本文選題：數(shù)據(jù)挖掘 + 城軌列車(chē)��； 參考：《北京交通大學(xué)》2017年碩士論文

【摘要】：近年來(lái)隨著我國(guó)城市軌道交通行業(yè)的快速發(fā)展,列車(chē)的運(yùn)行安全問(wèn)題受到了行業(yè)的廣泛關(guān)注。為了保證列車(chē)的運(yùn)行安全,在列車(chē)運(yùn)行中發(fā)現(xiàn)并解決故障,本文以城市軌道行業(yè)為背景,使用基于在途列車(chē)狀態(tài)的數(shù)據(jù)分析與挖掘技術(shù)解決列車(chē)運(yùn)行中的安全問(wèn)題。在現(xiàn)有的車(chē)輛維保生產(chǎn)管理系統(tǒng)中,使用該系統(tǒng)的列車(chē)在途運(yùn)行數(shù)據(jù),運(yùn)用數(shù)據(jù)挖掘技術(shù)進(jìn)一步開(kāi)發(fā)子系統(tǒng)-安全預(yù)測(cè)系統(tǒng)。系統(tǒng)主要包括故障統(tǒng)計(jì)、故障關(guān)聯(lián)分析、故障識(shí)別和故障預(yù)測(cè)四個(gè)功能模塊,本文的主要工作包括:(1)按照系統(tǒng)的設(shè)置和用戶(hù)的要求,使用原始數(shù)據(jù)表在數(shù)據(jù)庫(kù)中建立相應(yīng)的故障對(duì)應(yīng)關(guān)系表,根據(jù)不同的條件,在對(duì)應(yīng)表中對(duì)故障數(shù)據(jù)進(jìn)行統(tǒng)計(jì),生成故障統(tǒng)計(jì)圖。(2)使用Hadoop對(duì)列車(chē)運(yùn)行時(shí)產(chǎn)生的故障數(shù)據(jù)進(jìn)行數(shù)據(jù)分析和挖掘,得出故障的屬性和故障之間的關(guān)聯(lián)規(guī)則,生成關(guān)聯(lián)規(guī)則數(shù)據(jù)表。(3)使用關(guān)聯(lián)規(guī)則進(jìn)行故障識(shí)別,在故障表中找到與異常數(shù)據(jù)有關(guān)的故障,在關(guān)聯(lián)規(guī)則數(shù)據(jù)庫(kù)中查找異常數(shù)據(jù)的屬性與故障的關(guān)聯(lián)規(guī)則,對(duì)異常數(shù)據(jù)進(jìn)行判斷,在確認(rèn)故障隱患后,生成故障隱患單。(4)綜合相關(guān)數(shù)據(jù),運(yùn)用回歸分析知識(shí)對(duì)故障的發(fā)展趨勢(shì)進(jìn)行預(yù)測(cè),構(gòu)造故障屬性之間的回歸方程,建立回歸模型,通過(guò)回歸模型對(duì)故障隱患進(jìn)行預(yù)測(cè)。安全預(yù)測(cè)系統(tǒng)將數(shù)據(jù)挖掘技術(shù)引入車(chē)輛的維保管理系統(tǒng)中,實(shí)現(xiàn)了對(duì)列車(chē)運(yùn)行狀態(tài)的實(shí)時(shí)監(jiān)測(cè),經(jīng)過(guò)系統(tǒng)對(duì)異常數(shù)據(jù)的識(shí)別和預(yù)測(cè),及時(shí)通知用戶(hù)對(duì)故障隱患進(jìn)行處理,保證了列車(chē)的運(yùn)行安全。系統(tǒng)測(cè)試結(jié)果表明安全預(yù)測(cè)系統(tǒng)的功能要求已經(jīng)基本實(shí)現(xiàn),車(chē)輛維保生產(chǎn)管理系統(tǒng)已經(jīng)實(shí)現(xiàn)部分功能,相關(guān)版本已在廣州地鐵的具體項(xiàng)目中進(jìn)行測(cè)試驗(yàn)收,軟件相關(guān)后續(xù)開(kāi)發(fā)工作也在進(jìn)行中。
[Abstract]:In recent years, with the rapid development of urban rail transit industry in China, the safety of train operation has been widely concerned by the industry. In order to ensure the safety of train operation and to find and solve the trouble in train operation, this paper takes the urban rail industry as the background, and uses the data analysis and mining technology based on the state of the train on the way to solve the safety problem in the train operation. In the existing vehicle maintenance and maintenance production management system, the data of train running in the system is used to further develop the subsystem, the safety prediction system, by using the data mining technology. The system mainly includes four function modules: fault statistics, fault correlation analysis, fault identification and fault prediction. Using the original data table to establish the corresponding fault correspondence table in the database, according to the different conditions, the fault data in the corresponding table is counted, Using Hadoop to analyze and mine the fault data generated by train operation, to get the association rules between fault attributes and faults, and to generate association rules data table. 3) to identify faults using association rules. Find the fault related to the abnormal data in the fault table, look up the attribute of the abnormal data and the association rule of the fault in the association rule database, judge the abnormal data, after confirming the hidden trouble of the fault, (4) synthesizing relevant data, using regression analysis knowledge to predict the trend of fault development, constructing regression equation between fault attributes, establishing regression model and predicting hidden trouble through regression model. The safety prediction system introduces data mining technology into the maintenance management system of the vehicle, realizes the real-time monitoring of the train running state. After the system recognizes and predicts the abnormal data, the users are informed in time to deal with the hidden trouble. The running safety of the train is ensured. The system test results show that the functional requirements of the safety prediction system have been basically realized, the vehicle maintenance and production management system has realized some functions, and the related versions have been tested and accepted in the specific projects of Guangzhou Metro. Software related follow-up development work is also under way.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TP311.13;TP311.52

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