摘要
随着大型长距离管道运输的推广应用，管道焊接质量直接关系到运输的可靠性。作为焊缝质量检测的新型设备，管道检测机器人的研究和应用成为了国内外学者的研究热点之一。目前对于管道焊缝检测机器人的理论研究和实际应用还处于发展阶段，研究成果大多为实验样机，距离产业化的普及应用还有不小的差距，主要是管道机器人还存在着定位不准、体积重量较大、管径适应能力差等问题。针对以上问题，受国家质量监督检验检疫总局项目“核电领域放射性安全监测量值溯源技术研究”（项目编号：201210044-03）子项目资助，本文提出了一种新型的管道焊缝检测机器人机构，并对其检测原理、本体结构、定位方法等问题进行了深入的分析和研究。
鉴于野外作业的特殊性，如何有效地降低机器人对于外部能源的依赖成为影响其产业化的限制条件之一。本文针对目前管道焊缝检测机器人大多采用拖缆方式的X射线检测，并通过对当前常见的γ射线源的特性进行了对比分析，提出了采用~(75)Se的检测方案。通过实验研究更新了~(75)Se射线源在AB级像质灵敏度要求下其有效的管道壁厚检测范围。管道焊缝检测实验表明，在壁厚4~30mm的范围内，~(75)Seγ射线检测的胶片像质达到AB级，满足国家标准和设计要求。
针对管道焊缝检测机器人管径适应能力差的问题，本文设计了一种新型的管道焊缝检测机器人的本体结构，创造性地设计了伸缩足结构，并采用蓄能器保障能量供给，极大地提升了管道机器人的管径适应能力，并设计了机器人的工作平台调节机构，确保焊缝检测质量的可靠性。
为了确保本体结构设计的合理性，建立了完整的机器人空间运动力学模型。对机器人在弯管中的运动进行了理论研究，分析了机器人在管内的运动状态。模拟实验表明，管道机器人在弯管中运行时，适用管径为Φ440~Φ858mm。
管道焊缝检测机器人质心的自我稳定性对于检测结果、通过性和越障性能具有重要的影响。文中分析了管道焊缝检测机器人质心发生偏心、振动的原因，建立了机器人质心的运动姿态方程，分析表明在弯管内，机器人质心的运动规律为一椭圆轨迹，并采用ADAMS软件验证了数学模型的正确性。
论文分析了管道机器人现有管内定位方案存在的问题，提出了采用计程轮主定位、机器视觉精确定位的管道机器人管内定位方法。鉴于传统视觉定位基于灰度差异不易提取焊缝特征的问题，系统采用基于色彩特征的图像焊缝特征识别方法，并提出了一种改进的矢量中值滤波法和基于归一化处理的改进型增强算法，有效地增强了各通道通过的色差，提高了图像对比度，实现了焊缝中心线的准确定位。通过对管道机器人在可测管道范围内的误差分析可知，最大误差为1.84~3.76mm，定位精度得到了很大的提高。
With the development of the long-distance pipeline transportation, the weldingquality for pipeline directly influences the reliability of the transportation. As the newequipment for welding test, the research and application of pipeline inspection robothas become one of the hot topics recently both at home and abroad. At present thetheoretical research and practical application of pipe robot are still in the developmentstage and will be available in the future and the research results mostly are onlylimited to the experimental prototype, which should be done before industrializationthrough systematic research and pilot plant scale. Supported by GeneralAdministration of Quality Supervision, Inspection and Quarantine fund （Grant No.201210044-03）, the paper analyzes the existing problems that the pipeline robot is tooheavy, positioning is not accurate, the ability of adapting pipe is poor, andsystematically put forward a new type of mechanism of pipe robot, analyzing andstudying profoundly the detecting principle, the bulk structure and the localizationmethod.
Considering the particularity of field operations, how to make robot effectivelyreduce dependence on external energy has become one of the key factors. According tothe facts that pipe robot adopts mostly X-ray to detect the weld by dragging cable, thepaper intends to make a contrastive analysis of the characteristics of different γ-raysources and proposes the test scheme to use Se75. The effective weld detection range isascertained in level AB through experiment. The experiments about the detection ofpipe welds show that the image reached AB-level in the range between4mm and30mm by Se75and meet the national standards and design requirements.
The mechanical self adapting characteristics of robot are one of key performancesand the novel ontological structure is designed scientifically. The stretching leg structure whose energy and the adjusting mechanism of working platform are suppliedwith accumulator is created, which greatly improves the ability to adapt to pipeline andensures the reliability of the weld inspection. Based on the establishment of the motiondynamics model, the paper analyzes the motion state of robot. The simulation resultsreveal that the suitable diameter of the pipeline robot in bend pipe ranges from440mmto858mm. The self stability of the robot mass centroid exerts significant influence onthe test results, the passing capacity and the obstacle negotiation performance. Thepaper analyzes the causes of the eccentricity and vibration of robot and establishes themovement state formulas. The analysis shows that the motion law of the centroid is anellipse trajectory in bending pipe, and verifies the correctness of the mathematicalmodel by ADAMS.
The paper analyzes the current positioning scheme of robot in pipe and problems,and puts forward the location plan by which the odometer method is mainly locatedand the visual recognition method is accurately positioned accurately. In view of thetraditional visual position based on gray level difference which is difficult to extractthe weld characteristics, the recognition method of image for welding seam based onthe color characteristics is applied, and the improved vector median filtering and theimage enhancement algorithm based on based on normalized improvement arepresented. The measures improve the color difference of multi-channels effectively,enhancing the image contrast and realizing the accurate positioning of the weld centerline. The analysis shows that error bound is1.84~3.76mm in the measurable pipelineand improves location accuracy greatly.
引文
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