發(fā)布時間：2018-05-12 13:05

  本文選題：機(jī)器視覺 + 儀表　； 參考：《湖北工業(yè)大學(xué)》2017年碩士論文

【摘要】：本文基于機(jī)器視覺技術(shù)的研究,針對汽車組合儀表中需要被檢測的繁雜信息,包括指針、燈和字符等,設(shè)計并實(shí)現(xiàn)了一整套檢測系統(tǒng)來對其進(jìn)行智能檢測。相比于傳統(tǒng)的人工目檢,不僅降低了檢測誤差,而且還提高了生產(chǎn)效率。主要工作如下:1.通過研究汽車儀表自身特點(diǎn),結(jié)合實(shí)際的檢測過程,提出了整個儀表檢測系統(tǒng)的設(shè)計方案。硬件方面,根據(jù)實(shí)際的檢測需求,采用集成式的方式進(jìn)行儀表驅(qū)動設(shè)計,并選擇合適的圖像采集裝置;軟件方面,由檢測的內(nèi)容,設(shè)計了汽車組合儀表整個檢測的流程。2.針對用傳統(tǒng)的圖像減影法提取指針存在的不足,提出了一種基于高精度模板匹配的減影法,為有效的獲取指針圖像提供了保障。然后分析各種直線提取的方法,根據(jù)儀表自身特點(diǎn),提出了結(jié)合用最小二乘法來擬合橢圓的方法,提取橢圓長軸作為直線,測量該直線與水平線之間的夾角,再由指針中心與旋轉(zhuǎn)中心的相對位置,確定指針的實(shí)際偏轉(zhuǎn)角度。3.研究了儀表LED燈的檢測方法,通過灰度值確定其亮度,轉(zhuǎn)換到HSV色域空間內(nèi)測量色調(diào)值確定其顏色,結(jié)合集合的思想確定其是否存在連錫的情況。研究了段式燈的檢測方法,通過擬合出段式燈的最小外接矩形進(jìn)行來段式燈的檢測。研究了字符的檢測方法,通過字符預(yù)處理、字符分割和支持向量機(jī)的方法識別液晶屏上的數(shù)字。4.由提出的硬件、軟件的設(shè)計方案和圖像處理算法完成對整個檢測系統(tǒng)的實(shí)現(xiàn)。操作檢測系統(tǒng),對東風(fēng)汽車康明斯組合儀表進(jìn)行檢測實(shí)驗(yàn)。檢測實(shí)驗(yàn)結(jié)果表明,本文所設(shè)計實(shí)現(xiàn)的基于機(jī)器視覺的汽車組合儀表檢測系統(tǒng)能夠完成對儀表較為全面的檢測,在時間消耗較少的情況下能夠保證各個檢測項目的精準(zhǔn)檢測,滿足實(shí)際的工業(yè)檢測要求,具有一定的發(fā)展前景和實(shí)用價值。
[Abstract]:Based on the research of machine vision technology, this paper designs and implements a set of detection system to detect the complex information, including pointer, lamp and character, which need to be detected in the automobile combination instrument. Compared with the traditional manual inspection, it not only reduces the detection error, but also improves the production efficiency. The main work is as follows: 1. The design scheme of the whole instrument detection system is put forward by studying the characteristics of the automobile instrument and combining the actual testing process. In the hardware aspect, according to the actual testing demand, the instrument driving design is carried out in the integrated way, and the appropriate image acquisition device is selected. In the software aspect, the whole detection process of the automobile combination instrument is designed by the content of the detection. 2. Aiming at the shortcomings of traditional image subtraction method, a subtraction method based on high precision template matching is proposed, which provides a guarantee for obtaining pointer images effectively. According to the characteristics of the instrument, a method of fitting the ellipse with the least square method is put forward. The long axis of the ellipse is extracted as the straight line, and the angle between the line and the horizontal line is measured. Then the relative position of the center of the pointer and the center of rotation is used to determine the actual deflection angle of the pointer. 3. The detection method of instrument LED lamp is studied. The brightness of instrument LED lamp is determined by gray value, and the color of instrument LED lamp is determined by converting it to the measurement hue value in HSV gamut space, and the existence of tin is determined by combining with the idea of set. The detection method of segment lamp is studied, and the detection of segment lamp is carried out by fitting the minimum external rectangle of segment lamp. The method of character detection is studied. The method of character preprocessing, character segmentation and support vector machine (SVM) is used to identify the number. 4 on the LCD screen. By the proposed hardware, software design and image processing algorithm to complete the implementation of the whole detection system. Operate the detection system and test the Cummins instrument of Dongfeng Automobile. The test results show that the vehicle combination instrument detection system based on machine vision designed in this paper can complete the more comprehensive detection of the instrument and ensure the accurate detection of each test item in the case of less time consumption. To meet the actual industrial testing requirements, has a certain development prospects and practical value.
【學(xué)位授予單位】：湖北工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP391.41;U463.7

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 朱柏林;郭亮;吳清文;;基于ORB和改進(jìn)Hough變換的指針儀表智能識讀方法[J];儀表技術(shù)與傳感器;2017年01期

2 尹紅敏;葛廣英;肖�？�;張如如;;基于Halcon的指針式儀表的讀數(shù)[J];現(xiàn)代電子技術(shù);2016年17期

3 宋偉;張文杰;張家齊;王玉平;周慶;石為人;;基于指針區(qū)域特征的儀表讀數(shù)識別算法[J];儀器儀表學(xué)報;2014年S2期

4 岳曉峰;張嬌;;基于SIFT算法和改進(jìn)最小二乘法的汽車儀表指針的識別[J];機(jī)械工程師;2014年12期

5 徐洋;張清蓉;;基于圖像處理的汽車指針儀表檢測研究[J];計算機(jī)應(yīng)用與軟件;2014年08期

6 許松南;;基于STM32和CAN總線的雙通道正弦信號發(fā)生器設(shè)計[J];計算機(jī)測量與控制;2014年02期

7 李悠;;視覺識別背景下的指針式儀表圖像預(yù)處理技術(shù)研究[J];電測與儀表;2013年S1期

8 張冀;王俊宏;尉遲明;丁明躍;侯文廣;;基于計算機(jī)視覺的汽車儀表指針檢測方法[J];計算機(jī)工程與科學(xué);2013年03期

9 冀辰宇;闞一凡;焦圣喜;;基于顏色提取方法的儀表彩色指針識別[J];東北電力大學(xué)學(xué)報;2012年03期

10 劉松濤;殷福亮;;基于圖割的圖像分割方法及其新進(jìn)展[J];自動化學(xué)報;2012年06期

相關(guān)碩士學(xué)位論文 前3條

1 呂姝慧;基于機(jī)器視覺的高精度指針式儀表自動檢定系統(tǒng)研究[D];哈爾濱工業(yè)大學(xué);2013年

2 孟祥雪;基于機(jī)器視覺的汽車儀表讀數(shù)檢測技術(shù)研究[D];哈爾濱工業(yè)大學(xué);2012年

3 葛婷;幾種數(shù)字圖像濾波算法[D];南京信息工程大學(xué);2006年

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