水下干式高压焊接焊缝跟踪实验系统研究
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摘要
随着海底管道铺设增多,水下焊接越来越受到人们的重视。水下干式高压焊接是水下焊接的重要手段,实现水下干式高压焊接自动化对于推动水下焊接的发展具有重要的意义。而水下干式高压焊接焊缝跟踪技术是水下干式高压焊接自动化的重要内容。
本课题在对焊缝跟踪技术最新进展研究和高压环境对焊缝跟踪系统影响研究的基础上,建立了一套适合于高压环境进行焊缝跟踪的实验系统。实验采用被动光视觉方法,通过选取合适带宽的滤光镜,保证系统能在高压环境中采集到清晰的焊缝图像。控制单元采用最新发展的DSP技术,能够确保系统离线式和实时性。将采集到的焊缝图像传输到DM642中进行图像处理,得到的偏差信号通过串口通讯传递到DSP2812中,DSP2812将这个信号通过实时控制算法处理,转换为两个不同占空比的PWM波信号,PWM波被发送到电机驱动器中分别用于控制电机的运动方向和运动速度。
对被动光视觉技术的焊缝图像处理技术进行了研究分析,结合DSP技术的特点,提出一种有效的焊缝边缘识别算法。采用开小窗技术、中值滤波、Sobel边缘检测、二值化、特定区域边缘搜索法实现焊缝边缘的识别,保证系统的实时性。采用中值滤波对识别到的焊缝中心线数据进行滤波去噪,增强算法的抗干扰性,保证系统鲁棒性。通过选取钨极顶部区域的焊缝中心线坐标值参与偏差计算,消除系统的前导误差;在识别焊缝中心线时,同时对钨极中心线进行识别,对识别到的钨极中心线坐标做中值滤波和校正,保证系统的准确性。在算法中加入一些控制参数,防止算法失效和钨极调整位置超出焊缝范围,保证系统的智能性。
对曲线焊缝进行模拟跟踪实验,对斜焊缝进行智能行走实验,对斜焊缝在焊接条件下进行实时跟踪实验,实验结果表明系统能够满足水下高压焊接焊缝跟踪实验要求。
With the increase of submarine pipelines laying, underwater welding has been considered by increasing people. Underwater hyperbaric welding is an important method in the underwater welding field, and realizing the automation of underwanter hyperbaric welding is critical to the development of underwater welding. The technology of seam tracking is an important part of underwater hyperbaric welding.
Based on the in-depth investigation of the latest progress of seam tracking technologies and the influence of hyperbaric environment upon the seam tracking system, a set of seam tracking experimental system has been established. In the system, a technology of passive vision is adopted, and a filter with an appropriate bandwidth is used to acquisition high quality seam images in hyperbaric welding environment. The latest developments in DSP technology applied to the system's control unit can ensure the system off-line mode and a real-time processing ability. Seam images are processed by DM642 using corresponding seam recognition algorithm, and the deviation information is calculated by the algorithm. The information is translated into two PWM signals with different duty cycle by real-time control algorithm in DSP2812, and the PWM signals are used to control motor's moving direction and moving speed.
A feasible seam recognition algorithm is introduced on the basis of the research and analysis of image processing algorithms applied to passive vision technology and DSP technology. Respectively, windowing technology, median filtering, Sobel edge detection, binarization, edge search of a particular region are used to the seam recognition algorithm, which ensure the algorithm's real-time ability. To enhance the algorithm's anti-interference ability and make the algorithm robust, the seam midline data calculated by the algorithm is filtered using median filtering algorithm. The points of seam midline in the region at the top of tungsten pole and the points of the tungsten pole's midline are selected to be used to calculate the deviation information, which can eliminate the system's precursor error. In order to prevent the algorithm failure and stop automatically when the position of the tungsten pole is adjusted beyond the range of seam area, some control parameters are added to the algorithm.
Curved and linear seams are tracked under the simulated and welding conditions respectively using the system, and the system's intelligentized ability is also validated in experiments. The experimental results show that the system can meet the requirements of underwater hyperbaric welding.
本课题在对焊缝跟踪技术最新进展研究和高压环境对焊缝跟踪系统影响研究的基础上,建立了一套适合于高压环境进行焊缝跟踪的实验系统。实验采用被动光视觉方法,通过选取合适带宽的滤光镜,保证系统能在高压环境中采集到清晰的焊缝图像。控制单元采用最新发展的DSP技术,能够确保系统离线式和实时性。将采集到的焊缝图像传输到DM642中进行图像处理,得到的偏差信号通过串口通讯传递到DSP2812中,DSP2812将这个信号通过实时控制算法处理,转换为两个不同占空比的PWM波信号,PWM波被发送到电机驱动器中分别用于控制电机的运动方向和运动速度。
对被动光视觉技术的焊缝图像处理技术进行了研究分析,结合DSP技术的特点,提出一种有效的焊缝边缘识别算法。采用开小窗技术、中值滤波、Sobel边缘检测、二值化、特定区域边缘搜索法实现焊缝边缘的识别,保证系统的实时性。采用中值滤波对识别到的焊缝中心线数据进行滤波去噪,增强算法的抗干扰性,保证系统鲁棒性。通过选取钨极顶部区域的焊缝中心线坐标值参与偏差计算,消除系统的前导误差;在识别焊缝中心线时,同时对钨极中心线进行识别,对识别到的钨极中心线坐标做中值滤波和校正,保证系统的准确性。在算法中加入一些控制参数,防止算法失效和钨极调整位置超出焊缝范围,保证系统的智能性。
对曲线焊缝进行模拟跟踪实验,对斜焊缝进行智能行走实验,对斜焊缝在焊接条件下进行实时跟踪实验,实验结果表明系统能够满足水下高压焊接焊缝跟踪实验要求。
With the increase of submarine pipelines laying, underwater welding has been considered by increasing people. Underwater hyperbaric welding is an important method in the underwater welding field, and realizing the automation of underwanter hyperbaric welding is critical to the development of underwater welding. The technology of seam tracking is an important part of underwater hyperbaric welding.
Based on the in-depth investigation of the latest progress of seam tracking technologies and the influence of hyperbaric environment upon the seam tracking system, a set of seam tracking experimental system has been established. In the system, a technology of passive vision is adopted, and a filter with an appropriate bandwidth is used to acquisition high quality seam images in hyperbaric welding environment. The latest developments in DSP technology applied to the system's control unit can ensure the system off-line mode and a real-time processing ability. Seam images are processed by DM642 using corresponding seam recognition algorithm, and the deviation information is calculated by the algorithm. The information is translated into two PWM signals with different duty cycle by real-time control algorithm in DSP2812, and the PWM signals are used to control motor's moving direction and moving speed.
A feasible seam recognition algorithm is introduced on the basis of the research and analysis of image processing algorithms applied to passive vision technology and DSP technology. Respectively, windowing technology, median filtering, Sobel edge detection, binarization, edge search of a particular region are used to the seam recognition algorithm, which ensure the algorithm's real-time ability. To enhance the algorithm's anti-interference ability and make the algorithm robust, the seam midline data calculated by the algorithm is filtered using median filtering algorithm. The points of seam midline in the region at the top of tungsten pole and the points of the tungsten pole's midline are selected to be used to calculate the deviation information, which can eliminate the system's precursor error. In order to prevent the algorithm failure and stop automatically when the position of the tungsten pole is adjusted beyond the range of seam area, some control parameters are added to the algorithm.
Curved and linear seams are tracked under the simulated and welding conditions respectively using the system, and the system's intelligentized ability is also validated in experiments. The experimental results show that the system can meet the requirements of underwater hyperbaric welding.
引文
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