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  本文選題：接觸網(wǎng)吊弦　切入點(diǎn)：受電弓滑板　出處：《西南交通大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：近年來,隨著鐵路運(yùn)營量不斷增加以及社會各界對能源利用率的重視,電氣化鐵路憑借其牽引功率大、節(jié)能環(huán)保、能大幅度提高運(yùn)輸能力和速度,并具有技術(shù)、經(jīng)濟(jì)、環(huán)保方面的優(yōu)點(diǎn),成為了各國鐵路優(yōu)先發(fā)展的鐵路牽引動力方式。而我國高速鐵路在近幾年的飛速發(fā)展也使得電氣化鐵路在現(xiàn)已運(yùn)營的所有鐵路中的比例越來越大。在鐵路大幅提速的背景下,交通的安全性日益受到關(guān)注,成為鐵路運(yùn)營的重要議題。而傳統(tǒng)的依靠人力來進(jìn)行的巡檢方式不僅效率低、成本高、檢測周期長,已經(jīng)不能滿足人們的要求,故采用圖片處理技術(shù)的智能巡檢方法越來越受到人們的重視。本文的研究工作是按照6C系統(tǒng)中的受電弓安全巡檢裝置和接觸網(wǎng)安全巡檢裝置的技術(shù)規(guī)范來展開的,本文算法以受電弓巡檢圖片及接觸網(wǎng)巡檢圖片為實(shí)驗數(shù)據(jù),利用圖片處理的技術(shù)手段來實(shí)現(xiàn)對巡檢圖片內(nèi)的敏感設(shè)備進(jìn)行智能識別,通過實(shí)驗測試也論證了本文所提算法的有效性。本文的主要工作及創(chuàng)新內(nèi)容包括以下幾個方面:在接觸網(wǎng)吊弦檢測的過程中,研究采用了基于海森矩陣的Ridge Filter對圖片進(jìn)行過濾,然后對過濾后的圖片進(jìn)行霍夫曼直線檢測,通過設(shè)定閾值的方法對所有直線進(jìn)行篩選,排除不符合條件的直線,則剩下的直線即為代表吊弦的直線,實(shí)現(xiàn)了對接觸網(wǎng)吊弦的準(zhǔn)確識別。在受電弓滑板檢測中,首先研究采用了 HOG特征與廣義霍夫曼變換相結(jié)合的方法來對受電弓滑板進(jìn)行識別;該方法不僅有效去除了車頂復(fù)雜的鋼架結(jié)構(gòu)對識別的干擾,還較為理想的提高了程序的檢測效率。在受電弓滑板檢測中,采用了翻轉(zhuǎn)檢測的方法,該方法在實(shí)驗數(shù)據(jù)較少的情況下有效的增加了訓(xùn)練樣本數(shù)量,使得分類器得到了較為有效的訓(xùn)練,提高了程序檢測的準(zhǔn)確率。最后,對目前收集到的受電弓巡檢圖片及接觸網(wǎng)巡檢圖片進(jìn)行了實(shí)驗測試,本文算法具有較好的適用性,得到了較為理想的識別率,驗證了本文所采用的兩種方法均具有一定的有效性。
[Abstract]:In recent years, with the increasing of railway operation and the importance of energy utilization, electrified railway, with its large traction power, energy saving and environmental protection, can greatly improve the transportation capacity and speed, and has the technology and economy. The advantages of environmental protection, In recent years, the rapid development of high-speed railway in our country also makes the proportion of electrified railway in all the railways in operation more and more. Under the background of the rapid increase of railway speed, The safety of traffic has been paid more and more attention to, which has become an important issue in railway operation. However, the traditional way of patrol and inspection based on manpower is not only low efficiency, high cost, long detection period, but also can not meet the requirements of people. Therefore, more and more attention has been paid to the intelligent inspection method using image processing technology. The research work in this paper is carried out according to the technical specifications of pantograph safety patrol device and catenary safety patrol device in 6C system. In this paper, the pantograph and catenary images are used as experimental data, and the technology of image processing is used to realize the intelligent recognition of sensitive devices in the inspection pictures. The effectiveness of the proposed algorithm is also demonstrated through experimental tests. The main work and innovative contents of this paper include the following aspects: in the detection process of catenary hoisting string, the Ridge Filter based on Hessen matrix is used to filter the images. Then the filtered images are detected by Hoffman line, and all the lines are screened by setting a threshold, and the non-conforming lines are excluded, and the remaining lines are the lines representing the hanging string. In the pantograph slide detection, the HOG feature and the generalized Hoffman transform are used to identify the pantograph slide plate. This method not only effectively removes the interference from the complex steel frame structure of the roof, but also improves the detection efficiency of the program. In the pantograph slide detection, the flipping detection method is adopted. This method can effectively increase the number of training samples in the case of less experimental data, make the classifier get more effective training, and improve the accuracy of program detection. Finally, Experiments are made on the pantograph and catenary images collected at present. The algorithm in this paper has a good applicability and an ideal recognition rate. The validity of the two methods is verified.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：U226.8;U269.6;TP391.41

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本文編號：1639545