交叉件GTA填丝增材制造弧压检测与成形控制

doi:10.3901/JME.2019.15.017

机械工程学报 ›› 2019, Vol. 55 ›› Issue (15): 17-23.doi: 10.3901/JME.2019.15.017

• 特邀专栏：增材制造技术 • 上一篇下一篇

交叉件GTA填丝增材制造弧压检测与成形控制

朱贝贝, 熊俊

西南交通大学材料先进技术教育部重点实验室成都 610036

收稿日期:2018-08-26 修回日期:2019-03-16 出版日期:2019-08-05 发布日期:2019-08-05
通讯作者: 熊俊(通信作者),男,1986年出生,博士,副教授,博士研究生导师。主要研究方向为电弧增材制造,焊接过程传感与控制,发表论文30余篇。E-mail:xiongjun@home.swjtu.edu.cn
作者简介:朱贝贝,女,1996年出生。主要研究方向为电弧增材制造成形过程检测与控制。E-mail:Pigbeibei@126.com
基金资助:
国家自然科学基金（61573293，51505394）和国家重点研发计划（2016YFB1100202）资助项目。

Arc Voltage Detection and Forming Control for Crossing Parts in GTA Additive Manufacturing

ZHU Beibei, XIONG Jun

Key Laboratory of Advanced Technologies of Materials, Ministry of Education, Southwest Jiaotong University, Chengdu 610036

Received:2018-08-26 Revised:2019-03-16 Online:2019-08-05 Published:2019-08-05

摘要/Abstract

摘要： 基于电弧电压与弧长的关系特征，提出GTA填丝增材制造弧压检测与成形质量控制方法，以解决交叉结构件成形稳定性差和堆积路径交叉处产生严重凸起的难题。考虑到弧压干扰的影响，采用基于小波包的防脉冲干扰滑动平均滤波方法，有效滤除原始弧压波形中的杂波信号，并保证波形的平滑性。针对复杂且时变的GTA填丝增材制造系统，设计积分分离PID控制器并整定其参数，对比研究恒规范和闭环控制试验下的交叉件成形质量。结果表明，弧压实时检测与送丝速度闭环调控策略，可有效增强交叉件GTA填丝增材制造稳定性并解决交叉点凸起难题，弧压信号检测准确，成形控制精度高。

关键词: GTA填丝增材制造, 防脉冲干扰滑动平均滤波, 积分分离PID控制器, 交叉件, 小波包

Abstract: Based on the correlation between arc voltage and arc length, a method for arc voltage detection and forming control in GTA additive manufacturing is proposed to solve the problems of process instability and serious protrusion at the crossover of depositing path for crossing parts. Considering the influence of interferences, the original voltage signal is filtered by a new de-noising method of anti-impulse interference moving average based on wavelet packet, which can effectively filter out the disturbances in the original signal and ensure the smoothness of the waveform. For a complex and time-variant GTA additive manufacturing system, an integral separation PID controller is designed and its parameters ware adjusted. Depositions with constant wire feed speed and closed-loop control are compared to analyze the forming quality of crossing parts. The results show that arc voltage online detection and closed-loop adjustment of the wire feed speed can effectively increase the process stability and solve the problem of protrusion at the crossover on deposition path for crossing parts in GTA additive manufacturing, and accurate arc voltage detection as well as high control accuracy can be obtained.

Key words: anti-impulse interference moving average filter, crossing parts, GTA additive manufacturing, integral separation PID controller, wavelet packet

中图分类号:

TG156

朱贝贝, 熊俊. 交叉件GTA填丝增材制造弧压检测与成形控制[J]. 机械工程学报, 2019, 55(15): 17-23.

ZHU Beibei, XIONG Jun. Arc Voltage Detection and Forming Control for Crossing Parts in GTA Additive Manufacturing[J]. Journal of Mechanical Engineering, 2019, 55(15): 17-23.

参考文献

[1] MUGHAL M P,FAWAD H,MUFTI R A. Three-dimensional finite-element modelling of deformation in weld-based rapid prototyping[J]. In:Proceedings of the Institution of Mechanical Engineers,Part C:Journal of Mechanical Engineering Science,2006,220(6):875-885.
[2] de LIMA M S F,SANKARE S. Microstructure and mechanical behavior of laser additive manufactured AISI 316 stainless steel stringers[J]. Materials and Design,2014,55:526-32.
[3] TAMINGER K M B,HAFLEY R A. Characterization of 2219 aluminum alloy produced by electron beam freeform fabrication[C]//Proceedings of 13th SFF Symposium,2002:482-489.
[4] KAZANAS P,DEHERKAR P,ALMEIDA P,et al. Fabrication of geometrical features using wire and arc additive manufacture[J]. Proceedings of the Institution of Mechanical Engineers Part B-Journal of Engineering Manufacture,2012,226(B6):1042-1051.
[5] 卢秉恒,李涤尘. 增材制造(3D打印)技术发展[J]. 机械制造与自动化,2013(4):1-4. LU Bingheng,LI Dichen. Development of the additive manufacturing (3D printing) technology[J]. Machine Building & Automation,2013(4):1-4.
[6] 柏久阳,王计辉,林三宝,等. 电弧増材制造厚壁结构焊道间距计算策略[J]. 机械工程学报,2016,52(10):97-102. BAI Jiuyang,WANG Jihui,LIN Sanbao,et al. Model for multi-beads overlapping calculation in GTA-additive manufacturing[J]. Journal of Mechanical Engineering,2016,52(10):97-102.
[7] DING D,PAN Z,CUIURI D,et al. Wire-feed additive manufacturing of metal components:Technologies,developments and future interests[J]. The International Journal of Advanced Manufacturing Technology,2015,81:465-481.
[8] BONACCORSO F,CANTELLI L,MUSCATO G. An arc welding robot control for a shaped metal deposition plant:Modular software interface and sensors[J]. IEEE Transactions on Industrial Electronics,2011,58(8):3126-3132.
[9] 马倩,马树元,刘长猛,等. 典型TC4框类结构TIG电弧增材制造工艺研究[J]. 热加工工艺,2018,47(1):189-194. MA Qian,MAShuyuan,LIU Changmeng,et al. Study on TIG arc additive manufacturing process of typical TC4 frame structure[J]. Hot Working Technology,2018,47(1):189-194.
[10] KARUNAKARAN K P,SURYAKUMAR S,PUSHPA V,et al. Low cost integration of additive and subtractive processes for hybrid layered manufacturing[J]. Robotics and Computer-Integrated Manufacturing,2010,26(5):490-499.
[11] MEHNEN J,DING J,LOCKETT H,et al. Design study for wire and arc additive manufacture[J]. International Journal of Product Development,2014,19(1/2/3),2-20.
[12] SPENCER J D,DICKENS P M,WYKES C M. Rapid prototyping of metal parts by three-dimensional welding[J]. Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture,1998,212(3):175-182.
[13] XIONG J,ZHANG G. Online measurement of bead geometry in GMAW-based additive manufacturing using passive vision[J]. Measurement Science & Technology,2013,24(11):5103.
[14] WANG H,JIANG W,OUYANG J,et al. Rapid prototyping of 4043 Al-alloy parts by VP-GTAW[J]. Journal of Materials Processing Technology,2004,148(1):93-102.
[15] XU Y,LV N,ZHONG J,et al. Research on the real-time tracking information of three-dimension welding seam in robotic GTAW process based on composite sensor technology[J]. Journal of Intelligent & Robotic Systems,2012,68(2):89-103.
[16] YANG D,WANG G,ZHANG G. Thermal analysis for single-pass multi-layer GMAW based additive manufacturing using infrared thermography[J]. Journal of Materials Processing Technology,2017,244:215-224.
[17] XIONG J,ZHANG G. Adaptive control of deposited height in GMAW-based layer additive manufacturing[J]. Journal of Materials Processing Tech.,2014,214(4):962-968.
[18] 王其隆. 弧焊过程质量实时传感与控制[M]. 北京:机械工业出版社,2000. WANG Qilong. Real-time sensing and control of arc welding process quality[M]. Beijing:China Machine Press,2000.
[19] WALCZAK B,MASSART D L. Noise suppression and signal compression using the wavelet packet transform[J]. Chemometrics & Intelligent Laboratory Systems,1997,36(2):81-94.
[20] 程正兴. 小波分析算法与应用[M]. 西安:西安交通大学,2004. CHENG Zhengxing. Wavelet analysis algorithm and application[M]. Xi'an:Xi'an Jiaotong University,2004.

交叉件GTA填丝增材制造弧压检测与成形控制

Arc Voltage Detection and Forming Control for Crossing Parts in GTA Additive Manufacturing

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	熊鹏, 汤宝平, 邓蕾, 赵明航. 基于动态加权密集连接卷积网络的变转速行星齿轮箱故障诊断[J]. 机械工程学报, 2019, 55(7): 52-57.
[2]	柯庆镝, 詹伟, 宋守许, 刘光复. 基于磨损间隙下碰撞能耗模型的发动机曲轴服役-再制造状态分析方法[J]. 机械工程学报, 2019, 55(5): 148-155.
[3]	张智, 刘成颖, 刘辛军, 张洁. 采用小波包能量熵的铣削振动状态分析方法研究[J]. 机械工程学报, 2018, 54(21): 57-62.
[4]	崔芮华,王绍敏,刘骉. 基于小波包技术和熵理论的航空故障电弧特征频段研究[J]. 电气工程学报, 2017, 12(1): 1-8.
[5]	王涛,张兴,杜成孝. 基于小波包对数能量熵与BP神经网络的孤岛检测方法[J]. 电气工程学报, 2016, 11(6): 9-12.
[6]	闫晓玲, 董世运, 徐滨士. 基于最优小波包Shannon熵的再制造电机转子缺陷诊断技术[J]. 机械工程学报, 2016, 52(4): 7-12.
[7]	罗荣;田福庆;冯昌林;丁庆喜;李万. 冗余小波包改进及其在齿轮箱故障诊断中应用[J]. , 2014, 50(15): 82-88.
[8]	陈敬龙;张来斌;段礼祥;胡超. 基于非抽样提升小波包及奇异值分解的液阀故障诊断[J]. , 2011, 47(9): 72-77.
[9]	李宏坤;赵长生;周帅;郭义杰. 基于小波包—坐标变换的滚动轴承故障特征增强方法[J]. , 2011, 47(19): 74-80.
[10]	陈保家;陈雪峰;李兵;曹宏瑞;蔡改改;何正嘉. Logistic回归模型在机床刀具可靠性评估中的应用[J]. , 2011, 47(18): 158-164.
[11]	敖银辉;汪宝生. 钻头磨损检测与剩余寿命评估[J]. , 2011, 47(1): 177-181.
[12]	曹衍龙;程实;杨将新;郑华文;何元峰. 基于小波包的松动件质量估计方法[J]. , 2010, 46(22): 1-5.
[13]	崔玲丽;康晨晖;张建宇;李文斌;高立新. 基于时延相关及小波包系数熵阈值的增强型共振解调方法[J]. , 2010, 46(20): 53-57.
[14]	高英杰;孔祥东;ZHANG Qin. 基于小波包分析的液压泵状态监测方法[J]. , 2009, 45(8): 80-88.
[15]	谭大鹏;李培玉. 基于小波的钢液连铸下渣检测系统[J]. , 2007, 43(2): 141-146.