Seam Tracking and Detection of Groove by using Neural Network in Robotic Welding
机器人焊接中使用神经网络进行焊缝跟踪和坡口检测
基本信息
- 批准号:12650709
- 负责人:
- 金额:$ 0.45万
- 依托单位:
- 依托单位国家:日本
- 项目类别:Grant-in-Aid for Scientific Research (C)
- 财政年份:2000
- 资助国家:日本
- 起止时间:2000 至 2001
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
In this study, where backing plate or backing material are not used, one side back bead welding system is proposed to obtain a good welding result without the variation of the root gap. In the system, the torch is not only oscillated in the groove, but also moved before and behind like the switch back. During the forward process, a heat is given and is melted the base material and its root edge. During backward process, the droplet is deposited at the root edge and the bridge is formed. After that, the torch is moved forward by high-speed before burn through is generated. This torch motion is repeated. Therefore, there is no incomplete fusion and the stable back bead is obtained.For this purpose,1) The system is constructed to do the cooperative control of the torch motion (weaving width, welding speed), the wire feed rate and the power source characteristic, i.e., the stable weld pool penetration is kept and the seam tracking is carried out. The pulsed current becomes peak where the t … More orch approaches the root edge. The droplet is deposited on the root edges. The interface circuit between computer and welding robot, the welding power source and the wire feeder was made, and the cooperative control of the wire feed rate and current waveform was carried out according to the torch position.2) The technique is proposed for enabling the real-time sensing of the arc length and the extension length of the electrode wire in transient response.3) The neural network models are constructed by using the extension length in the beginning of the welding, and the welding current at each sampling, the wire feed rate. Its model output is the arc length and the extension length.The transient response is obtained by carrying out the fundamental welding experiment. The validity of this neural network is confirmed by comparing the output of the model with the experimental result. It is shown that the extension length and the arc length from voltage and current can be estimated and the neural network model is applicable as a sensor of the arc length. By using its model, it is possible to detect the groove shape during the forward process in the switch back motion. Less
在这项研究中,在不使用垫板或衬垫材料,单面背面堆焊系统提出了获得良好的焊接效果,没有变化的根部间隙。在该系统中,焊枪不仅可以在槽内摆动,而且可以像开关一样前后移动。在前进过程中,热量被给予并熔化基材及其根部边缘。在反向过程中,液滴沉积在根部边缘,并形成桥。之后,在产生烧穿之前,使焊炬高速向前移动。重复该焊炬运动。为此,1)系统被构造为对焊炬运动(摆动宽度、焊接速度)、送丝速率和电源特性进行协调控制,即,保持稳定的熔池熔深并进行焊缝跟踪。脉冲电流变为峰值, ...更多信息 Orch接近根部边缘。液滴沉积在根部边缘上。制作了计算机与焊接机器人、焊接电源和送丝机的接口电路,根据焊枪位置对送丝速度和电流波形进行协调控制。2)提出了一种在瞬态响应中实时检测电弧长度和电极丝伸出长度的技术。利用焊接开始时的延伸长度、每次采样时的焊接电流和送丝速度建立了神经网络模型。其模型输出为电弧长度和延伸长度,并通过基础焊接实验获得了瞬态响应。通过模型输出与实验结果的比较,验证了该神经网络的有效性。结果表明,该神经网络模型可以由电压和电流估计出电弧的延伸长度和弧长,可以作为电弧长度的传感器。通过使用其模型,可以在切换回运动的前进过程期间检测槽形状。少
项目成果
期刊论文数量(58)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Oshima, K: "Sensing of Gap and Seam Tracking Using Neural Network in Pulsed Arc Welding"Recent Technology of Arc Welding in Vessel and Pipe, Japan Welding Society. II112-II116 (2000)
Oshima, K:“脉冲电弧焊接中使用神经网络进行间隙和焊缝跟踪的传感”,容器和管道电弧焊接的最新技术,日本焊接学会。
- DOI:
- 发表时间:
- 期刊:
- 影响因子:0
- 作者:
- 通讯作者:
K. Oshima: "Sensing and Control of Weld Pool In One Side Robotic Welding"Proc. of International Institute of Welding Commission XII. IIW Doc. XII-1626-00. 68-75 (2000)
K. Oshima:“一侧机器人焊接熔池的传感和控制”Proc。
- DOI:
- 发表时间:
- 期刊:
- 影响因子:0
- 作者:
- 通讯作者:
H. Yamamoto: "Application of a Neural Network to Sensing and Control of Arc Length and Wire Extension"Proc. of Seventh Int. Welding Sym.. 223-228 (2001)
H. Yamamoto:“神经网络在弧长和导线延伸传感和控制中的应用”Proc。
- DOI:
- 发表时间:
- 期刊:
- 影响因子:0
- 作者:
- 通讯作者:
山根 敏: "初層片面裏ビード溶接におけるトーチモーションと電源特性の協調制卸"溶接学会全国大会講演概要. 67巻. 348-349 (2000)
Satoshi Yamane:“第一层单面背面焊道焊接中焊炬运动和功率特性的协作控制”日本焊接学会全国会议摘要第 67 卷 348-349 (2000)。
- DOI:
- 发表时间:
- 期刊:
- 影响因子:0
- 作者:
- 通讯作者:
L. H. Sharif: "Sensing and Control in Robotic Welding"Annual Meeting of Japan Welding Society. Vol. 67. 382-383 (2000)
L. H. Sharif:日本焊接学会年会“机器人焊接中的传感与控制”。
- DOI:
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YAMANE Satoshi其他文献
Numerical Simulation in high efficiency spot welding
高效点焊的数值模拟
- DOI:
10.2207/qjjws.35.177s - 发表时间:
2017 - 期刊:
- 影响因子:0
- 作者:
TAKAHASHI Ayumi;YAMANE Satoshi;YOSHIOKA Nobuyori;KOHANAWA Akihiko;YAMAMOTO Hideki - 通讯作者:
YAMAMOTO Hideki
Spectroscopic Measurement of the Arc and the Weld Pool in Robotic Welding
机器人焊接中电弧和焊池的光谱测量
- DOI:
10.2207/qjjws.38.59s - 发表时间:
2020 - 期刊:
- 影响因子:0
- 作者:
KOMAYA Daiki;YAMANE Satoshi - 通讯作者:
YAMANE Satoshi
YAMANE Satoshi的其他文献
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{{ truncateString('YAMANE Satoshi', 18)}}的其他基金
Fundamental of 3D adaptive model in Robotic welding
机器人焊接中 3D 自适应模型的基础
- 批准号:
15K06456 - 财政年份:2015
- 资助金额:
$ 0.45万 - 项目类别:
Grant-in-Aid for Scientific Research (C)
Advanced methods of design and verification for dynamically reconfigurable embedded systems
动态可重构嵌入式系统的先进设计和验证方法
- 批准号:
24500034 - 财政年份:2012
- 资助金额:
$ 0.45万 - 项目类别:
Grant-in-Aid for Scientific Research (C)
Development of Automatic Control System in Plasma-MIG Hybrid Welding
等离子-MIG复合焊自动控制系统的研制
- 批准号:
23560862 - 财政年份:2011
- 资助金额:
$ 0.45万 - 项目类别:
Grant-in-Aid for Scientific Research (C)
Automatic verification method for large scale embedded object-oriented design based on predicate abstraction
基于谓词抽象的大规模嵌入式面向对象设计自动验证方法
- 批准号:
19500025 - 财政年份:2007
- 资助金额:
$ 0.45万 - 项目类别:
Grant-in-Aid for Scientific Research (C)
Development of design methodologies and support environments of high-reliability embedded systems based on hybrid models
基于混合模型的高可靠性嵌入式系统的设计方法和支持环境的开发
- 批准号:
14580368 - 财政年份:2002
- 资助金额:
$ 0.45万 - 项目类别:
Grant-in-Aid for Scientific Research (C)
Design Support of Autonomous Distributed Systems by Integratig Temporal Logic, Concurrency Theny, Autom
集成时态逻辑、并发 Theny、Autom 的自治分布式系统设计支持
- 批准号:
11680360 - 财政年份:1999
- 资助金额:
$ 0.45万 - 项目类别:
Grant-in-Aid for Scientific Research (C)
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