基于数字图像处理的摘锭磨损程度定量分析研究

发布时间：2018-08-17 08:39

【摘要】：摘锭作为采棉机采摘棉花的重要工作部件,数量多、服役条件复杂。工作状态中的摘锭和籽棉、棉花秸秆发生直接接触,长时间的摩擦造成摘锭钩齿表面磨损,目前,摘锭磨损程度主要依靠人工判定,这种方法不仅效率低、易漏检,而且没有统一的标准,影响了摘锭正常的维护维修,因此,本文研究基于数字图像处理技术的摘锭磨损程度定量判定方法,提高摘锭磨损程度判定的准确率,为磨损摘锭检测后的更换标准提供大量数据参考,为制定维护计划和准备维护资源(如备品备件)具有重要的意义。本文通过数字图像处理技术获取摘锭钩齿轮廓的特征信息,利用SPSS软件进行统计分析得到磨损时间与磨损程度的曲线,实现了摘锭磨损程度的定量化表达,并确定了摘锭预防性维护的范围,为摘锭磨损的等级划分提供理论研究。具体研究内容和结论如下:1、基于数字图像处理技术的摘锭钩齿轮廓特征信息提取的研究。搭建了适宜采集摘锭钩齿轮廓的采集系统,确定采集系统的各个硬件设备。确定了数字图像处理系统图像增强、边缘检测、特征提取三个步骤的算法,实现了区域填充,最终求取未磨损摘锭和已磨损摘锭的像素面积差值(35)S,实现了摘锭磨损程度的定量化表达。2、磨损程度的统计分析研究。获取120组磨损摘锭样本的数据,通过SPSS软件分析得到相应曲线,结合人工主观判定的等级标准,确定了摘锭磨损程度的预警线和临界线,规定摘锭磨损程度处在预警线和临界线之间时作为预防性维护。3、摘锭备品备件管理的研究。通过数字图像处理技术获得摘锭磨损程度的定量化表达,替代了人工主观检测,并根据预防性维护的两个参照线,得知摘锭的已服役实践和预测摘锭未来服役时间,从而为摘锭的备品备件管理提供数据参考。
[Abstract]:As an important working part of cotton picking machine, ingot picking has a lot of quantity and complex service conditions. In the working state of picking ingot and seed cotton, cotton straw is in direct contact with cotton straw, and long time friction causes wear on the surface of pick ingot hook tooth. At present, the wear degree of picking ingot mainly depends on manual judgment. This method is not only low efficiency, but also easy to miss detection. Moreover, there is no uniform standard, which affects the normal maintenance and maintenance of the spindles. Therefore, this paper studies the quantitative determination method of the wear degree of the spindles based on the digital image processing technology to improve the accuracy of the determination of the wear degree of the spindles. It is of great significance to provide a large amount of data reference for the replacement standard after testing wear and tear spindles. It is of great significance to make maintenance plans and prepare maintenance resources (such as spare parts). In this paper, the characteristic information of the contour of the hook teeth is obtained by digital image processing technology. The curve of wear time and wear degree is obtained by using SPSS software, and the quantitative expression of wear degree is realized. The range of preventive maintenance of spindles is determined, which provides a theoretical study for the classification of wear of spindles. The specific research contents and conclusions are as follows: 1. Research on extracting contour information of ingot hook teeth based on digital image processing technology. A collection system is set up which is suitable for collecting the outline of the hook teeth, and the hardware equipments of the system are determined. The algorithm of image enhancement, edge detection and feature extraction in digital image processing system is determined. Finally, the pixel area difference (35) S of the unworn and worn ingots is obtained, and the quantitative expression of wear degree. 2. The statistical analysis of wear degree is realized. The data of 120 groups of wear ingot samples were obtained, the corresponding curves were obtained by SPSS software analysis, and the warning line and critical line of wear degree of picking ingot were determined by combining with the grade standard of artificial subjective judgment. When the wear degree of the spindles is between the warning line and the critical line, it is considered as the preventive maintenance. The quantitative expression of wear degree of spindles is obtained by digital image processing technology, which replaces artificial subjective testing, and according to two reference lines of preventive maintenance, it is known that the spindles are in service and the future service time of the spindles is predicted. Thus provides the data reference for the spare parts management of the spindles.
【学位授予单位】：石河子大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：S225.911;TP391.41

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