[1]张飞翔,花海燕,张杰,等.矩形内花键轮廓自主识别与视觉测量影响分析[J].福建理工大学学报,2025,23(01):48-56.[doi:10.3969/j.issn.2097-3853.2025.01.004]
 ZHANG Feixiang,HUA Haiyan,ZHANG Jie,et al.Influence analysis of contour autonomous recognition and visual measurement for rectangular internal spline[J].Journal of Fujian University of Technology;,2025,23(01):48-56.[doi:10.3969/j.issn.2097-3853.2025.01.004]
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矩形内花键轮廓自主识别与视觉测量影响分析
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《福建理工大学学报》[ISSN:2097-3853/CN:35-1351/Z]

卷:
第23卷
期数:
2025年01期
页码:
48-56
栏目:
出版日期:
2025-02-26

文章信息/Info

Title:
Influence analysis of contour autonomous recognition and visual measurement for rectangular internal spline
作者:
张飞翔花海燕张杰郭浩浩
福建理工大学机械与汽车工程学院
Author(s):
ZHANG Feixiang HUA Haiyan ZHANG Jie GUO Haohao
Fujian Key Laboratory of Intelligent Machining Technology and Equipment, Fujian University of Technology
关键词:
矩形内花键自主识别视觉测量行为影响
Keywords:
rectangular internal spline autonomous recognition visual measurement behavior influence
分类号:
TH124
DOI:
10.3969/j.issn.2097-3853.2025.01.004
文献标志码:
A
摘要:
针对小尺寸内花键轮廓特征检测难度大、效率低的问题,开展基于视觉的轮廓特征识别与尺寸测量方法研究。以花键套筒为研究对象,从矩形内花键几何特征分析入手,建立轮廓特征识别与视觉测量分析机制,提出了基于标志特征识别的图像自主找正与轮廓信息提取策略;设计了视觉测量行为分层分析流程。通过实验分析了图像采集、预处理和特征提取3 环节的行为变化对内花键几何参数测量的影响,并实现行为优选。实验结果表明,优选方案对槽宽的测量误差可控制在6.3 μm 以内,外径测量误差在20 μm 左右,内径测量误差在3 μm 以内,单个被测量平均测量用时不高于320 ms,具有较高的测量精度和效率。
Abstract:
Aiming at the difficulty and low efficiency of contour feature detection for small-sized internal spline, the vision-based method for recognizing and measuring geometric contour feature was carried out. Starting from the analysis of the geometric characteristics for the rectangular inner spline by taking the spline sleeve as the research object, the contour feature recognition and visual measurement analysis mechanism was established. And then, a new strategy of image self-alignment and contour information extraction based on the recognition of key features was proposed. After designing the hierarchical analysis process of visual measurement behavior, the influence of behavior changes in image acquisition, preprocessing and feature extraction on the measurement of internal spline geometric parameters was analyzed through experiments, and the behavior optimization was realized. Results show that the measurement error for the keyway width can be controlled within 6.3 μm. Meanwhile, the measurement error for the outer diameter is about 20μm and that for the inner diameter is within 3μm. The average measurement time of a single measurement is no more than 320ms, which has high accuracy and efficiency.

参考文献/References:

[1] 王锐锋,徐智浩,刘成沛,等. 机械系统直轴零件直径高精度视觉测量方法研究[J]. 仪表技术与传感器,2023(7):111-116.[2] 吕宁. 基于机器视觉的轴套尺寸测量技术的研究[D]. 哈尔滨:哈尔滨工业大学,2022.[3] 李鹏阳,杨文辉,曹利平,等. 圆盘类零件几何量机器视觉测量技术研究[J]. 西安工业大学学报,2020,40(6):598-604.[4] DUAN Z Y,WANG N,FU J S,et al. High precision edge detection algorithm for mechanical parts[J]. Measurement Science Review,2018,18(2):65-71.[5] 江磊,朱华炳,王烽,等. 基于机器视觉的汽车半轴花键参数检测[J]. 组合机床与自动化加工技术,2019(11):119-122.[6] 廉凤慧. 基于线结构光的矩形花键轴视觉测量技术研究[D]. 长春:吉林大学,2019.[7] 师力力. 基于面结构光的矩形花键轴测量技术研究[D]. 西安:西安工业大学,2021.[8] MORU D K,BORRO D. A machine vision algorithm for quality control inspection of gears[J]. The International Journal of Advanced Manufacturing Technology,2020,106(1):105-123.[9] 陈怡然,廖宁,刘超. 基于机器视觉的圆形零件尺寸参数测量[J]. 工具技术,2022,56(3):109-113.[10] 尹婉婉,赵文辉,张静. 基于机器视觉的摆线轮精度综合测量[J]. 计量学报,2023,44(6):844-851.

更新日期/Last Update: 2025-02-25