【摘要】：伴隨著中國(guó)經(jīng)濟(jì)和科技實(shí)力的全面快速發(fā)展,國(guó)民經(jīng)濟(jì)和人民出行對(duì)交通運(yùn)輸?shù)男枨笕找嬖鲩L(zhǎng),軌道交通作為交通運(yùn)輸技術(shù)的重要一個(gè)分支,具備速度快、運(yùn)量大、安全舒適、節(jié)能減排、效率高等無(wú)法媲美的優(yōu)點(diǎn)。近十年來(lái),軌道交通在國(guó)內(nèi)外的發(fā)展突飛猛進(jìn),包括高速鐵路、城際鐵路、城市地鐵。軌道交通建設(shè)的里程數(shù)增加速度也十分迅猛,運(yùn)輸量也快速上升。軌道交通發(fā)展在為國(guó)內(nèi)經(jīng)濟(jì)發(fā)展、人們出行便利服務(wù)的同時(shí),軌道交通的運(yùn)輸特點(diǎn)也發(fā)生了變化:運(yùn)輸任務(wù)加大、行車密度提升、運(yùn)行速度提高,也正是因?yàn)檫@些變化,輪軌之間的相互作用也隨之增大,加速了車輪輪對(duì)踏面的磨損,車輪幾何參數(shù)的變化也隨之加速。車輪幾何參數(shù)的變化程度很大程度上決定了輪對(duì)的使用壽命,是線路大、中、小維修工作的重要部分,相關(guān)軌道公司的工務(wù)部門需要定期對(duì)車輪幾何參數(shù)進(jìn)行測(cè)量,掌握車輪幾何參數(shù)變化情況,實(shí)現(xiàn)對(duì)其合理預(yù)測(cè),進(jìn)而相應(yīng)地制定合理并具有針對(duì)性的維護(hù)計(jì)劃。所以,對(duì)車輪幾何參數(shù)實(shí)現(xiàn)高效準(zhǔn)確的在線動(dòng)態(tài)跟蹤檢測(cè)是一項(xiàng)十分必要的任務(wù)。本學(xué)位論文主要研究工作和創(chuàng)新成果,概括起來(lái)主要包括以下幾個(gè)方面:1:介紹了車輪幾何參數(shù)檢測(cè)的主要內(nèi)容,提出一種在線式動(dòng)態(tài)跟蹤檢測(cè)方法,介紹測(cè)量的技術(shù)原理,基于激光三角法和圖像處理技術(shù)設(shè)計(jì)的傳感器,實(shí)現(xiàn)了對(duì)車輪輪對(duì)踏面輪廓非接觸式高精度地檢測(cè),結(jié)合無(wú)線射頻識(shí)別技術(shù),提出了基于該技術(shù)的車輪幾何參數(shù)動(dòng)態(tài)在線跟蹤檢測(cè)方案,闡述了各個(gè)車輪幾何參數(shù)的計(jì)算算法。2:車輪踏面輪廓圖像處理,分析了車輪輪廓激光光帶圖像噪聲來(lái)源和分類,利用空域?yàn)V波和頻域?yàn)V波技術(shù)對(duì)車輪輪廓圖像進(jìn)行處理降噪,對(duì)處理后的圖片進(jìn)行比較分析,選擇合適的降噪處理算法。車輪踏面輪廓檢測(cè)的重要一個(gè)環(huán)節(jié)是對(duì)激光投射在輪對(duì)踏面形成的光帶中心點(diǎn)提取,本文在對(duì)各種傳統(tǒng)方法進(jìn)行分析研究后,采用灰度重心法提取激光光帶中心點(diǎn)。在此基礎(chǔ)上,研究分析二維圖像坐標(biāo)系、傳感器坐標(biāo)系和世界坐標(biāo)系三者之間的關(guān)系,得出了激光輪廓傳感器的測(cè)量坐標(biāo)系,根據(jù)輪廓上各點(diǎn)在測(cè)量坐標(biāo)系坐標(biāo)換算得到激光發(fā)射點(diǎn)的距離。3:在圖像處理技術(shù)和激光輪廓傳感器的基礎(chǔ)上實(shí)現(xiàn)車輪幾何參數(shù)在線動(dòng)態(tài)跟蹤檢測(cè)后,針對(duì)列車在線動(dòng)態(tài)行駛,鋼軌豎向振動(dòng)位移情況,分析了其對(duì)車輪幾何參數(shù)中車輪滾動(dòng)圓直徑檢測(cè)可能帶來(lái)的誤差進(jìn)行了分析,建立有限元模型,分析軌道振動(dòng),結(jié)合車輪滾動(dòng)圓動(dòng)態(tài)在線測(cè)量原理,在ANSYS下進(jìn)行模擬仿真計(jì)算,得出鋼軌豎向振動(dòng)對(duì)其測(cè)量可能帶來(lái)的影響。4:根據(jù)提出的車輪幾何參數(shù)在線動(dòng)態(tài)跟蹤檢測(cè)方法,現(xiàn)場(chǎng)布置傳感器,進(jìn)行現(xiàn)象實(shí)驗(yàn),并得出結(jié)果。
[Abstract]:With the rapid development of China's economy and science and technology, the demand of national economy and people for transportation is increasing day by day. As an important branch of transportation technology, rail transit has the advantages of fast speed, large capacity, safety and comfort. Energy saving and emission reduction, high efficiency and other unparalleled advantages. In the past ten years, rail transit has developed rapidly at home and abroad, including high speed railway, intercity railway and city subway. The mileage of rail transit construction is also increasing rapidly, and the volume of transportation is also rising rapidly. With the development of rail transit for the development of domestic economy and the convenient service for people to travel, the transport characteristics of rail transit have also changed: the transportation task has been increased, the traffic density has been increased, and the speed of operation has been increased, which is precisely because of these changes. The interaction between wheel and rail increases, which accelerates the wear of wheel tread and the change of wheel geometric parameters. The variation of wheel geometric parameters determines the service life of wheelset to a great extent, and is an important part of the maintenance work of large, medium and small lines. The public works departments of relevant rail companies need to measure the geometric parameters of wheels regularly. According to the change of wheel geometry parameters, the reasonable forecast is realized, and the reasonable and targeted maintenance plan is worked out accordingly. Therefore, it is a very necessary task to realize efficient and accurate on-line dynamic tracking detection of wheel geometry parameters. In this dissertation, the main research work and innovative achievements are summarized as follows: the main contents of wheel geometric parameter detection are introduced, a on-line dynamic tracking detection method is proposed, and the technical principle of measurement is introduced. Based on the sensor designed by laser triangulation and image processing technology, the non-contact high-precision detection of wheel tread profile is realized, and the wireless radio frequency identification (RFID) technology is combined. This paper presents a dynamic on-line tracking detection scheme for wheel geometric parameters based on this technique. The calculation algorithm of each wheel geometry parameter is described. The image processing of wheel tread profile is described. The noise source and classification of wheel profile laser belt image are analyzed. Spatial filtering and frequency domain filtering are used to process the noise of wheel contour image. The image after processing is compared and analyzed, and the appropriate denoising algorithm is selected. One of the most important steps in wheel tread profile detection is to extract the center of the laser beam which is formed on the wheel tread. After analyzing and studying the traditional methods, the gray gravity method is used to extract the center of the laser beam. On this basis, the relationship among two-dimensional image coordinate system, sensor coordinate system and world coordinate system is analyzed, and the measuring coordinate system of laser contour sensor is obtained. The distance of laser emission point is obtained according to the coordinate conversion of each point on the contour in the measuring coordinate system. On the basis of image processing technology and laser contour sensor, the on-line dynamic tracking detection of wheel geometric parameters is realized, and the train is running dynamically on line. The vertical vibration displacement of rail is analyzed. The error caused by wheel rolling circle diameter detection in wheel geometry parameters is analyzed. The finite element model is established to analyze the track vibration, and the dynamic on-line measurement principle of wheel rolling circle is combined. The influence of vertical vibration of rail on the measurement of rail is obtained by simulation calculation under ANSYS. 4. According to the proposed on-line dynamic tracking detection method for wheel geometry parameters, sensors are arranged on the spot, and the phenomena are tested, and the results are obtained.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：U270.7;TP391.41

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 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(shí)別算法[J];儀器儀表學(xué)報(bào);2014年05期

2 袁勃;張桂香;陳根余;周聰;鄧將;;基于CCD傳感器的砂輪輪廓測(cè)量系統(tǒng)設(shè)計(jì)[J];傳感器與微系統(tǒng);2014年01期

3 曾文靜;張鐵棟;萬(wàn)磊;徐玉如;;基于Hough變換的水下管道檢測(cè)方法[J];儀器儀表學(xué)報(bào);2012年01期

4 夏博光;王衛(wèi)東;王登陽(yáng);;無(wú)線射頻(RFID)技術(shù)在高速檢測(cè)列車精確定位中的應(yīng)用[J];鐵道建筑;2011年12期

5 黃邦奎;劉震;張廣軍;;多傳感器線結(jié)構(gòu)光視覺(jué)測(cè)量系統(tǒng)全局校準(zhǔn)[J];光電子.激光;2011年12期

6 方銳;肖新標(biāo);房建英;金學(xué)松;;軌道結(jié)構(gòu)參數(shù)對(duì)鋼軌和軌枕振動(dòng)特性的影響[J];鐵道學(xué)報(bào);2011年03期

7 向俊;赫丹;曾京;;高速列車作用下不同類型無(wú)砟軌道振動(dòng)響應(yīng)分析[J];機(jī)械工程學(xué)報(bào);2010年16期

8 熊顯名;馬蓓;張文韜;;一種改進(jìn)的去除灰度圖像椒鹽噪聲方法的研究[J];國(guó)外電子測(cè)量技術(shù);2010年05期

9 羅仁;曾京;鄔平波;戴煥云;;高速列車輪軌參數(shù)對(duì)車輪踏面磨耗的影響[J];交通運(yùn)輸工程學(xué)報(bào);2009年06期

10 馮其波;陳士謙;崔建英;李鳳山;張英杰;;輪對(duì)幾何參數(shù)動(dòng)態(tài)測(cè)量系統(tǒng)[J];中國(guó)鐵道科學(xué);2008年05期

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