高速旋转电弧传感器水下焊缝自动跟踪系统的研究
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摘要
随着深海资源的开发,海洋工程的建造规模和施工深度的不断加大,而水下焊接是海洋工程建造和维修中必不可少的关键技术之一。因潜水焊工受到深水饱和度的限制,迫切需要应用机器人来取代潜水焊工,实现水下焊接的自动化和智能化,而机器人焊缝跟踪是其中的重要研究内容之一。
基于高速旋转电弧传感的机器人水下焊缝跟踪系统直接使用焊接过程中的焊接电流信号来进行焊缝跟踪。它通过电弧的旋转来扫描焊接坡口,引起导电嘴与工件之间的距离(CTWD)有规律变化而引起焊接电信号变化来探测焊炬高度和左右偏差。通过分析焊接电流的变化规律得到偏差信息从而实现水下焊缝跟踪。其稳定性好,灵敏度高,空间可达性好,因而它是目前最有效的水下焊缝跟踪方法之一。
本文基于前人的研究成果,首先改善了旋转电弧传感器,在此基础上建立了一套基于旋转电弧传感器的机器人水下焊缝跟踪系统硬件平台,为实现焊缝的跟踪奠定了研究基础。该跟踪系统的硬件主要包括旋转电弧传感器、霍尔电流传感器、单片机、光电传感器、数据采集卡、工控机和机器人。该系统是由焊接子系统、信号采集子系统、滤波与偏差识别子系统、机器人跟踪控制子系统四个子系统组成。
采用PWM控制方式和PID控制算法,设计了以单片机为核心控制芯片的水下旋转电弧直流电机转速闭环控制系统,具有电路简单,控制方便和工作稳定可靠等特点,为水下焊缝偏差识别提供了保障。
由于水下焊接过程中受到冷却速度快和水压力的影响以及弧光、飞溅和短路过渡等因素的综合影响,采集到的电流信号和转速信号受到干扰。在LabVIEW8.5开发平台上进行小波滤波和中值滤波后,明显地改善电流波形;消除了弧光对转速信号的干扰,并和电流信号合并,确定电流信号周期,为偏差识别提供更加准确的信息;采用左右区间积分进行焊缝偏差识别,取得较高的识别精度,为水下焊接焊缝跟踪奠定了基础。
对影响水下焊接焊缝成形质量和电流信号特征的四个主要因素:旋转电弧传感器的旋转频率、旋转半径、焊接高度和焊接电流,进行了正交试验,并分别对抗拉强度、熔宽、熔深等三个试验指标进行了分析比较,确定最优水下焊接工艺参数。
最后建立工控机与机器人之间的通信,在斜线和折线两种V形坡口上进行水下焊缝跟踪实验,获得了较好的跟踪结果。
With the exploitation of deep ocean resource, offshore engineering construction become a large scale. As one of the key technologies in offshore engineering construction and maintenance, underwater welding is required absolutely necessary. Due to the saturation restrict of diving welder in deep water, underwater robot, instead of diving welder, is in emergent need to achieve underwater welding automatization and intelligentization. The robot seam tracking is among the important research area.
The robot underwater seam tracking system based on the rotating arc sensor, directly use the welding current to track the seam. When the rotational arc scans the groove, causing the distance between the tip and workpiece (CTWD) to change regularly, the welding current change in accordance. Therefore the offset between the center of the welding torch and the midline of the seam can be detected by the current variation. By analyzing the variation of welding current, offset information obtained in order to achieve underwater seam tracking. With high stability, sensitivity and spatial accessibility, the seam tracking system based on the rotating arc sensor is one of the most effective methods currently.
Based on previous research results, we improved of the rotating arc sensor firstly, hence the hardware of the robot underwater seam tracking system based on the rotational arc sensor is set up, which was the research basis for seam tracking. The hardware largely include the rotating arc sensor, the current sensor, singlechip, photoelectric sensor, data capture card, IPC and the robot. The system is composed of welding subsystem, signal acquisition subsystem, filter and offset identification subsystem, and the robot tracking control subsystem.
Aimed at the DC motor used in high speed rotational arc sensor of underwater welding, a system of speed feedback controlled by closed-loop has been designed, in which singlechip is used as the core control chip, the control mode of PWM and the control algorithm of PID are adopted. With simple circuit, easy to control and work stable and reliable, it provided a guarantee for offset identification of underwater welding.
As the fast cooling speed and water pressure in the underwater welding process, due to the strong arc, splash, short circuit transfer and so forth, the current signal and speed signal have been interfered. After the wavelet filter and median filter in the LabVIEW8.5 software development platform, current waveform have improved significantly. Eliminated the interference of arc on the speed signal, mergered the current signal and speed signal to determine the current signal cycle, provided a more accurate information for offset identification. Finally, left-right integral method was adopted to identify the welding torch offset. Obtained quite high recognition accuracy, builted a foundation for underwater welding seam tracking.
The four main factors, which were rotating frequency, the radius of the torch, torch height and welding current, affect the welding forming and the underwater current waveform characteristics. Orthogonal tests were carried through, the three test indicators, which were the tensile strength, weld width and pool depth, were analyzed and compared respectively, to determine the optimal parameters for underwater welding.
Finally, set up the communication between the IPC and the robots. The underwater seam tracking experiments were carried out on the steel plates with the bias seam and broken seam, achieved a good tracking results.
基于高速旋转电弧传感的机器人水下焊缝跟踪系统直接使用焊接过程中的焊接电流信号来进行焊缝跟踪。它通过电弧的旋转来扫描焊接坡口,引起导电嘴与工件之间的距离(CTWD)有规律变化而引起焊接电信号变化来探测焊炬高度和左右偏差。通过分析焊接电流的变化规律得到偏差信息从而实现水下焊缝跟踪。其稳定性好,灵敏度高,空间可达性好,因而它是目前最有效的水下焊缝跟踪方法之一。
本文基于前人的研究成果,首先改善了旋转电弧传感器,在此基础上建立了一套基于旋转电弧传感器的机器人水下焊缝跟踪系统硬件平台,为实现焊缝的跟踪奠定了研究基础。该跟踪系统的硬件主要包括旋转电弧传感器、霍尔电流传感器、单片机、光电传感器、数据采集卡、工控机和机器人。该系统是由焊接子系统、信号采集子系统、滤波与偏差识别子系统、机器人跟踪控制子系统四个子系统组成。
采用PWM控制方式和PID控制算法,设计了以单片机为核心控制芯片的水下旋转电弧直流电机转速闭环控制系统,具有电路简单,控制方便和工作稳定可靠等特点,为水下焊缝偏差识别提供了保障。
由于水下焊接过程中受到冷却速度快和水压力的影响以及弧光、飞溅和短路过渡等因素的综合影响,采集到的电流信号和转速信号受到干扰。在LabVIEW8.5开发平台上进行小波滤波和中值滤波后,明显地改善电流波形;消除了弧光对转速信号的干扰,并和电流信号合并,确定电流信号周期,为偏差识别提供更加准确的信息;采用左右区间积分进行焊缝偏差识别,取得较高的识别精度,为水下焊接焊缝跟踪奠定了基础。
对影响水下焊接焊缝成形质量和电流信号特征的四个主要因素:旋转电弧传感器的旋转频率、旋转半径、焊接高度和焊接电流,进行了正交试验,并分别对抗拉强度、熔宽、熔深等三个试验指标进行了分析比较,确定最优水下焊接工艺参数。
最后建立工控机与机器人之间的通信,在斜线和折线两种V形坡口上进行水下焊缝跟踪实验,获得了较好的跟踪结果。
With the exploitation of deep ocean resource, offshore engineering construction become a large scale. As one of the key technologies in offshore engineering construction and maintenance, underwater welding is required absolutely necessary. Due to the saturation restrict of diving welder in deep water, underwater robot, instead of diving welder, is in emergent need to achieve underwater welding automatization and intelligentization. The robot seam tracking is among the important research area.
The robot underwater seam tracking system based on the rotating arc sensor, directly use the welding current to track the seam. When the rotational arc scans the groove, causing the distance between the tip and workpiece (CTWD) to change regularly, the welding current change in accordance. Therefore the offset between the center of the welding torch and the midline of the seam can be detected by the current variation. By analyzing the variation of welding current, offset information obtained in order to achieve underwater seam tracking. With high stability, sensitivity and spatial accessibility, the seam tracking system based on the rotating arc sensor is one of the most effective methods currently.
Based on previous research results, we improved of the rotating arc sensor firstly, hence the hardware of the robot underwater seam tracking system based on the rotational arc sensor is set up, which was the research basis for seam tracking. The hardware largely include the rotating arc sensor, the current sensor, singlechip, photoelectric sensor, data capture card, IPC and the robot. The system is composed of welding subsystem, signal acquisition subsystem, filter and offset identification subsystem, and the robot tracking control subsystem.
Aimed at the DC motor used in high speed rotational arc sensor of underwater welding, a system of speed feedback controlled by closed-loop has been designed, in which singlechip is used as the core control chip, the control mode of PWM and the control algorithm of PID are adopted. With simple circuit, easy to control and work stable and reliable, it provided a guarantee for offset identification of underwater welding.
As the fast cooling speed and water pressure in the underwater welding process, due to the strong arc, splash, short circuit transfer and so forth, the current signal and speed signal have been interfered. After the wavelet filter and median filter in the LabVIEW8.5 software development platform, current waveform have improved significantly. Eliminated the interference of arc on the speed signal, mergered the current signal and speed signal to determine the current signal cycle, provided a more accurate information for offset identification. Finally, left-right integral method was adopted to identify the welding torch offset. Obtained quite high recognition accuracy, builted a foundation for underwater welding seam tracking.
The four main factors, which were rotating frequency, the radius of the torch, torch height and welding current, affect the welding forming and the underwater current waveform characteristics. Orthogonal tests were carried through, the three test indicators, which were the tensile strength, weld width and pool depth, were analyzed and compared respectively, to determine the optimal parameters for underwater welding.
Finally, set up the communication between the IPC and the robots. The underwater seam tracking experiments were carried out on the steel plates with the bias seam and broken seam, achieved a good tracking results.
引文
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