本文選題：盾構機推進系統(tǒng) + 故障預測��； 參考：《南京理工大學》2014年碩士論文

【摘要】：盾構機作為一種被廣泛應用于城市地鐵建設的大型工程機械,其工作條件受到多種自然環(huán)境的影響,容易發(fā)生故障,因此對其故障預測技術的研究有十分重要的意義,但是采用傳統(tǒng)故障預測技術很難滿足要求,而隨著人工智能故障預測技術的出現(xiàn)及其在實際工程應用中取得了很好的預測效果,所以對盾構機的故障采用智能預測方法變得現(xiàn)實可行。本文主要是通過對專家系統(tǒng)理論知識的分析,并結合模糊邏輯理論和神經(jīng)網(wǎng)絡知識的技術優(yōu)勢,對盾構機推進系統(tǒng)的故障預測進行了初步的探討,完成了如下幾個方面的工作： (1)建立了盾構機推進系統(tǒng)的故障知識庫。對盾構機推進系統(tǒng)的故障產(chǎn)生機理進行了分析,將其故障分為了淺層故障知識和深層故障知識,并對與盾構機推進系統(tǒng)相關的故障征兆參數(shù)進行了選取,同時引入數(shù)據(jù)庫技術對故障知識庫進行了設計和處理。 (2)研究了盾構機推進系統(tǒng)的故障預測推理機的算法。針對盾構機推進系統(tǒng)故障的復雜性和不確定性,引入模糊邏輯理論和神經(jīng)網(wǎng)絡知識對其故障預測推理機分別進行設計與仿真,在對比分析了它們的優(yōu)缺點與精確度之后,提出將模糊神經(jīng)網(wǎng)絡運用于故障預測推理機的設計之中,并在MATLAB軟件中對模糊神經(jīng)網(wǎng)絡故障預測算法進行了實驗仿真,其仿真結果具有更高的精度,證明了其在盾構機推進系統(tǒng)故障預測中的有效性和準確性。 (3)設計了盾構機推進系統(tǒng)的故障預測軟件。結合軟件設計原則,本文選擇VisualC++6.0軟件作為專家系統(tǒng)的軟件設計平臺,并通過OPC技術完成了VC與WinCC軟件的數(shù)據(jù)交換,采用COM組件技術實現(xiàn)了VC對MATLAB編寫的神經(jīng)網(wǎng)絡和模糊神經(jīng)網(wǎng)絡故障預測算法的調(diào)用,同時在開發(fā)過程中采用界面化和模塊化設計方式,使得對系統(tǒng)軟件功能模塊的擴充更加方便,也更加符合整個系統(tǒng)軟件的設計要求。
[Abstract]:As a kind of large-scale construction machinery widely used in urban subway construction, the working conditions of shield machine are affected by many kinds of natural environment and are prone to failure. Therefore, it is of great significance to study the fault prediction technology of shield machine. However, it is difficult to meet the requirements by using the traditional fault prediction technology, and with the emergence of artificial intelligence fault prediction technology and its application in practical engineering has achieved a very good prediction effect. So it is feasible to apply intelligent prediction method to shield machine fault. Based on the analysis of expert system theory knowledge and the technical advantages of fuzzy logic theory and neural network knowledge, this paper makes a preliminary discussion on the fault prediction of shield machine propulsion system, and accomplishes the following work: The fault knowledge base of shield machine propulsion system is established. The fault generation mechanism of shield machine propulsion system is analyzed, the fault is divided into shallow fault knowledge and deep fault knowledge, and the fault symptom parameters related to shield machine propulsion system are selected. At the same time, the database technology is introduced to design and deal with the fault knowledge base. The algorithm of fault prediction inference machine for shield machine propulsion system is studied. In view of the complexity and uncertainty of the fault of shield machine propulsion system, the fuzzy logic theory and neural network knowledge are introduced to design and simulate the fault prediction inference machine respectively. The fuzzy neural network is applied to the design of the fault prediction inference machine, and the simulation of the fuzzy neural network fault prediction algorithm is carried out in the MATLAB software. The simulation results show that the simulation results have higher accuracy. The validity and accuracy of this method in fault prediction of shield machine propulsion system are proved. The software of fault prediction for shield machine propulsion system is designed. Combined with the principle of software design, this paper chooses VisualC 6.0 software as the software design platform of expert system, and completes the data exchange between VC and WinCC software through OPC technology. The COM component technology is used to realize the call of the neural network and fuzzy neural network fault prediction algorithm written by MATLAB by VC. At the same time, the interface and modularization design method are adopted in the development process. It makes it more convenient to expand the function module of the system software and meets the design requirements of the whole system software.
【學位授予單位】：南京理工大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：U455.39

【參考文獻】

相關期刊論文 前10條

1 黃景德,王興貴,王祖光;自行火炮故障預測模糊專家系統(tǒng)研究[J];兵工學報;2002年03期

2 史天運,王信義,張之敬,朱小燕;神經(jīng)網(wǎng)絡與模糊故障診斷專家系統(tǒng)結合的應用研究[J];北京理工大學學報;1998年01期

3 龔伏廷;;淺談數(shù)據(jù)庫技術的應用與發(fā)展[J];電腦編程技巧與維護;2012年12期

4 曹立軍,杜秀菊,秦俊奇,黃景德;復雜裝備的故障預測技術[J];飛航導彈;2004年04期

5 鐘堅;;盾構機技術研究[J];廣東造船;2012年03期

6 曾聲奎,Michael G.Pecht,吳際;故障預測與健康管理(PHM)技術的現(xiàn)狀與發(fā)展[J];航空學報;2005年05期

7 劉白林,范躍華;一種故障診斷專家知識庫編輯和維護系統(tǒng)[J];火力與指揮控制;2004年05期

8 左憲章;康健;李浩;唐力偉;;故障預測技術綜述[J];火力與指揮控制;2010年01期

9 黃景德;;虛擬環(huán)境下大口徑火炮故障預測技術——虛擬預測環(huán)境[J];火炮發(fā)射與控制學報;2006年02期

10 梁旭;李行善;張磊;于勁松;;支持視情維修的故障預測技術研究[J];測控技術;2007年06期

相關博士學位論文 前1條

1 何映思;模糊推理方法及模糊邏輯形式系統(tǒng)研究[D];西南大學;2011年

，

本文編號：1991731