基于神經(jīng)網(wǎng)絡(luò)的計算機(jī)聯(lián)鎖系統(tǒng)壽命評估方法
本文選題:計算機(jī)聯(lián)鎖系統(tǒng) + 壽命預(yù)測; 參考:《北京交通大學(xué)》2017年碩士論文
【摘要】:計算機(jī)聯(lián)鎖系統(tǒng)是鐵路信號的核心技術(shù)裝備,是保證安全高效運(yùn)行及鐵路車站作業(yè)的重要環(huán)節(jié)。現(xiàn)階段,我國鐵路計算機(jī)聯(lián)鎖系統(tǒng)的壽命周期管理辦法主要參考沿用傳統(tǒng)繼電聯(lián)鎖設(shè)備的有關(guān)規(guī)定,缺乏針對系統(tǒng)中電子設(shè)備使用壽命的分析與評估方法,這在很大程度上限制了對計算機(jī)聯(lián)鎖系統(tǒng)使用壽命的科學(xué)管理。本文從系統(tǒng)的體系結(jié)構(gòu)出發(fā)研究了一種基于神經(jīng)網(wǎng)絡(luò)的計算機(jī)聯(lián)鎖系統(tǒng)壽命評估方法。主要工作如下:(1)綜合分析了計算機(jī)聯(lián)鎖系統(tǒng)應(yīng)用現(xiàn)狀和各領(lǐng)域系統(tǒng)壽命評估方法研究的現(xiàn)狀,提出了適合于計算機(jī)聯(lián)鎖系統(tǒng)的壽命評估方案,給出了壽命評估的具體實(shí)施步驟;(2)結(jié)合聯(lián)鎖系統(tǒng)硬件結(jié)構(gòu)和部件功能分析,以二乘二取二制式聯(lián)鎖系統(tǒng)為主要研究對象,構(gòu)建了聯(lián)鎖系統(tǒng)故障樹模型;通過定性分析得出故障樹模型的最小割集,建立了部件故障與系統(tǒng)失效之間的關(guān)系,構(gòu)造了神經(jīng)網(wǎng)絡(luò)訓(xùn)練數(shù)據(jù)集;(3)研究了神經(jīng)網(wǎng)絡(luò)預(yù)測性能提升方法,利用粒子群算法對GRNN神經(jīng)網(wǎng)絡(luò)進(jìn)行中心神經(jīng)元寬度矩陣的參數(shù)尋優(yōu),有效提高了神經(jīng)網(wǎng)絡(luò)預(yù)測的精度;(4)為了充分體現(xiàn)聯(lián)鎖系統(tǒng)硬件冗余結(jié)構(gòu)特點(diǎn),基于GRNN神經(jīng)網(wǎng)絡(luò)、改進(jìn)型GRNN神經(jīng)網(wǎng)絡(luò)和BP神經(jīng)網(wǎng)絡(luò),建立了三種不同的計算機(jī)聯(lián)鎖系統(tǒng)壽命評估模型;(5)對三種基于神經(jīng)網(wǎng)絡(luò)方法的聯(lián)鎖系統(tǒng)壽命評估模型,進(jìn)行了性能對比分析,并結(jié)合系統(tǒng)特點(diǎn),給出了網(wǎng)絡(luò)性能最優(yōu)的評估模型。最后,以我國鐵路廣泛使用的AB型聯(lián)鎖系統(tǒng)為對象,利用現(xiàn)場運(yùn)營數(shù)據(jù),進(jìn)行系統(tǒng)壽命評估,檢驗(yàn)本文提出評估模型和方法的有效性。本文通過理論分析和實(shí)例驗(yàn)證,給出了一種基于神經(jīng)網(wǎng)絡(luò)的計算機(jī)聯(lián)鎖系統(tǒng)壽命評估方法,以實(shí)現(xiàn)對計算機(jī)聯(lián)鎖系統(tǒng)服役壽命的科學(xué)預(yù)測評估,可為我國計算機(jī)聯(lián)鎖系統(tǒng)的運(yùn)營管理提供借鑒和參考。
[Abstract]:Computer interlocking system is the core technology equipment of railway signal and an important link to ensure safe and efficient operation and railway station operation.At present, the life cycle management method of railway computer interlocking system in our country mainly refers to the relevant provisions of traditional relay interlocking equipment, and lacks the analysis and evaluation method for the service life of electronic equipment in the system.This limits the scientific management of the life of computer interlocking system to a great extent.In this paper, a method of evaluating the life of computer interlocking system based on neural network is studied based on the architecture of the system.The main work is as follows: (1) A comprehensive analysis of the application status of computer interlocking system and the present situation of life evaluation methods in various fields are given, and a life evaluation scheme suitable for computer interlocking system is put forward.Based on the analysis of hardware structure and component function of the interlocking system, the fault tree model of the interlocking system is constructed by taking the two-plus-two-mode interlocking system as the main research object.Through qualitative analysis, the minimum cut set of fault tree model is obtained, the relationship between component failure and system failure is established, and the neural network training data set is constructed.Particle swarm optimization algorithm is used to optimize the parameters of central neuron width matrix of GRNN neural network, which effectively improves the precision of neural network prediction. In order to fully reflect the characteristics of hardware redundancy structure of interlocking system, it is based on GRNN neural network.Improved GRNN neural network and BP neural network, three different computer interlocking system life evaluation models are established. The performances of three interlocking system life evaluation models based on neural network are compared and analyzed.Combined with the characteristics of the system, the optimal evaluation model of network performance is given.Finally, taking AB type interlocking system, which is widely used in railway in China, as the object, using field operation data, the system life evaluation is carried out, and the validity of the evaluation model and method proposed in this paper is verified.In this paper, a method of evaluating the service life of computer interlocking system based on neural network is presented through theoretical analysis and example verification, so as to realize the scientific prediction and evaluation of the service life of computer interlocking system.It can provide reference and reference for the operation and management of computer interlocking system in China.
【學(xué)位授予單位】:北京交通大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2017
【分類號】:U284.362;TP183
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