本文選題：鐵路接觸網(wǎng) + DSP�。� 參考：《遼寧科技大學(xué)》2016年碩士論文

【摘要】：近年來,高速電氣化鐵路不斷發(fā)展,其安全問題也備受關(guān)注。接觸網(wǎng)是電氣化鐵路牽引供電系統(tǒng)的重要組成部分,一旦發(fā)生故障,將會(huì)直接影響牽引供電系統(tǒng)的正常運(yùn)行,甚至還會(huì)中斷電氣化鐵路的行車功能。由于接觸網(wǎng)的露天布置,受環(huán)境影響大,運(yùn)行中受到各種惡劣天氣和外侵異物的影響,調(diào)查發(fā)現(xiàn),接觸網(wǎng)經(jīng)常會(huì)懸掛有塑料袋、風(fēng)箏、氣球等異物,主要懸掛在承力索、吊弦、接觸線、附加導(dǎo)線上,接觸網(wǎng)懸掛異物對(duì)運(yùn)輸?shù)挠绊懖蝗莺鲆?輕則造成動(dòng)車組降弓或停車,重則造成供電設(shè)備故障或弓網(wǎng)故障,使動(dòng)車組大量晚點(diǎn),造成嚴(yán)重的社會(huì)影響。所以,對(duì)接觸網(wǎng)異物檢測(cè)系統(tǒng)的研究也是非常必要的。隨著計(jì)算機(jī)技術(shù)的發(fā)展,數(shù)字圖像處理技術(shù)也被應(yīng)用在鐵路檢測(cè)系統(tǒng)中。由于鐵路系統(tǒng)的復(fù)雜性,其對(duì)圖像采集和識(shí)別的技術(shù)的要求也不斷提高。目前大多數(shù)接觸網(wǎng)檢測(cè)系統(tǒng)都是通過攝像頭來檢測(cè),其具有不定性,且攝像頭所拍攝的畫面受外界影響很大,本文提出一種可以應(yīng)用在接觸網(wǎng)異物檢測(cè)系統(tǒng)中的圖像采集和識(shí)別的硬件系統(tǒng)。接觸網(wǎng)異物檢測(cè)系統(tǒng)的關(guān)鍵就是圖像的采集和處理,要求具有較高的實(shí)時(shí)性和可靠性。本文采用了DSP+FPGA的硬件結(jié)構(gòu),DSP和FPGA的結(jié)合能夠充分發(fā)揮DSP芯片的處理速度和運(yùn)算能力以及FPGA可重復(fù)配置的靈活性以及實(shí)時(shí)性等優(yōu)點(diǎn)。大大的提高了圖像處理的速度和準(zhǔn)確性。在硬件上,本文選擇了TI的8核Keystone架構(gòu)的TMS320C6678芯片作為核心的DSP處理器,Altera Cyclone IV系列的EP4CE15作為FPGA協(xié)處理器,設(shè)計(jì)了一套圖像采集和識(shí)別系統(tǒng)。該系統(tǒng)的設(shè)計(jì)主要包括圖像采集部分的設(shè)計(jì)、圖像處理部分的設(shè)計(jì)以及一些外圍電路的設(shè)計(jì)。在算法上,本文完成了圖像預(yù)處理的濾波算法以及圖像的銳化方法,對(duì)比了幾種常用的濾波算法,設(shè)計(jì)了基于非局部濾波的時(shí)空聯(lián)合濾波方法、針對(duì)拉普拉斯算法設(shè)計(jì)了拉普拉斯銳化濾波器,并進(jìn)行了仿真。最后,針對(duì)Sobel算子邊緣檢測(cè),提出了一種改進(jìn)的方法,并對(duì)其效果進(jìn)行驗(yàn)證。
[Abstract]:In recent years, high-speed electrified railway has been developing, and its safety has been concerned. Catenary is an important part of the traction power supply system of electrified railway. Once the fault occurs, it will directly affect the normal operation of the traction power supply system and even interrupt the running function of the electrified railway. Because of the open-air arrangement of the catenary, which is greatly affected by the environment, and affected by all kinds of bad weather and foreign bodies in operation, the investigation found that the catenary often has foreign objects such as plastic bags, kites, balloons, etc., which are mainly suspended on the load cables and strings. The influence of foreign body suspended by catenary on the contact line and additional wire can not be ignored. The light causes the lower bow or stop of the EMU, and the heavy causes the fault of the power supply equipment or the pantograph, which makes the EMU delayed a lot and causes serious social impact. Therefore, it is necessary to study the foreign body detection system of catenary. With the development of computer technology, digital image processing technology is also used in railway detection system. Due to the complexity of railway system, the requirements of image acquisition and recognition technology are also increasing. At present, most of the catenary detection systems are detected by the camera, which is uncertain, and the images taken by the camera are greatly influenced by the outside world. In this paper, a hardware system for image acquisition and recognition is presented, which can be used in the detection system of foreign bodies in catenary. The key of the foreign body detection system of catenary is the acquisition and processing of image, which requires high real-time and reliability. In this paper, the hardware structure of DSP FPGA and the combination of FPGA and DSP can give full play to the processing speed and computing ability of DSP chip, the flexibility of FPGA reconfigurable configuration and real-time performance. The speed and accuracy of image processing are greatly improved. In terms of hardware, this paper chooses the TMS320C6678 chip of TI's 8-core Keystone architecture as the core DSP processor and the EP4CE15 of Cyclone IV series as FPGA coprocessor, and designs a set of image acquisition and recognition system. The design of the system mainly includes the design of the image acquisition part, the image processing part and the design of some peripheral circuits. In the algorithm, the filtering algorithm of image preprocessing and the sharpening method of image are completed in this paper. Several common filtering algorithms are compared, and a spatio-temporal joint filtering method based on non-local filtering is designed. Laplace sharpening filter is designed for Laplace algorithm and simulated. Finally, an improved method for edge detection of Sobel operator is proposed and its effect is verified.
【學(xué)位授予單位】：遼寧科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：U226.8;TP391.41

【參考文獻(xiàn)】

相關(guān)期刊論文 前1條

1 朱德勝;德國(guó)接觸網(wǎng)動(dòng)態(tài)檢測(cè)技術(shù)[J];電氣化鐵道;2004年03期

，

本文編號(hào)：1810009