环境光干扰下轨道车辆轮纹轮廓的激光条纹分割算法

IF 3.5 2区 工程技术 Q2 OPTICS Optics and Lasers in Engineering Pub Date : 2024-09-19 DOI:10.1016/j.optlaseng.2024.108600
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引用次数: 0

摘要

在轨道车辆车轮踏面的测量中,线激光视觉测量技术具有良好的应用前景。然而,在实际应用场景中,环境光的强度和位置会不断变化。传统的激光条纹分割算法往往无法得出准确的结果,导致车轮踏面的测量精度降低。为了解决这个问题,我们提出了一种激光条纹分割算法。首先,利用 SSR 算法和帧减法去除背景噪声。然后,使用 OTSU 方法进行初步分割。然后,利用几何平均滤波和形态学闭合对图像进行平滑处理并降低噪声。最后,根据图像各区域的灰度分布特征建立分割函数,实现激光条纹的精确分割。在环境光干扰下,设计并进行了激光条纹分割实验、激光条纹分割对比实验和车轮花纹几何提取实验。实验结果表明,所提算法的分割成功率不<90.625%。与其他算法相比,所提出的算法具有更优越的分割效果。所提算法可提高测量精度。在法兰高度测量中,平均误差从 0.298 mm 下降到 0.161 mm,标准偏差从 0.600 下降到 0.548。在测量凸缘宽度时,平均误差保持在 0.200 毫米,标准偏差从 0.681 降至 0.536。在环境光强为 37lux∼1050 lx 且激光功率不超过 50mW 的条件下,所提出的算法能较好地实现激光条纹的自适应分割。
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A laser stripe segmentation algorithm for wheel tread profile of rail vehicles under ambient light interference

In the measurement of the wheel tread in rail vehicles, line laser vision measurement technology has a good application prospect. However, the intensity and location of the ambient light will constantly change in the actual application scenarios. Traditional laser stripe segmentation algorithms often fail to produce accurate results, leading to decreased measurement precision in wheel tread. To solve the problem, a segmentation algorithm for laser stripes was proposed. Firstly, the SSR algorithm and frame subtraction were utilized to remove the background noise. Then, the OTSU method was used for the preliminary segmentation. After that, smoothing Images and reducing noise were performed with geometric mean filtering and morphological closing. Finally, the segmentation function which was based on the gray scale distribution characteristics of each region of the image was established to achieve the accurate segmentation of laser stripes. Laser stripe segmentation experiments, laser stripe segmentation comparison experiments, and wheel tread geometry extraction experiments were designed and conducted under the ambient light interference. The experimental results show that the segmentation success rate of the proposed algorithm is not <90.625 %. The proposed algorithm has a superior segmentation effect compared to other algorithms. The proposed algorithm can improve the measurement accuracy. For flange height measurement, the mean error decreased from 0.298 mm to 0.161 mm, and the standard deviation decreased from 0.600 to 0.548. For flange width measurement, the mean error remained constant at 0.200 mm, and the standard deviation decreased from 0.681 to 0.536. Under the condition that the ambient light intensity is in the range of 37lux∼1050 lx and the laser power is not <50mW, the proposed algorithm can better realize the adaptive segmentation of laser stripes.

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来源期刊
Optics and Lasers in Engineering
Optics and Lasers in Engineering 工程技术-光学
CiteScore
8.90
自引率
8.70%
发文量
384
审稿时长
42 days
期刊介绍: Optics and Lasers in Engineering aims at providing an international forum for the interchange of information on the development of optical techniques and laser technology in engineering. Emphasis is placed on contributions targeted at the practical use of methods and devices, the development and enhancement of solutions and new theoretical concepts for experimental methods. Optics and Lasers in Engineering reflects the main areas in which optical methods are being used and developed for an engineering environment. Manuscripts should offer clear evidence of novelty and significance. Papers focusing on parameter optimization or computational issues are not suitable. Similarly, papers focussed on an application rather than the optical method fall outside the journal''s scope. The scope of the journal is defined to include the following: -Optical Metrology- Optical Methods for 3D visualization and virtual engineering- Optical Techniques for Microsystems- Imaging, Microscopy and Adaptive Optics- Computational Imaging- Laser methods in manufacturing- Integrated optical and photonic sensors- Optics and Photonics in Life Science- Hyperspectral and spectroscopic methods- Infrared and Terahertz techniques
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