based on RBF-BP neural network was established.The results show that the prediction model is effective and feasible,and provides technical support for controlling the stability of the droplet transition process.
关键词
自保护药芯焊丝/工艺稳定性/熔滴过渡/RBF-BP神经网络Key words
self-protected flux-cored wire/process stability/droplet transition/RBF-BP neural network引用本文复制引用
基金项目
宁夏回族自治区自然科学基金(2023AAC03122)
宁夏回族自治区自然科学基金(2022AAC03100)
宁夏回族自治区科技厅自治区重点研发计划(2021BEE03001)
宁夏回族自治区科技厅自治区重点研发计划(2021BDE931030)
出版年
2024
NETL
NSTL
万方数据