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中 文 摘 要
I
中
文
摘
要
固定风力发电机底座的锚杆是风力发电系统中不可缺少的部件,对整个风力发电系
统的发展起着举足轻重的作用。锚杆在制造及运输中极易产生微小裂纹,当前对其裂纹
的检测主要依靠手工视觉,存在检测效率低、准确率低、漏检率高等问题。本文根据锚
杆裂纹图像的特征,利用磁粉与数字图像处理相结合的方法来进行检测,其主要研究内
容包括:
对国内外磁粉检测技术和基于图像处理的视觉检测技术研究现状分析基础上,根据
锚杆裂纹特征和对裂纹检测系统的性能要求,设计了基于图像处理的锚杆裂纹检测系统,
完成了软硬件选型。
对采集到的锚杆表面裂纹图像进行感兴趣区域提取,在 HSV 颜色空间下将紫色置
0,解决了采集锚杆图像时因紫外灯照射产生的噪声干扰问题,并用加权平均法对图像
灰度化。对比不同滤波算法和改进后的滤波算法效果图,客观的根据图像质量指标对滤
波效果评价,体现改进算法的优越性,解决了自适应中值滤波算法繁琐和以噪音点作为
输出的问题,并对处理后的图像灰度线性变化,增强了裂纹和背景区域的对比度。
采用 Niblack 局部阈值和面积阈值相结合的方法,将锚杆表面图像中的裂纹与背景
信息分离,对信息分离后的图像进行形态学膨胀操作,补充因图像分割缺失的裂纹信息。
之后通过对裂纹信息几何特征描述,筛选出裂纹,实现锚杆表面图像的裂纹提取。
基于 MATLAB 软件 GUI 平台编写裂纹识别系统软件界面,完成软件模块设计,对
采集到的锚杆图像做检测实验分析,实验结果表明锚杆图像的综合检测正确率达到
93.33%,漏检率为 0%,满足设计要求。
关键词:锚杆;磁粉检测;图像处理;裂纹
ABSTRACT
III
ABSTRACT
The anchor rod that fixes the base of the wind turbine is an indispensable
component in the wind power generation system and plays a crucial role in the
development of the entire wind power generation system. Anchor rods are prone
to small cracks during manufacturing and transportation. Currently, the detection
of cracks mainly relies on manual vision, which has problems such as low
detection efficiency, low accuracy, and high missed detection rate. This article
uses a combination of magnetic powder and digital image processing methods
based on the characteristics of anchor crack images for detection. The main
research content includes:
Based on the analysis of the current research status of magnetic particle
testing technology and visual inspection technology based on image processing
both domestically and internationally, and based on the characteristics of anchor
rod cracks and the performance requirements for crack detection systems, an
image processing based anchor rod crack detection system was designed, and the
selection of software and hardware was completed.
Extract the region of interest from the collected image of surface cracks on
the anchor rod, set purple to 0 in the HSV color space, and solve the problem of
noise interference caused by ultraviolet light irradiation when collecting anchor
rod images. The weighted average method is used to grayize the image.
Comparing the effectiveness of different filtering algorithms and improved
filtering algorithms, objectively evaluating the filtering effect based on image
quality indicators reflects the superiority of the improved algorithm, solves the
problem of cumbersome adaptive median filtering algorithm and using noise
points as output, and linearly changes the grayscale of the processed image,
enhancing the contrast between cracks and background areas.
Using a combination of Niblack local threshold and area threshold, the
cracks in the surface image of the anchor rod are separated from the background
information, and the morphological dilation operation is performed on the
separated image to supplement the missing crack information due to image
基于图像处理的锚杆裂纹检测系统研究
IV
segmentation. Afterwards, by describing the geometric features of the crack
information, cracks were screened out to achieve crack extraction from the surface
image of the anchor rod.
Based on the MATLAB software GUI platform, the software interface of the
crack recognition system was written, and the software module design was
completed. The collected bolt images were analyzed through detection
experiments. The experimental results showed that the comprehensive detection
accuracy of the bolt images reached 93.33%, and the missed detection rate was
0%, meeting the design requirements.
Key words: Anchor rod; Magnetic particle testing; Image processing; Crack
目 录
第一章 绪论............................................................................................... 1
1.1 课题研究背景和意义 ....................................................................... 1
1.2 磁粉检测技术研究现状................................................................... 1
1.3 基于图像处理的视觉检测研究现状 .............................................. 3
1.4 研究问题的提出 ............................................................................... 5
1.5 本文研究内容及安排 ....................................................................... 6
第二章 锚杆裂纹检测系统的方案设计 .................................................. 7
2.1 方案设计 ........................................................................................... 7
2.2 系统硬件的选型 ............................................................................... 7
2.2.1 工业相机的选择 ......................................................................... 8
2.2.2 光学镜头的选择 ......................................................................... 9
2.2.3 光源的选择 ............................................................................... 10
2.2.4 磁粉类型的选择 ....................................................................... 11
2.3 系统的软件选择 ............................................................................. 13
2.4 本章小结 ......................................................................................... 14
第三章 锚杆表面裂纹图像的采集与预处理 ........................................ 15
3.1 锚杆表面裂纹图像的采集 ............................................................ 15
3.2 ROI 感兴趣区域提取 ...................................................................... 15
3.3 颜色空间转换和图像灰度化 ........................................................ 17
3.3.1 颜色空间转换方法 ................................................................... 17
3.3.2 滤除紫色干扰 ........................................................................... 18
3.3.3 图像灰度化 ............................................................................... 19
3.4 锚杆表面图像去噪 ......................................................................... 21
3.4.1 图像表面噪声 ........................................................................... 21
3.4.2 图像滤波 ................................................................................... 22
3.4.3 改进的自适应中值滤波 ........................................................... 26
3.4.4 图像降噪的客观评价 ............................................................... 28
3.5 图像的增强处理 ............................................................................. 29
3.5.1 直方图均值化 ........................................................................... 29
3.5.2 灰度线性变化 ........................................................................... 31
3.6 本章总结 ......................................................................................... 33
第四章 锚杆表面裂纹图像特征提取 .................................................... 35
4.1 图像处理的边缘检测算法 ............................................................ 35
4.1.1 传统的边缘检测算子 ............................................................... 36
4.1.2 传统边缘检测算子的对比实验 ............................................... 37
4.2 传统基于阈值的图像分割方法研究 ............................................ 38
4.2.1 直方图阈值分割 ....................................................................... 38
4.2.2 OTSU 阈值分割 ........................................................................ 39
4.2.3 Niblack 局部阈值和面积阈值分割 .......................................... 41
4.3 裂纹的形态学处理 ......................................................................... 42
4.4 裂纹的筛选 ..................................................................................... 43
4.5 裂纹的检测结果及分析................................................................. 44
4.6 本章小结 ......................................................................................... 46
第五章 检测软件设计及仿真实验结果分析 ........................................ 47
5.1 软件开发工具和模块 ..................................................................... 47
5.2 软件模块设计 ................................................................................. 47
5.3 软件功能展示及仿真实验结果分析 ............................................ 48
5.4 本章小结 ......................................................................................... 49
第六章 总结与展望 ................................................................................ 51
6.1 总结 ................................................................................................. 51
6.2 展望 ................................................................................................. 51
参考文献 ................................................................................................... 53
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