论文总字数：21175字

摘 要

工件的精确识别系统在现代工业中已被广泛应用，不仅可以实现对工件形状、颜色的精准识别，还可以实现对工件螺纹数的精准识别。随着现代工业的不断发展，这种识别系统将在未来的生产活动中扮演越来越重要的角色。精确而又精准的识别结果，将有利于我们解放劳动力，降低生产成本，从而提升整个生产的经济效益。

本文以CSY环形实验带模拟生产流水线，借助普通usb摄像头及LabVIEW软件，实现工件的形状识别、颜色识别以及螺钉的螺纹数识别三种功能，主要工作如下：

（1）实现了工件形状的精确识别。本文在实现形状识别时分为静态图像识别和动态工件识别两种方法，通过摄像头对工件实际图像的采集，并与比较模块中储存的模板进行识别比对，以此实现工件形状识别。

（2）实现了工件螺纹数的精准识别。通过普通usb摄像头采集螺钉模板，并对其进行灰度化、增强对比度、阈值分割、填充孔洞等处理，然后根据边缘波峰的检测数量，对其进行运算，得到螺纹数，从而实现对螺钉螺纹数的检测功能。

（3）实现了工件颜色的准确识别。通过外接摄像头对工件进行颜色识别、采集、添加模板、色彩值测试等一系列操作，并将其模板与CSY环形实验带上的运动工件进行比对，完成颜色识别。

关键词：CSY环形带实验平台 精确识别 螺纹数识别 颜色识别

Abstract

The accurate identification system of workpieces is widely used in modern industry. It not only can accurately identify the shape and color of workpieces, but also can accurately identify the number of threads for a specific screw workpiece. With the continuous development of modern industry, this identification system will play an increasingly important role in the future production activities. Accurate and accurate recognition results will help us liberate the labor force and reduce the production cost, thereby increasing the economic benefits of the entire production.

This article simulates the CSY loop test zone as a production line. With the help of an ordinary usb camera and LabVIEW software, three functions are realized: shape recognition, color recognition, and screw thread number recognition. The main tasks are as follows:

(1) The accurate identification of the workpiece shape is achieved. In the realization of shape recognition, we are divided into static image recognition and dynamic workpiece recognition. The dynamic recognition is to capture the video captured by the camera to convert it into a single image and send it to the comparison module for identification. The static recognition is It is to send the collected workpiece pictures to the comparison module for comparison and identification.

(2) The accurate identification of the number of workpiece threads is achieved. In this paper, a common USB camera is used to collect screw templates, and grayscale processing, contrast enhancement, threshold segmentation, and filling holes are performed. Then, calculation is performed based on the number of edge detection peaks so that the number of screw threads can be detected. .

(3) The color of the workpiece is accurately identified. In the color recognition experiment, an external camera is used to perform color recognition, collection, template addition, color value testing and other operations on the workpiece, and the template is compared with the moving workpiece on the CSY circular experiment belt to complete the color recognition.

Keywords: CSY annular belt experimental platform; accurate identification of thread number recognition; color recognition.

目 录

摘要 I

Abstract II

第一章 绪论 1

1.1课题研究背景 1

1.2课题研究现状 1

1.2.1工件精确识别的国内外现状 1

1.2.2工件形状精确识别方法概述 2

1.3本文的研究内容 3

第二章 实验台及使用软件简介 4

2.1 实验台介绍 4

2.2 本文使用软件介绍 5

2.2.1 虚拟仪器 6

2.2.2 LABVIEW软件的实际应用 6

2.2.3 附属模块 7

第三章 工件形状的精确识别 8

3.1 工件精确识别的原理 8

3.1.1 识别原理 8

3.1.2 通讯与模板采集步骤 8

3.2 工件形状识别的算法实现 9

3.2.1 工件形状的静态识别算法 9

3.2.2 工件形状的动态识别算法 12

第四章 工件的颜色识别 16

4.1 NI助手简介 16

4.2 工件颜色识别原理 16

4.3 工件颜色识别的算法实现 17

4.3.1 NI助手创建的程序步骤 17

4.3.2 工件颜色识别程序及人机交互界面展示 18

4.3.3 颜色识别算法优化 20

第五章 螺纹数的精准识别 23

5.1 螺纹数精准识别算法思路 23

5.1.1 图像采集原理 23

5.1.2 图像处理过程 23

5.1.3 边缘检测原理 23

5.2 人机交互界面操作步骤 23

5.2.1 螺纹数静态图像识别人机界面操作步骤 23

5.2.2 螺纹数动态采集识别人机界面操作步骤 24

5.3 螺纹数识别算法 24

5.4 螺纹数识别实验分析 25

第六章 总结和展望 29

参考文献 31

致谢 34

绪论

1.1课题研究背景

随着国民经济的快速发展，人民生活水平的不断提高，使得人们对物质的需求不断增大，因此，工厂产品的生产压力也逐渐增大。虽然我国已基本实现了自动化生产，但是工件精确识别技术，部分厂家仍停留在人工操作，较进口的生产线相对落后。人工识别检测工件，不仅分拣的速度慢，而且这样的分拣方式也无法与现代自动化产线相契合；并且，识别时无法避免误差也是目前存在的问题之一。而另一个明显存在的问题是人工接触式的操作方式使得工人劳动强度增大，生产成本也随之增加。这就使得基于视觉摄像头配合下的非接触式测量装置的必要性显现出来。

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