本文選題：80m標(biāo)準(zhǔn)裝置 + 寬線紋量具��； 參考：《中國(guó)計(jì)量學(xué)院》2016年碩士論文

【摘要】：寬線紋量具是長(zhǎng)度量值傳遞的重要工具,在我國(guó)每年都有大批量寬線紋量具需要進(jìn)行示值誤差校準(zhǔn)。傳統(tǒng)寬線紋量具的校準(zhǔn)方式主要依靠人眼瞄線實(shí)現(xiàn),需要校準(zhǔn)人員配合完成,不僅工作量大,并且校準(zhǔn)結(jié)果存在主觀因素的影響�；跈C(jī)器視覺(jué)實(shí)現(xiàn)寬線紋量具的自動(dòng)化校準(zhǔn)是寬線紋量具校準(zhǔn)技術(shù)發(fā)展的主要方向,其中寬線紋量具的自動(dòng)瞄準(zhǔn)是該技術(shù)的核心。針對(duì)目前對(duì)大批量寬線紋量具的自動(dòng)瞄準(zhǔn)存在的定位不準(zhǔn)、重復(fù)性較差的問(wèn)題,本文的主要研究工作如下:首先,分析了寬線紋量具的特征及校準(zhǔn)要求,研究探討了寬線紋量具自動(dòng)化校準(zhǔn)的關(guān)鍵技術(shù)及要求,詳細(xì)分析了數(shù)字圖像處理技術(shù)在寬線紋量具自動(dòng)化校準(zhǔn)技術(shù)中的應(yīng)用及其影響。其次,基于80m大長(zhǎng)度標(biāo)準(zhǔn)裝置,采用圖像無(wú)線傳輸方式,搭建了寬線紋量具圖像采集系統(tǒng),并利用C#開(kāi)發(fā)了軟件操作系統(tǒng),實(shí)現(xiàn)了無(wú)拖鏈、供電一體化的寬線紋量具的自動(dòng)化校準(zhǔn)。再者,分析探討了寬線紋量具的圖像噪聲及線紋邊緣特征,分別采用了差分式鄰域極值中心線提取算法、基于最小二乘擬合取交點(diǎn)的中心線提取算法及基于Sobel算子鄰域極值的中心線提取算法,以滿足對(duì)不同類型的寬線紋量具線紋中心線提取。分析了像素標(biāo)定系數(shù)與行程的關(guān)系,在同樣的視場(chǎng)中,較大行程下計(jì)算得到的像素標(biāo)定系數(shù)可靠性更高。針對(duì)三等標(biāo)準(zhǔn)金屬線紋尺、標(biāo)準(zhǔn)鋼卷尺、因瓦條碼水準(zhǔn)尺等做了校準(zhǔn)實(shí)驗(yàn),實(shí)驗(yàn)結(jié)果表明整套系統(tǒng)能夠滿足對(duì)寬線紋量具的自動(dòng)化校準(zhǔn)。最后,對(duì)系統(tǒng)的標(biāo)準(zhǔn)不確定度進(jìn)行了評(píng)定。其中三等標(biāo)準(zhǔn)金屬線紋尺的標(biāo)準(zhǔn)不確定度為u_c=0.86μm+1.5×10~(-6)L,擴(kuò)展不確定度U=1.72μm+3.0×10~(-6)L,標(biāo)準(zhǔn)鋼卷尺校準(zhǔn)標(biāo)準(zhǔn)不確定度u_c=1.32μm+1.2×10~(-6)L,擴(kuò)展不確定度U=2.64μm+2.3×10~(-6)L。
[Abstract]:The wide line grain measuring tool is an important tool for the transmission of the long measure value. Every year a large number of wide line grain gauges need to be calibrated for the indication value in our country. The calibration of traditional wide line stripe gauges is mainly realized by the human line of sight, which needs the cooperation of the calibration staff. It not only has a large workload, but also has the influence of subjective factors on the calibration results. The automatic calibration of wide line gauges based on machine vision is the main direction of the development of wide line gauges calibration technology, in which the automatic aiming of wide line grain gauges is the core of this technology. In view of the problems of inaccurate positioning and poor repeatability of automatic aiming for large quantities of wide line grain gauges, the main research work of this paper is as follows: firstly, the characteristics and calibration requirements of wide line grain gauges are analyzed. The key technologies and requirements of automatic calibration of wide line stripe gauges are discussed. The application and influence of digital image processing technology in automatic calibration technology of wide line grain gauges are analyzed in detail. Secondly, based on 80m large length standard device, the image acquisition system of wide line grain measuring device is built by using wireless image transmission mode, and the software operating system is developed by using C #. Automatic calibration of wide line gauges integrated with power supply. Furthermore, the image noise and the edge features of the wide line grain measuring tools are analyzed and discussed, and the differential neighborhood extremum centerline extraction algorithms are used respectively. The centerline extraction algorithm based on least squares fitting intersection point and the centerline extraction algorithm based on neighborhood extremum of Sobel operator can meet the requirements of different types of wide line measuring tools. The relationship between pixel calibration coefficient and stroke is analyzed. In the same field of view, the reliability of pixel calibration coefficient calculated with larger stroke is higher. The calibration experiments are carried out for the third class standard wire gauge, standard steel tape gauge and bar code leveler. The experimental results show that the whole system can meet the automatic calibration of wide line stripe gauges. Finally, the standard uncertainty of the system is evaluated. The standard uncertainty of the third class standard metal wire stripe is u_c=0.86 渭 m 1.5 脳 10 ~ (10) ~ (-6) L, the extended uncertainty is 1.72 渭 m, the calibration standard uncertainty is 1. 2 脳 10 ~ (-6) L, the standard uncertainty is 1. 2 脳 10 ~ (-6) L, and the extended uncertainty is U2.64 渭 m ~ (2.3 脳 10 ~ (-6) L ~ (-1).
【學(xué)位授予單位】：中國(guó)計(jì)量學(xué)院
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：TH711;TP391.41

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 陳汗青;萬(wàn)艷玲;王國(guó)剛;;數(shù)字圖像處理技術(shù)研究進(jìn)展[J];工業(yè)控制計(jì)算機(jī);2013年01期

2 錢崢;;基于計(jì)算機(jī)視頻的銦鋼水準(zhǔn)標(biāo)尺測(cè)量系統(tǒng)的研制[J];計(jì)量與測(cè)試技術(shù);2012年03期

3 謝勰;王輝;張雪鋒;;圖像閾值分割技術(shù)中的部分和算法綜述[J];西安郵電學(xué)院學(xué)報(bào);2011年03期

4 張巧芬;高健;;機(jī)器視覺(jué)中照明技術(shù)的研究進(jìn)展[J];照明工程學(xué)報(bào);2011年02期

5 王旭東;葉玉堂;;CMOS與CCD圖像傳感器的比較研究和發(fā)展趨勢(shì)[J];電子設(shè)計(jì)工程;2010年11期

6 張勇;潘嘉聲;黃穌;衛(wèi)作之;陳偉琪;;多功能線紋尺自動(dòng)測(cè)量裝置研制[J];中國(guó)測(cè)試;2010年05期

7 陳炳權(quán);劉宏立;孟凡斌;;數(shù)字圖像處理技術(shù)的現(xiàn)狀及其發(fā)展方向[J];吉首大學(xué)學(xué)報(bào)(自然科學(xué)版);2009年01期

8 袁春蘭;熊宗龍;周雪花;彭小輝;;基于Sobel算子的圖像邊緣檢測(cè)研究[J];激光與紅外;2009年01期

9 張輝;張道勇;何最紅;;灰度等級(jí)處理中的OSTU動(dòng)態(tài)閾值法研究[J];傳感器世界;2008年07期

10 張旭升,周桃庚,沙定國(guó);數(shù)字圖像噪聲估計(jì)的方法及數(shù)學(xué)模型[J];光學(xué)技術(shù);2005年05期

，

本文編號(hào)：1990036