【摘要】：伴隨著中國經濟和科技實力的全面快速發(fā)展,國民經濟和人民出行對交通運輸?shù)男枨笕找嬖鲩L,軌道交通作為交通運輸技術的重要一個分支,具備速度快、運量大、安全舒適、節(jié)能減排、效率高等無法媲美的優(yōu)點。近十年來,軌道交通在國內外的發(fā)展突飛猛進,包括高速鐵路、城際鐵路、城市地鐵。軌道交通建設的里程數(shù)增加速度也十分迅猛,運輸量也快速上升。軌道交通發(fā)展在為國內經濟發(fā)展、人們出行便利服務的同時,軌道交通的運輸特點也發(fā)生了變化:運輸任務加大、行車密度提升、運行速度提高,也正是因為這些變化,輪軌之間的相互作用也隨之增大,加速了車輪輪對踏面的磨損,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的使用壽命,是線路大、中、小維修工作的重要部分,相關軌道公司的工務部門需要定期對車輪幾何參數(shù)進行測量,掌握車輪幾何參數(shù)變化情況,實現(xiàn)對其合理預測,進而相應地制定合理并具有針對性的維護計劃。所以,對車輪幾何參數(shù)實現(xiàn)高效準確的在線動態(tài)跟蹤檢測是一項十分必要的任務。本學位論文主要研究工作和創(chuàng)新成果,概括起來主要包括以下幾個方面:1:介紹了車輪幾何參數(shù)檢測的主要內容,提出一種在線式動態(tài)跟蹤檢測方法,介紹測量的技術原理,基于激光三角法和圖像處理技術設計的傳感器,實現(xiàn)了對車輪輪對踏面輪廓非接觸式高精度地檢測,結合無線射頻識別技術,提出了基于該技術的車輪幾何參數(shù)動態(tài)在線跟蹤檢測方案,闡述了各個車輪幾何參數(shù)的計算算法。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源和分類,利用空域濾波和頻域濾波技術對車輪輪廓圖像進行處理降噪,對處理后的圖片進行比較分析,選擇合適的降噪處理算法。車輪踏面輪廓檢測的重要一個環(huán)節(jié)是對激光投射在輪對踏面形成的光帶中心點提取,本文在對各種傳統(tǒng)方法進行分析研究后,采用灰度重心法提取激光光帶中心點。在此基礎上,研究分析二維圖像坐標系、傳感器坐標系和世界坐標系三者之間的關系,得出了激光輪廓傳感器的測量坐標系,根據輪廓上各點在測量坐標系坐標換算得到激光發(fā)射點的距離。3:在圖像處理技術和激光輪廓傳感器的基礎上實現(xiàn)車輪幾何參數(shù)在線動態(tài)跟蹤檢測后,針對列車在線動態(tài)行駛,鋼軌豎向振動位移情況,分析了其對車輪幾何參數(shù)中車輪滾動圓直徑檢測可能帶來的誤差進行了分析,建立有限元模型,分析軌道振動,結合車輪滾動圓動態(tài)在線測量原理,在ANSYS下進行模擬仿真計算,得出鋼軌豎向振動對其測量可能帶來的影響。4:根據提出的車輪幾何參數(shù)在線動態(tài)跟蹤檢測方法,現(xiàn)場布置傳感器,進行現(xiàn)象實驗,并得出結果。
[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.
【學位授予單位】：西南交通大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：U270.7;TP391.41

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