發(fā)布時間：2018-06-17 18:46

  本文選題：礦井提升機 + 遠程在線監(jiān)測��； 參考：《太原理工大學》2015年碩士論文

【摘要】：提升機是礦山的重要機電設備，素有礦井“咽喉”之稱。其運行狀況直接影響礦區(qū)的生產能力，一旦提升機出現(xiàn)故障，將造成礦區(qū)生產工作癱瘓，甚至對工作人員造成傷害，因此，提升機的運行狀況一直是安全生產過程中的主要監(jiān)管對象，對其運行狀況進行監(jiān)控與故障診斷具有重要的實際意義。 論文開始對提升機狀態(tài)監(jiān)測與故障診斷發(fā)展情況進行闡述分析，結合課題實際應用條件，以及礦區(qū)通信方式構成，最終確定基于以太網通信技術的提升機遠程在線監(jiān)測與故障診斷的研究方向。 文中在系統(tǒng)設計過程中主要結合多信息采集、多信息融合的設計思想，在故障診斷問題中提出SVM與D-S證據(jù)算法相結合的信息融合算法模型，，充分實現(xiàn)兩種算法的優(yōu)勢互補，取得了較好的效果。本文的主要工作內容有： (1)研究分析提升機狀態(tài)監(jiān)測與故障診斷的現(xiàn)實意義，從目前研究的現(xiàn)狀總結分析出現(xiàn)有研究的不足。 (2)對提升機自身各部分組成及工作原理進行分析研究，總結出提升機各部分故障類型，在此基礎上設計提出本文的監(jiān)測與故障診斷方法。 (3)詳細闡述各部分硬件的選型與各級軟件組成及使用。 (4)應用基于多信息融合思想，采用基于SVM和D-S證據(jù)理論相結合的故障診斷方法，建立了故障診斷模型，并對模擬故障特征數(shù)據(jù)進行故障診斷分析。 (5)在實驗室內充分模擬論證之后，實現(xiàn)該套監(jiān)測與故障診斷系統(tǒng)在礦區(qū)的成功安裝與使用。 本套系統(tǒng)可以實現(xiàn)以下功能，礦區(qū)三臺提升機信息進行遠程實時在線的監(jiān)控管理和不同地域數(shù)據(jù)的融合；系統(tǒng)和礦區(qū)的其他系統(tǒng)存在很大的整合空間與擴展空間；系統(tǒng)可以實現(xiàn)監(jiān)測信息整個礦區(qū)的全網WEB發(fā)布；通過基于SVM與D-S證據(jù)理論相結合的故障診斷模型很好的實現(xiàn)了故障診斷；同時，系統(tǒng)還具有數(shù)據(jù)保存功能，方便建立提升機系統(tǒng)故障數(shù)據(jù)庫，為課題的更深入研究提供寶貴的資料，為更好的提高提升機安全運行水平提供保障。
[Abstract]:Hoist is an important mechanical and electrical equipment, known as the mine "throat" said. Its running condition directly affects the production capacity of the mining area. Once the hoist breaks down, the production work in the mining area will be paralyzed, and even the staff will be injured. Therefore, The running condition of hoist is always the main supervision object in the process of safety production. It is of great practical significance to monitor and diagnose the running condition of hoist. The paper begins to elaborate and analyze the status monitoring and fault diagnosis of hoist, combined with the practical application conditions of the subject, and the composition of communication mode in mining area. Finally, the research direction of remote on-line monitoring and fault diagnosis of hoist based on Ethernet communication technology is determined. In the process of system design, this paper mainly combines the design idea of multi-information collection and multi-information fusion, and puts forward the information fusion algorithm model combining SVM and D-S evidence algorithm in fault diagnosis, which fully realizes the complementary advantages of the two algorithms. Good results have been achieved. The main contents of this paper are as follows: 1) the practical significance of studying and analyzing the status monitoring and fault diagnosis of hoist. From the present research situation summary analysis has the research insufficiency. (2) carries on the analysis to the hoist itself each part composition and the work principle, summarizes the hoist each part breakdown type, On this basis, the method of monitoring and fault diagnosis in this paper is designed and put forward. (3) the selection of hardware and the composition and use of software at all levels are described in detail. 4) the application is based on the idea of multi-information fusion. The fault diagnosis model based on SVM and D-S evidence theory is established, and the fault diagnosis analysis of simulated fault characteristic data is carried out. The monitoring and fault diagnosis system is successfully installed and used in mining area. The system can realize the following functions: remote real-time monitoring and management of three hoist information and integration of different regional data, there is a great space for integration and expansion between the system and other systems in the mining area; The system can realize the whole Web release of monitoring information in the whole mining area. The fault diagnosis model based on SVM and D-S evidence theory is used to realize the fault diagnosis. At the same time, the system also has the function of data saving. It is convenient to set up the fault database of hoist system, to provide valuable information for further study of the subject, and to provide guarantee for improving the safe operation level of hoist.
【學位授予單位】：太原理工大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TD633

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本文編號：2032074