受电弓论文：受电弓典型故障图像检测算法的研究
【中文摘要】随着高速铁路事业不断的飞速发展,对其运输的安
全性的要求越来越高。为电力机车提供能量的主要部件之一是受电弓,它的滑板的表面直接与接触导线接触,滑板表面和导线之间构成了一对特别的摩擦副,当滑板磨耗超限、弓头倾斜和羊角缺失等典型故障出现的时候,都可能会引发严重交通事故,危及行车安全。因而,精确地检测出磨耗值,判断出弓头倾斜和羊角缺失的情况对于受电弓的维护和行车安全十分重要。本文基于一种采用图像测量技术检测受电弓的检测方案,利用非接触式测量,不需要停车检测,可以实现在线检测。该受电弓检测系统主要采用了近年来被广泛应用于测量领域中的图像测量技术,达到了检测系统测量效率高,检测精度高等要求。首先,在充分调研了国内外当前受电弓检测技术和高速铁路的发展情况的基础上,选择了采用图像测量技术检测受电弓。其次详细分析了滑板磨耗检测系统,弓头倾斜检测系统及羊角缺失检测系统的总体设计方案、检测原理及相关的图像算法。在滑板磨耗检测系统的图像预处理中,采用了图像增强技术和结合形态学的滤波技术,减少光照不均等因素对图像成像的影响；在边缘检测中采用了改进的Canny算法,减少了边缘信息的丢失,在一定程度上保证了磨耗检测的精度。在弓头倾斜检测系统中,采用Radon变换求取倾斜角,方法简单易行。在羊角缺失检测系统中,探索性地展示出了一种判断受电弓羊角缺失情况的方法。最后本文进行了受电弓检测系统的试验,对试验过程和结果进
行了分析和研究,试验结果表明,所研究的系统能够完成预期的滑板磨耗、弓头倾斜及羊角缺失的检测任务,具有非接触、高效率、高精度等优点,对我国高速铁路受电弓典型故障的检测具有一定的理论研究价值和实际应用意义。
【英文摘要】With the rapid development of the high-speed railway industry continuously, the transportation security demands more and more. Pantograph is one of the important
components which provide power to electric locomotive and metro. The surface of the slide is next to the contact wire, and they form a pair of special friction pair, when the abrasion of the slide is greater than a threshold, the inclination of bow head and horns missing will cause significant vehicle accident, seriously endanger security. Therefore, it is very important for accurately detecting the abrasion value, judging the bow head inclination and horns missing of transportation.A
pantograph detection method taking on image measurement techniques has been proposed in this paper, which is a
non-contact and non-stopping inspecting means with the online detection. Image measurement technology widely used in filed of measurement is primarily applied in this pantograph
detection system, and it makes sure the system meets the
requirement of high efficiency, high precision and so on.First,
this paper thoroughly investigates some detecting technologies for pantograph and metro development situations at home and abroad, on the basis of the adoption image measurement
technologies to detect pantograph. Secondly, it analyzes in detail the overall system design schemes, detection principles and the relevant image algorithms of slide abrasion detection system, bow head inclination detection system and horns missing detection system. In the image preprocessing, it introduces the image enhancement technology and the filter technology
combined with the morphology to reduce the effect of image formation caused by uneven illuminate and so on factors. In edge detection, an improved Canny algorithm is proposed, which reduces the loss of edge information and guarantees the
accuracy of abrasion detection in a certain extent. The bow head inclination detection system uses Radon transformation in calculation gradient that is a simple method. In horns missing detection system, it displayed a judgment of horns missing methods in the innovation. Finally, this thesis describes test process and test results of pantograph detection, and the results are analyzed and investigated showing that the system can accomplish expected detection tasks, with non-contact, high efficiency, high precision and so on advantages. The
results of research propose certain theoretical and practical significance for pantograph detection system of high-speed railway in China.
【关键词】受电弓 磨耗检测 图像处理 边缘检测 弓头倾斜 羊
角缺失
【英文关键词】Pantograph Slide Abrasion Detection Image Processing Edge Detection Bow head
inclination Horns missing
【目录】受电弓典型故障图像检测算法的研究
6-7Abstract7第一章 绪论11-18摘要1.1 论文背
1.2.1 传景及意义11-12
统的受电弓检测系统
测系统13
13-14
14-16
16-18
容16-171.2 国内外研究现状12-1612-131.2.2 安装在机车上的受电弓检1.2.3 在线定点式受电弓检测系统1.2.4 基于图像处理技术的受电弓检测系统1.3 课题的研究目、内容及结构安排1.3.1 课题的研究目的161.3.3 课题的结构安排17-181.3.2 课题的研究内第二章 受电弓检测系统结构与检测原理18-26
18-222.1 检测系统结构2.1.2 检测系
2.3 章节2.1.1 检测系统结构设计18-202.2 检测系统原理22-24统硬件组成20-22
小结24-26
26-45第三章 受电弓检测系统算法设计与实现3.1 滑板磨耗检测系统算法设计与实现
26-38
28-32
接34-353.1.1 图像裁剪27-283.1.3 图像边缘检测32-343.1.2 图像预处理3.1.4 图像边缘连3.1.6 3.1.5 接触导线及上下边缘定位35-37
判断滑板磨耗37-38
38-40
393.2 弓头倾斜检测系统算法设计与实现3.2.2 图像边缘检测3.3 羊角缺失检测系统算
3.3.2 图
3.4 章节3.2.1 图像裁剪38-393.2.3 计算倾斜角39-40法设计与实现40-44像二值化42-43
小结44-45
45-53
45-48
47-48
48-50
49-50
50-52
52
总结533.3.1 图像裁剪41-423.3.3 判断羊角缺失43-44第四章 受电弓检测系统检测结果与分析4.1 滑板磨耗检测系统检测结果与分析4.1.1 检测试验45-474.1.2 误差分析4.2 弓头倾斜检测系统检测结果与分析4.2.1 检测试验48-494.2.2 误差分析4.3 羊角缺失检测系统检测结果与分析4.3.1 检测试验50-524.4 章节小结52-534.3.2 误差分析工作结论与展望53-55致谢55-56未来研究工作的展望53-55
参考文献56-61附录: 部分算法Matlab源代码61-71攻读硕士学位期间发表的论文及科研成果71
受电弓论文：受电弓典型故障图像检测算法的研究
【中文摘要】随着高速铁路事业不断的飞速发展,对其运输的安
全性的要求越来越高。为电力机车提供能量的主要部件之一是受电弓,它的滑板的表面直接与接触导线接触,滑板表面和导线之间构成了一对特别的摩擦副,当滑板磨耗超限、弓头倾斜和羊角缺失等典型故障出现的时候,都可能会引发严重交通事故,危及行车安全。因而,精确地检测出磨耗值,判断出弓头倾斜和羊角缺失的情况对于受电弓的维护和行车安全十分重要。本文基于一种采用图像测量技术检测受电弓的检测方案,利用非接触式测量,不需要停车检测,可以实现在线检测。该受电弓检测系统主要采用了近年来被广泛应用于测量领域中的图像测量技术,达到了检测系统测量效率高,检测精度高等要求。首先,在充分调研了国内外当前受电弓检测技术和高速铁路的发展情况的基础上,选择了采用图像测量技术检测受电弓。其次详细分析了滑板磨耗检测系统,弓头倾斜检测系统及羊角缺失检测系统的总体设计方案、检测原理及相关的图像算法。在滑板磨耗检测系统的图像预处理中,采用了图像增强技术和结合形态学的滤波技术,减少光照不均等因素对图像成像的影响；在边缘检测中采用了改进的Canny算法,减少了边缘信息的丢失,在一定程度上保证了磨耗检测的精度。在弓头倾斜检测系统中,采用Radon变换求取倾斜角,方法简单易行。在羊角缺失检测系统中,探索性地展示出了一种判断受电弓羊角缺失情况的方法。最后本文进行了受电弓检测系统的试验,对试验过程和结果进
行了分析和研究,试验结果表明,所研究的系统能够完成预期的滑板磨耗、弓头倾斜及羊角缺失的检测任务,具有非接触、高效率、高精度等优点,对我国高速铁路受电弓典型故障的检测具有一定的理论研究价值和实际应用意义。
【英文摘要】With the rapid development of the high-speed railway industry continuously, the transportation security demands more and more. Pantograph is one of the important
components which provide power to electric locomotive and metro. The surface of the slide is next to the contact wire, and they form a pair of special friction pair, when the abrasion of the slide is greater than a threshold, the inclination of bow head and horns missing will cause significant vehicle accident, seriously endanger security. Therefore, it is very important for accurately detecting the abrasion value, judging the bow head inclination and horns missing of transportation.A
pantograph detection method taking on image measurement techniques has been proposed in this paper, which is a
non-contact and non-stopping inspecting means with the online detection. Image measurement technology widely used in filed of measurement is primarily applied in this pantograph
detection system, and it makes sure the system meets the
requirement of high efficiency, high precision and so on.First,
this paper thoroughly investigates some detecting technologies for pantograph and metro development situations at home and abroad, on the basis of the adoption image measurement
technologies to detect pantograph. Secondly, it analyzes in detail the overall system design schemes, detection principles and the relevant image algorithms of slide abrasion detection system, bow head inclination detection system and horns missing detection system. In the image preprocessing, it introduces the image enhancement technology and the filter technology
combined with the morphology to reduce the effect of image formation caused by uneven illuminate and so on factors. In edge detection, an improved Canny algorithm is proposed, which reduces the loss of edge information and guarantees the
accuracy of abrasion detection in a certain extent. The bow head inclination detection system uses Radon transformation in calculation gradient that is a simple method. In horns missing detection system, it displayed a judgment of horns missing methods in the innovation. Finally, this thesis describes test process and test results of pantograph detection, and the results are analyzed and investigated showing that the system can accomplish expected detection tasks, with non-contact, high efficiency, high precision and so on advantages. The
results of research propose certain theoretical and practical significance for pantograph detection system of high-speed railway in China.
【关键词】受电弓 磨耗检测 图像处理 边缘检测 弓头倾斜 羊
角缺失
【英文关键词】Pantograph Slide Abrasion Detection Image Processing Edge Detection Bow head
inclination Horns missing
【目录】受电弓典型故障图像检测算法的研究
6-7Abstract7第一章 绪论11-18摘要1.1 论文背
1.2.1 传景及意义11-12
统的受电弓检测系统
测系统13
13-14
14-16
16-18
容16-171.2 国内外研究现状12-1612-131.2.2 安装在机车上的受电弓检1.2.3 在线定点式受电弓检测系统1.2.4 基于图像处理技术的受电弓检测系统1.3 课题的研究目、内容及结构安排1.3.1 课题的研究目的161.3.3 课题的结构安排17-181.3.2 课题的研究内第二章 受电弓检测系统结构与检测原理18-26
18-222.1 检测系统结构2.1.2 检测系
2.3 章节2.1.1 检测系统结构设计18-202.2 检测系统原理22-24统硬件组成20-22
小结24-26
26-45第三章 受电弓检测系统算法设计与实现3.1 滑板磨耗检测系统算法设计与实现
26-38
28-32
接34-353.1.1 图像裁剪27-283.1.3 图像边缘检测32-343.1.2 图像预处理3.1.4 图像边缘连3.1.6 3.1.5 接触导线及上下边缘定位35-37
判断滑板磨耗37-38
38-40
393.2 弓头倾斜检测系统算法设计与实现3.2.2 图像边缘检测3.3 羊角缺失检测系统算
3.3.2 图
3.4 章节3.2.1 图像裁剪38-393.2.3 计算倾斜角39-40法设计与实现40-44像二值化42-43
小结44-45
45-53
45-48
47-48
48-50
49-50
50-52
52
总结533.3.1 图像裁剪41-423.3.3 判断羊角缺失43-44第四章 受电弓检测系统检测结果与分析4.1 滑板磨耗检测系统检测结果与分析4.1.1 检测试验45-474.1.2 误差分析4.2 弓头倾斜检测系统检测结果与分析4.2.1 检测试验48-494.2.2 误差分析4.3 羊角缺失检测系统检测结果与分析4.3.1 检测试验50-524.4 章节小结52-534.3.2 误差分析工作结论与展望53-55致谢55-56未来研究工作的展望53-55
参考文献56-61附录: 部分算法Matlab源代码61-71攻读硕士学位期间发表的论文及科研成果71