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面向車輛租賃的遠(yuǎn)程監(jiān)控與決策方法的研究

發(fā)布時間:2018-03-06 10:44

  本文選題:本體 切入點(diǎn):遠(yuǎn)程診斷與決策 出處:《華東理工大學(xué)》2017年碩士論文 論文類型:學(xué)位論文


【摘要】:如何提高租賃公司對汽車的有效管理以及保證車輛的安全運(yùn)行是汽車租賃行業(yè)急需解決的問題。本文提出一種基于Web的云平臺,并對車輛的遠(yuǎn)程監(jiān)控與決策方法等關(guān)鍵技術(shù)進(jìn)行了研究。論文的主要工作如下:(1)提出了基于Web的車輛租賃云服務(wù)平臺,開發(fā)了車輛展示,租金測算,訂單填寫,訂單管理,車型管理,用戶管理,服務(wù)提醒,實(shí)時監(jiān)控,遠(yuǎn)程診斷與決策以及路徑規(guī)劃等功能模塊。為提高Web平臺的穩(wěn)定性與伸縮性,將云計算技術(shù)引入其中。(2)制定了數(shù)據(jù)采集終端與服務(wù)器之間的通訊協(xié)議,設(shè)計了基于ORACLE的數(shù)據(jù)庫系統(tǒng)及遠(yuǎn)程服務(wù)平臺,平臺開發(fā)了一個SOCKET常連接程序接收數(shù)據(jù)采集終端上傳的數(shù)據(jù),解析之后存儲到數(shù)據(jù)庫,最終在界面上展示出來。(3)基于本體,建立了汽車故障診斷本體模型,提出了基于規(guī)則與歷史案例推理的的診斷決策方法,設(shè)計了汽車診斷規(guī)則與診斷歷史案例庫,開發(fā)了具有可視化能力的界面,將故障原因、故障地點(diǎn)、維修建議、最佳維修點(diǎn)等直觀地呈現(xiàn)給用戶。(4)基于混沌蟻群算法對車輛前往維修點(diǎn)的行駛路徑進(jìn)行規(guī)劃,構(gòu)建了距離最短的算法模型,在算法的概率轉(zhuǎn)移中引入混沌擾動防止算法陷入局部最優(yōu),在蟻群選擇下一跳節(jié)點(diǎn)時,通過歐式距離篩選鄰節(jié)點(diǎn),提高了算法搜索效率。以綠途公司車輛租賃為應(yīng)用對象,對系統(tǒng)的功能及可靠性進(jìn)行了測試與驗(yàn)證。結(jié)果表明,系統(tǒng)在性能和可操作性上都有較大優(yōu)勢,具有一定的推廣意義。
[Abstract]:How to improve the efficient management of the car and ensure the safe operation of the car is an urgent problem to be solved in the car rental industry. This paper presents a cloud platform based on Web. The main work of this paper is as follows: 1. This paper proposes a cloud service platform for vehicle rental based on Web, develops vehicle display, rent calculation, order filling, order management, and so on. Model management, user management, service reminder, real-time monitoring, remote diagnosis and decision making, path planning and other functional modules. In order to improve the stability and scalability of the Web platform, The communication protocol between data acquisition terminal and server is established, and the database system and remote service platform based on ORACLE are designed. The platform has developed a SOCKET routine to receive the data uploaded by the data acquisition terminal, then parsed it and stored it into the database. Finally, the model of automobile fault diagnosis ontology is established based on ontology, which is displayed on the interface. This paper presents a diagnosis decision method based on rule and historical case reasoning, designs the automobile diagnosis rule and diagnosis history case base, develops the interface with visual ability, and proposes the fault cause, fault location, maintenance suggestion, etc. The optimal maintenance points are presented to the user intuitively. (4) based on chaotic ant colony algorithm, the route of vehicle to the maintenance point is planned, and the shortest distance algorithm model is constructed. The chaos disturbance is introduced into the probability transfer of the algorithm to prevent the algorithm from falling into the local optimum. When the ant colony selects the next hop node, the search efficiency is improved by the Euclidean distance selection. The function and reliability of the system are tested and verified. The results show that the system has great advantages in performance and maneuverability and has certain popularization significance.
【學(xué)位授予單位】:華東理工大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2017
【分類號】:U495

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