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High-precision width measurement method of laser profile sensor
Sensor Review ( IF 1.6 ) Pub Date : 2020-11-13 , DOI: 10.1108/sr-06-2019-0154
Yu Feng , Wei Tao , Yiyang Feng , Xiaoqia Yin , Na Lv , Hui Zhao

Purpose

Although a laser profile sensor (LPS) can be used to measure dimensions, the “shadow region” generally degrades the accuracy and precision of width measurements. The accuracy and precision of such measurements should be improved.

Design/methodology/approach

In this paper, the authors propose herein a technique that combines high dynamic range (HDR) imaging with logistic fitting. First, a HDR image is composed of several images acquired with different exposure times, which augments the grayscale of the object profile and significantly reduces overexposure. Next, the profile is fit to a logistic function, which provides accurate and precise edge coordinates. Finally, given the edge coordinates, the object width is calculated.

Findings

To verify the stability of this logistic algorithm, the authors simulate different noise conditions and different degrees of incomplete edge data. In addition, the progressiveness of the algorithm is demonstrated by comparing the results with those of other algorithms and with the height measurement. Furthermore, the suitability of the system is verified experimentally.

Research limitations/implications

Because of the limitation of the condition of laboratory, in the experimental section, this paper cannot represent perfectly the industrial situation. It makes this section limited in demonstration.

Originality/value

In this paper, the results show that the measurement accuracy and precision of the width is improved and exceeds that of the height measurement. The proposed HDR imaging method with logistic fitting may be applied to LPS width measurements, which should significantly aid the development of LPSs.



中文翻译:

激光轮廓传感器的高精度宽度测量方法

目的

尽管可以使用激光轮廓传感器(LPS)来测量尺寸,但“阴影区域”通常会降低宽度测量的准确性和精度。这种测量的准确性和精确度应该得到提高。

设计/方法/方法

在本文中,作者在这里提出了一种将高动态范围(HDR)成像与逻辑拟合相结合的技术。首先,HDR图像由在不同曝光时间下获取的几张图像组成,这增加了对象轮廓的灰度并显着减少了过度曝光。接下来,使轮廓适合于逻辑函数,该逻辑函数可提供精确的边缘坐标。最后,在给定边缘坐标的情况下,计算对象的宽度。

发现

为了验证该逻辑算法的稳定性,作者模拟了不同的噪声条件和不同程度的不完整边缘数据。另外,通过将结果与其他算法的结果和高度测量值进行比较,证明了该算法的先进性。此外,该系统的适用性已通过实验验证。

研究局限/意义

由于实验室条件的限制,在实验部分,本文不能完美地反映工业状况。这使本节仅限于演示。

创意/价值

结果表明,宽度的测量精度和精度有所提高,超过了高度测量的精度和精度。所提出的具有逻辑拟合的HDR成像方法可以应用于LPS宽度测量,这将大大有助于LPS的发展。

更新日期:2020-11-19
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