基于光斑位置的起重机轨道高度差自动检测方法

doi:10.16180/j.cnki.issn1007-7820.2022.01.004

摘要/Abstract

摘要：

针对目前起重机轨道自动检测技术无法满足轨道检测要求的问题,文中提出基于光斑位置的起重机轨道高度差自动检测方法。在轨道两侧分别放置激光发射器与成像板,激光经过传输,投射在成像板上形成光斑图像。对光斑图像灰度分布进行修整,增强图像清晰度与灰度分布差异。利用改进二维Otsu算法准确分割光斑图像,提取光斑边缘进行圆拟合。计算边缘拟合圆中心坐标,完成光斑图像位置识别。计算光斑在竖直方向上位置偏差得到起重机轨道两检测点之间高度差。通过试验可知,采用本文所提检测方法进行光斑图像位置识别的平均误差约为±0.22 mm,最大误差不超过±0.4 mm,与传统光斑图像位置识别方法相比,本文方法的精度提高了约0.10 mm。基于光斑位置轨道高度差检测的平均误差约为±0.8 mm,误差范围为±1.8 mm,满足轨道检测要求。

关键词: 激光光束, 位置识别, 图像处理, 起重机械, 轨道检测, 光斑图像, 光电检测, 机器视觉

Abstract:

The automatic detection technology of crane track is immature, which cannot meet the requirements of the track detection. In view of this problem, an automatic detection method of crane track altitude based on the position of the light spot image is proposed. A laser launcher and an imaging board are placed on both sides of the track. The laser is transmitted and projected on the imaging board to form a spot image. The gray-scale distribution of the light spot image is trimmed to enhance the difference between image sharpness and gray-scale distribution. The improved two-dimensional Otsu algorithm is used to accurately segment the spot image, and the edge of the spot is extracted for circle fitting. The center coordinates of the edge fitting circle are calculated to complete the spot image position recognition. Moreover, the position deviation of the light spot in the vertical direction is calculated to obtain the height difference between the two detection points of the crane track. Experimental research shows that the average error of spot image position recognition using the detection method of spot position recognition in this study is about ±0.22 mm, and the maximum error does not exceed ±0.4 mm. Compared with the traditional method of spot image position recognition, the accuracy of the proposed methed is improved by about 0.10 mm. Based on the track height difference of the spot position, the average error of detection is about ±0.8 mm, and the error range is ±1.8 mm, which meets the requirements of track detection.

Key words: laser beam, position recognition, image processing, hoisting machinery, track detection, spot image, photoelectric detection, machine vision

中图分类号:

TP391.4

宗圣康,程建鹏,张西良. 基于光斑位置的起重机轨道高度差自动检测方法[J]. 电子科技, 2022, 35(1): 21-28.

ZONG Shengkang,CHENG Jianpeng,ZHANG Xiliang. Automatic Detection Method of Crane Track Altitude Difference Based on Spot Position[J]. Electronic Science and Technology, 2022, 35(1): 21-28.

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修整拟合方法			亮度阈值方法
实际距离	识别结果	识别误差	识别结果	识别误差
3.12	3.30	0.18	3.48	0.36
3.18	3.41	0.23	2.95	-0.25
2.96	3.12	0.16	2.67	-0.29
3.22	3.02	-0.20	3.60	0.38
2.88	3.04	0.16	2.52	-0.36
6.26	6.08	-0.18	6.57	0.30
6.04	6.27	0.25	5.70	-0.34
6.12	6.29	0.18	6.41	0.29
5.92	5.66	-0.26	5.54	-0.38
5.98	5.77	-0.20	6.27	0.29
9.88	10.28	0.40	10.21	0.33
9.92	9.69	-0.23	9.81	-0.11
10.14	9.96	-0.18	9.95	-0.19
9.86	10.08	0.22	10.39	0.53
10.18	10.34	0.16	9.83	-0.35

次数	Δh'₁检测结果/mm	Δh'₁检测误差/mm	Δh'₂检测结果/mm	Δh'₂检测误差/mm
1	15.7	1.4	9.3	-1.1
2	15.3	1.0	12.0	1.6
3	13.1	-1.2	12.2	1.8
4	15.6	1.3	11.8	1.4
5	16.0	1.7	9.7	-0.7
平均值	15.1	0.8	11.0	0.6