SPOT WELDING QUALITY FUZZY CONTROL SYSTEM BASED ON MULTISENSOR INFORMATION FUSION

The multisensor information fusion technology is adopted for real time measuring the four parameters which are connected closely with the weld nugget size（welding current, electrode displacement, dynamic resistance, welding time）, thus much more original information is obtained. In this way, the difficulty caused by measuring indirectly weld nugget size can be decreased in spot welding quality control, and the stability of spot welding quality can be improved. According to this method, two-dimensional fuzzy controllers are designed with the information fusion result as input and the thyristor control signal as output. The spot welding experimental results indicate that the spot welding quality intelligent control method based on multiscnsor information fusion technology can compensate the influence caused by variable factors in welding process and ensure the stability of welding quality.

A cooperative control strategy of resistance spot welding process by combining the constant current control with the DRC method

The modeling control method based on the dynamic resistance characteristics of good nuggets, that is the DRC method, is an improvement on the dynamic resistance threshold method for the quality control of resistance spot welding. But there is still a control blind area in the initial four cycles. For this reason, the quality of every weld nugget could not be fully ensured. Thus a new fuzzy cooperative control method is put forward. It uses a multi-information time-control mechanism by combining the constant current control technology with the DRC method in a relay way. This whole-process control strategy has led to a good control effect and produced the dual-identical results in the weld nugget quality and the welding time.

An Electrothermal Model Based Adaptive Control of Resistance Spot Welding Process

Resistance Spot Welding (RSW) is a process commonly used for joining a stack of two or three metal sheets at desired spots. The weld is accomplished by holding the metallic workpieces together by applying pressure through the tips of a pair of electrodes and then passing a strong electric current for a short duration. Inconsistent weld and insufficient nugget size are some of the common problems associated with RSW. To overcome these problems, a new adaptive control scheme is proposed in this paper. It is based on an electrothermal dynamical model of the RSW process, and utilizes the principle of adaptive one-step-ahead control. It is basically a tracking controller that adjusts the weld current continuously to make sure that the temperature of the workpieces or the weld nugget tracks a desired reference temperature profile. The proposed control scheme is expected to reduce energy consumption by 5% or more per weld, which can result in significant energy savings for any application requiring a high volume of spot welds. The design steps are discussed in details. Also, results of some simulation studies are presented.

METHOD TO IMPROVE DYNAMIC TRACKING ABILITY OF SPOT WELDING MANIPULATOR WITH HEAVY PAYLOAD

To improve the dynamic tracking ability of spot welding manipulator withheavy payload, a new programmable motion controller, which can provide software and hardwaresupports for several kinds of control algorithms, is developed first. Then, a decentralized adaptivecontrol algorithm is used to compensate the coupling between the manipulator joints, and thealgorithm is easy to implement based on the motion controller. Finally, experiments demonstratethat, compared with the traditional PID, the dynamic tracking ability of the manipulator can beobviously improved with this algorithm.

Neural network prediction of the shunt current in resistance spot welding

An error back propagation （BP） neural network prediction model was established for the shunt current compensation in series resistance spot welding. The input variables for the neural network consist of the resistivity of the material, the thickness of workpiece and the spot spacing, and the shunt rate is outputted. A simplified calculation for the shunt rate was presented based on the feature of the constant-current resistance spot welding and the variation of the resistance in resistance spot welding process, and then the data generated by simplified calculation were used to train and adjust the neural network model. The neural network model proposed was used to predict the shunt rate in the spot welding of 20# mlid steel （in Chinese classification） （in 2. 0 mm thickness） and 10# mild steel （in 1.5 mm and 1.0 mm thickness）. The maximum relative prediction errors are, respectively, 2. 83%, 1.77% and 3.67%. Shunt current compensation experiments were peoCormed based on the neural network prediction model proposed to check the diameter difference of nuggets. Experimental results show that maximum nugget diameter deviation is less than 4% for both 10# and 20# mlid steels with spot spacing of 30 mm and 50 mm.

Internet of Things Enabled Intelligent Energy Management and Control System for Heavy Equipment Industrial Park and Fuzzy Assessment of Its Schemes

In order to solve the problems of poor informationflow,low energy utilization rate and energy consumption data reuse in the heavy equipment industrial park,the Internet of Things(IoT)technology is applied to construct the intelligent energy management and control system(IEMCS).The application architecture and function module planning are analyzed and designed.Furthermore,the IEMCS scheme is not unique due to the fuzziness of customer demand and the understanding deviation of designer to customer demand in the design stage.Scheme assessment is of great significance for the normal subsequent implementation of the system.A fuzzy assessment method for IEMCS scheme alternatives is proposed to achieve scheme selection.Fuzzy group decision using triangular fuzzy number to express the vague assessment of experts is adopted to determine the index value.TOPSIS is modified by replacing Euclidean distance with contact vector distance in IEMCS scheme alternative assessment.An experiment with eight IEMCS scheme alternatives in a heavy equipment industrial park is given for the validation.The experiment result shows that eight IEMCS scheme alternatives can be assessed.Through the comparisons with other methods,the reliability of the results obtained by the proposed method is discussed.

Industry 4.0 Application in Manufacturing for Real-Time Monitoring and Control

Modern manufacturing aims to reduce downtime and track process anomalies to make profitable business decisions.This ideology is strengthened by Industry 4.0,which aims to continuously monitor high-value manufacturing assets.This article builds upon the Industry 4.0 concept to improve the efficiency of manufacturing systems.The major contribution is a framework for continuous monitoring and feedback-based control in the friction stir welding(FSW)process.It consists of a CNC manufacturing machine,sensors,edge,cloud systems,and deep neural networks,all working cohesively in real time.The edge device,located near the FSW machine,consists of a neural network that receives sensory information and predicts weld quality in real time.It addresses time-critical manufacturing decisions.Cloud receives the sensory data if weld quality is poor,and a second neural network predicts the new set of welding parameters that are sent as feedback to the welding machine.Several experiments are conducted for training the neural networks.The framework successfully tracks process quality and improves the welding by controlling it in real time.The system enables faster monitoring and control achieved in less than 1 s.The framework is validated through several experiments.

基于电阻点焊过程与形貌的飞溅成因分析及控制方法

【目的】在汽车白车身制造生产过程中,电阻点焊是板件连接的主要焊接工艺,但电阻点焊焊接过程中焊渣飞溅对白车身焊接质量影响较大,还会导致设备故障等问题,进而增加返修成本并降低生产效率。因此,该文对降低电阻点焊白车身的飞溅成因分析与控制方法展开研究。【方法】提出了一种飞溅成因分析与控制方法的操作流程,从多维度分析焊接过程与焊接形貌,进而针对性地实施措施,并在实际生产中验证飞溅成因分析与控制方法的操作流程。【结果】在验证过程中。通过对焊装车间飞溅率较高的工位基于分析结果进行优化,使得车间整体飞溅率由14%降低至6%,飞溅率低于优化前50%,有效减少预打磨工位的工作量和飞溅引起的故障率。【结论】飞溅成因分析与控制方法的理论体系保证了白车身焊接质量,提高了生产效率,并为后续工作提供思路指导与经验借鉴。焊接飞溅率是焊装车间主要控制指标之一,在生产过程中还需要不断监测、调整和保持,从而制定更有效的标准流程,减少飞溅对白车身质量的影响。

物联网工控平台下移动焊接机器人焊缝轨迹跟踪控制方法

在大型物联网工控平台下,移动焊接机器人焊缝轨迹跟踪控制过程中,焊接机器人位姿参量获取困难,应用效果不理想,控制后机器人焊缝偏差仍然较大,焊缝轨迹与预期轨迹的一致性系数较低,因此,提出物联网工控平台下移动焊接机器人焊缝轨迹跟踪控制方法。在物联网工控平台内,利用角速度传感器与加速度传感器感知焊接机器人位姿参量。搭建焊接机器人运动学和动力学模型,跟踪焊接机器人焊缝轨迹,确定焊接机器人焊缝误差和调控量,利用控制器对焊缝轨迹自适应控制。经实验证明,设计方法控制下焊缝偏差在0.1 mm以内,焊缝轨迹与预期轨迹一致性系数在9以上,该方法具有良好的焊接机器人焊缝轨迹跟踪控制性能。

工业机器人点焊工艺系统探析

点焊机器人主要由工业机器人本体、点焊钳、点焊机和点焊工艺控制系统组成,点焊工艺控制系统作为点焊机器人的核心总控单元控制点焊机器人、点焊钳,点焊机协同动作进行点焊自动作业。系统软件主要由运动控制单元、参数配置单元、指令集和点焊工艺功能单元等多个部分组成,承担着机器人/电焊钳运动控制、点焊机逻辑控制和其他配套设备逻辑控制等重要任务,系统的工艺参数也是通过控制系统的人机交互界面进行设置。控制系统把参数、运动节拍、IO信号通过执行程序有机地执行和调度起来后,点焊机器人就带着电焊钳执行各种指定的动作完成对工件的点焊加工。

一种点焊机器人在C空间中的智能轨迹规划算法

针对点焊机器人在C空间中的轨迹规划问题,提出一种基于蚁群算法的智能轨迹规划参数自适应蚁群算法(parameter adaptive ant colony algorithm,PAACA),以期改进蚁群算法易早熟、收敛速度慢的问题,在PAACA中构建一种复合线性适应度函数,此函数可以智能控制算法中信息素的作用强度,从而提高寻优能力。通过MATLAB进行仿真测试证明了PAACA的优越性,并将智能轨迹规划应用在工业机器人实体中,用KEBA控制器进行3D建模仿真示教和机器人本体运行,验证了C空间中的智能轨迹规划PAACA具有很强的实际应用价值。

基于弧焊工艺包的机器人焊接工作站信号配置与关联

在机器人焊接工作站的焊接过程中,需按照焊接时序图对机器人与焊接电源、送气、送丝等设备进行协同控制.作为焊接工艺的控制者,工业机器人可以利用弧焊工艺包中的焊接设备信号参数改变和调整焊接效果.通过将信号参数与配置好的焊接控制系统I/O信号相关联,在机器人与焊接电源、送气、送丝等设备间建立信号传输,从而实现工业机器人对这些设备的自动控制.

工业焊接机器人在轧钢棒材生产线的设计应用

为实现轧钢线棒材标牌自动焊接,本文结合现场实际工作情况,研究并设计了一种基于3D视觉识别的热轧带肋钢筋标牌自动焊接系统。该系统以西门子PLC系统为控制核心,PLC控制系统与工控机、机器人系统、3D视觉定位系统、送钉系统、标牌打印系统、焊接系统等进行信息的传输及作业过程的控制,实现钢筋标牌自动焊接功能。现场测试结果表明:该系统工作站能自动完成热轧带肋钢筋标牌自动焊接任务,系统运行稳定,工作效率高,可有效替换人工在线焊接工序,实现热轧带肋钢筋标牌全自动焊接,切实提高了生产效率,从根本上解决了作业人员现场的危险作业问题,极大减轻了作业人员的劳动强度。

“机器人+”背景下工业机器人技术创新发展方向

就《“机器人+”应用行动实施方案》的提出,探讨工业机器人的总体发展趋势及其在传统领域和新兴行业的应用与现状,介绍工业机器人技术今后一段时间在协作共融、群智控制技术等方面创新发展的方向和思路。

一种基于四元数法的焊接工作站协调控制算法

针对6R串联机器人运动学求解计算量大、传统方法求解困难以及涉及多解和奇异性等问题,在普吕克坐标系下描述了刚体运动,建立其四元数数学模型以及6R串联机器人运动学数学模型,求得6R串联机器人运动学逆解。建立工作站中机器人与变位机的协调联动算法模型,包括位置协调算法、速度协调算法以及姿态协调算法,最终得到机器人与变位机的控制程序。并且搭建焊接机器人工作站进行算法的实验验证。

压力管道工程焊接技术与质量控制研究

随着工业技术的快速发展,压力管道已成为石油、化工、燃气和电力行业等关键领域的核心组件。在这些领域中,压力管道常处于高压、高温等复杂环境中,焊接技术成为确保压力管道工程质量和可靠性的关键措施。然而,焊接材料失控、焊接工艺微小偏差或不稳定性可能会导致重大安全隐患,这使得深入探讨压力管道焊接技术的关键影响因素及其质量控制策略显得至关重要。文章系统分析了这些影响因素,并提出一系列提高焊接质量的策略。

基于S7-400 PLC的焊机控制系统研究与应用

为了提高焊机的自动化水平,对焊机控制系统进行设计。采用西门子S7-400可编程逻辑控制器(PLC)作为核心控制系统,使焊机控制系统完成数据采集处理、逻辑运算和控制输出,实现参数设置和状态监控。研究结果和实践应用表明:3个月连续运行期间,S7-400 PLC及ET200SP控制系统运行稳定,响应速度、通信稳定性及逻辑处理量较原S5系统显著提高。对安装调试好的环缝焊机进行了单轴试验和总体试验,验证了环缝焊机可以应用在实际工程中,实现了焊缝跟踪,避免了偏焊和漏焊。

海洋钢结构组合梁预制质量控制重点难点分析

海洋钢结构包含大量的组合梁,例如组块、单层甲板片、吊装框架等,组合梁作为主要基本结构在海洋钢结构中起着非常重要的作用。组合梁预制在海洋钢结构施工过程中作为主要工作得到重视,如何提高其施工质量及检验效率,成为检验员的一项重要工作。文章针对海洋钢结构建造组合梁预制过程进行了分析及探讨,对组合梁质量控制过程中的重点难点及检查注意事项,进行了梳理并提出合理的控制措施。

动力电池1060铝合金薄板可调环形光斑激光搭接焊工艺优化

激光焊接为动力电池铝合金薄板焊接提供了有效技术手段,然而传统激光焊接工艺在高焊接速度要求下易产生飞溅、气孔等缺陷,影响构件的服役性能.文中开展可调环形光斑激光搭接焊工艺调控研究,阐明了中心-环形激光功率对焊缝成形的影响规律,在此基础上,确定了无飞溅、少气孔、大搭接面熔宽的高速稳定焊接工艺窗口.在上述工艺窗口范围内,以小熔深波动与大搭接面熔宽作为目标,基于Kriging模型与NSGA-Ⅱ遗传算法开展多目标工艺参数优化.经验证,在焊接速度70 mm/s以上,焊缝成形质量进一步得到提升,搭接面熔宽提高8.89%、熔深波动小于10%、无明显成形缺陷.

工业机器人自动焊接系统应用与焊接质量控制

工业机器人是一种可移动式的自动化生产设备,其在现代机械制造领域中具有重要作用。文章对焊枪轨迹进行实时检测和反馈,并根据系统程序设计出基于PLC的控制器,对机器人自动高效完成加工任务的特点提出了改进措施;采用工业机器人代替人工工作,改善人工操作环境,使其能够适应复杂多变工件的生产要求。