【摘要】：摘錠作為采棉機采摘棉花的重要工作部件,數(shù)量多、服役條件復(fù)雜。工作狀態(tài)中的摘錠和籽棉、棉花秸稈發(fā)生直接接觸,長時間的摩擦造成摘錠鉤齒表面磨損,目前,摘錠磨損程度主要依靠人工判定,這種方法不僅效率低、易漏檢,而且沒有統(tǒng)一的標(biāo)準(zhǔn),影響了摘錠正常的維護維修,因此,本文研究基于數(shù)字圖像處理技術(shù)的摘錠磨損程度定量判定方法,提高摘錠磨損程度判定的準(zhǔn)確率,為磨損摘錠檢測后的更換標(biāo)準(zhǔn)提供大量數(shù)據(jù)參考,為制定維護計劃和準(zhǔn)備維護資源(如備品備件)具有重要的意義。本文通過數(shù)字圖像處理技術(shù)獲取摘錠鉤齒輪廓的特征信息,利用SPSS軟件進行統(tǒng)計分析得到磨損時間與磨損程度的曲線,實現(xiàn)了摘錠磨損程度的定量化表達,并確定了摘錠預(yù)防性維護的范圍,為摘錠磨損的等級劃分提供理論研究。具體研究內(nèi)容和結(jié)論如下:1、基于數(shù)字圖像處理技術(shù)的摘錠鉤齒輪廓特征信息提取的研究。搭建了適宜采集摘錠鉤齒輪廓的采集系統(tǒng),確定采集系統(tǒng)的各個硬件設(shè)備。確定了數(shù)字圖像處理系統(tǒng)圖像增強、邊緣檢測、特征提取三個步驟的算法,實現(xiàn)了區(qū)域填充,最終求取未磨損摘錠和已磨損摘錠的像素面積差值(35)S,實現(xiàn)了摘錠磨損程度的定量化表達。2、磨損程度的統(tǒng)計分析研究。獲取120組磨損摘錠樣本的數(shù)據(jù),通過SPSS軟件分析得到相應(yīng)曲線,結(jié)合人工主觀判定的等級標(biāo)準(zhǔn),確定了摘錠磨損程度的預(yù)警線和臨界線,規(guī)定摘錠磨損程度處在預(yù)警線和臨界線之間時作為預(yù)防性維護。3、摘錠備品備件管理的研究。通過數(shù)字圖像處理技術(shù)獲得摘錠磨損程度的定量化表達,替代了人工主觀檢測,并根據(jù)預(yù)防性維護的兩個參照線,得知摘錠的已服役實踐和預(yù)測摘錠未來服役時間,從而為摘錠的備品備件管理提供數(shù)據(jù)參考。
[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.
【學(xué)位授予單位】：石河子大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：S225.911;TP391.41

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