【摘要】：鍋爐蒸汽管道的蠕變和宏觀位移是鍋爐安全運(yùn)行需要監(jiān)測的重要方面,上述位移的實(shí)時(shí)監(jiān)測可以反映鍋爐蒸汽管道內(nèi)部的應(yīng)力應(yīng)變情況。為了能夠?qū)崟r(shí)在線準(zhǔn)確獲取管道宏觀位移,本文從視覺測量技術(shù)研究出發(fā),利用支吊架與管道的結(jié)構(gòu)關(guān)系,提出一種基于視覺的鍋爐關(guān)鍵管道的宏觀位移以及蠕變情況的測量方法,并自主設(shè)計(jì)一套應(yīng)用此方法的在線檢測系統(tǒng)。提出鍋爐蒸汽管道蠕變情況及宏觀位移檢測方法,該方法通過在彈簧支吊架下節(jié)點(diǎn)焊兩個(gè)標(biāo)志圓,以標(biāo)志圓圓心為標(biāo)志點(diǎn),根據(jù)標(biāo)志圓圓心的三維空間坐標(biāo),擬合彈簧支吊架下節(jié)所在直線的直線方程,聯(lián)立蒸汽管道的圓柱體曲線方程,得到二者的交點(diǎn),根據(jù)該交點(diǎn)坐標(biāo)的變化量即可得出該點(diǎn)宏觀位移,在此基礎(chǔ)上,進(jìn)一步結(jié)合多個(gè)支吊架,將支吊架與管道的交點(diǎn)轉(zhuǎn)換到同一個(gè)坐標(biāo)系中,則可根據(jù)彼此交點(diǎn)距離的變化量,得到在兩個(gè)或多個(gè)支吊架之間管道的蠕變情況。為了實(shí)時(shí)準(zhǔn)確獲得標(biāo)志圓圓心的三維坐標(biāo),采用了標(biāo)志圓視覺檢測算法,即先對圖像進(jìn)行灰度化及灰度直方圖分析,接著進(jìn)行圖像去噪處理,之后對圖像進(jìn)行二值化,并通過邊緣特征提取標(biāo)志圓的輪廓,用Hough變換檢測標(biāo)志圓,獲得標(biāo)志圓圓心的像素坐標(biāo),最后根據(jù)針孔成像模型得到標(biāo)志圓圓心的三維坐標(biāo)。實(shí)驗(yàn)驗(yàn)證了該方法的可行性。針對強(qiáng)光照、標(biāo)志圓表面積灰等復(fù)雜環(huán)境,常規(guī)方法檢測誤差大甚至無法檢測的現(xiàn)象,提出基于HSV模型的圖像處理算法,該方法通過對HSV中H分量、S分量和V分量進(jìn)行的一系列數(shù)學(xué)組合運(yùn)算和色調(diào)、飽和度及亮度配比系數(shù)的調(diào)整,可有效解決強(qiáng)光照,表面積灰等情況,仿真實(shí)驗(yàn)結(jié)果證明了該方法的有效性。設(shè)計(jì)了一套鍋爐管道宏觀位移在線檢測系統(tǒng),運(yùn)行于珠海電廠1號機(jī)組。軟件系統(tǒng)采用VC在VS2013開發(fā)環(huán)境下進(jìn)行開發(fā),試驗(yàn)結(jié)果表明該系統(tǒng)能夠全天候?qū)﹀仩t管道宏觀位移進(jìn)行實(shí)時(shí)在線檢測,精度高,該方法的成功應(yīng)用為鍋爐蒸汽管道失效概率和剩余壽命計(jì)算模型的建立奠定了基礎(chǔ)。
[Abstract]:The creep and macroscopic displacement of boiler steam pipeline are important aspects of boiler safety operation. The real-time monitoring of the above displacement can reflect the stress and strain situation in boiler steam pipeline. In order to accurately obtain the macroscopic displacement of pipeline in real time and online, this paper, based on the research of visual measurement technology, makes use of the structural relationship between the support hanger and the pipeline. This paper presents a vision-based measurement method for macroscopic displacement and creep of boiler critical pipes, and designs an on-line detection system using this method. The creep condition and macroscopic displacement detection method of boiler steam pipeline are put forward. By spot welding two mark circles under the spring support and hanger, the method takes the mark circle center as the mark point, and according to the three dimensional space coordinate of the mark circle center, By fitting the straight line equation of the lower node of the spring support hanger and the cylinder curve equation of the steam pipeline, the intersection point of the two points can be obtained. According to the change of the coordinate of the intersection point, the macroscopic displacement of the point can be obtained. The creep of the pipe between two or more supports and hangers can be obtained according to the variation of the distance between the points of intersection between the two or more supports and hangers by converting the intersection points of the support and hanger to the same coordinate system. In order to get the 3D coordinate of the mark circle center in real time, this paper adopts the sign circle vision detection algorithm, that is, the image is first grayscale and grayscale histogram analysis, then the image is de-noised, and then the image is binarized. The contour of mark circle is extracted by edge feature, and the pixel coordinate of mark circle is obtained by Hough transform. Finally, the 3D coordinate of mark circle center is obtained according to the pinhole imaging model. The feasibility of the method is verified by experiments. A new image processing algorithm based on HSV model is proposed in view of the complex environment such as strong illumination, marked circle surface area ash and so on, in which the detection error is large or even undetectable by conventional methods. This method can effectively solve the problems of strong illumination, surface area ash and so on by a series of mathematical combination operations and adjustment of hue, saturation and luminance ratio coefficient of H component S component and V component in HSV. The simulation results show that the method is effective. A set of boiler pipeline macro displacement measurement system is designed, which runs in No. 1 unit of Zhuhai Power Plant. The software system is developed by using VC in the VS2013 development environment. The experimental results show that the system can detect the macroscopic displacement of boiler pipeline in real time and online all the time, and the precision is high. The successful application of this method has laid a foundation for the establishment of failure probability and residual life model of boiler steam pipeline.
【學(xué)位授予單位】：長沙理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：TP391.41;TK228

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 王偉;鐘萬里;林介東;許傳龍;丁輝;;電站鍋爐高溫?zé)煔鈱Ρ诿婕t外測溫的影響[J];儀表技術(shù)與傳感器;2016年01期

2 李龍光;蘇靜;韓海倫;喬海強(qiáng);錢帆;;不同光照條件下二值化技術(shù)研究及應(yīng)用[J];電子世界;2015年20期

3 蔡磊;王贊超;岳桂金;;復(fù)雜背景下的圖像去噪處理方法[J];科技與企業(yè);2015年13期

4 劉玉;;數(shù)字圖像處理技術(shù)[J];通訊世界;2015年05期

5 高如新;王俊孟;;雙目立體視覺求取三維坐標(biāo)的方法研究[J];計(jì)算機(jī)仿真;2014年10期

6 張燕紅;韓慶龍;劉瑜;李祁;;基于邊緣檢測的分割方法的研究及Matlab實(shí)現(xiàn)[J];福建電腦;2014年09期

7 王萬國;王濱海;張晶晶;李麗;;基于直方圖規(guī)定化的圖像去霧算法[J];計(jì)算機(jī)技術(shù)與發(fā)展;2014年09期

8 宋曉宇;袁帥;郭寒冰;劉繼飛;;基于自適應(yīng)閾值區(qū)間的廣義Hough變換圖形識別算法[J];儀器儀表學(xué)報(bào);2014年05期

9 張藝雪;;基于直方圖的X線醫(yī)學(xué)圖像增強(qiáng)及Matlab實(shí)現(xiàn)[J];通化師范學(xué)院學(xué)報(bào);2014年04期

10 葉峰;陳燦杰;賴乙宗;陳劍東;;基于有序Hough變換的快速圓檢測算法[J];光學(xué)精密工程;2014年04期

相關(guān)博士學(xué)位論文 前2條

1 戴金波;基于視覺信息的圖像特征提取算法研究[D];吉林大學(xué);2013年

2 孫雙花;視覺測量關(guān)鍵技術(shù)及在自動檢測中的應(yīng)用[D];天津大學(xué);2007年

相關(guān)碩士學(xué)位論文 前10條

1 孫付超;基于OpenCV的圖像預(yù)處理在儀表定位中的應(yīng)用[D];山東大學(xué);2015年

2 吳超偉;基于遠(yuǎn)程監(jiān)測的電站鍋爐厚壁承壓元件壽命管理[D];浙江大學(xué);2014年

3 武云龍;鍋爐集箱熱應(yīng)力有限元分析及裂紋擴(kuò)展速率的研究[D];天津大學(xué);2012年

4 王娟;SMT模板的自動影像檢測系統(tǒng)的研究[D];華南理工大學(xué);2010年

5 楊全銀;基于Hough變換的圖像形狀特征檢測[D];山東大學(xué);2009年

6 孫小勇;結(jié)構(gòu)腐蝕損傷的波激勵(lì)—散斑檢測技術(shù)研究[D];南京航空航天大學(xué);2008年

7 萬敏;電子散斑干涉檢測技術(shù)的研究[D];南京航空航天大學(xué);2008年

8 熊倫;激光散斑相關(guān)計(jì)量系統(tǒng)的研究[D];華中師范大學(xué);2007年

9 王開龍;電廠鍋爐部件壽命損耗的研究及應(yīng)用[D];華北電力大學(xué)（北京）;2006年

10 陳大慶;數(shù)字散斑相關(guān)技術(shù)及在結(jié)構(gòu)監(jiān)測中的應(yīng)用[D];蘇州大學(xué);2005年

，

本文編號：2236389