發(fā)布時間：2018-06-03 18:14

  本文選題：專家系統(tǒng) + 巡檢機器人��； 參考：《山東科技大學》2017年碩士論文

【摘要】：隨著科學技術的發(fā)展,尤其是機器人技術的發(fā)展,輸電線路的巡檢工作逐漸由人工巡檢方式向機器人巡檢方式過渡,巡檢機器人在輸電線路巡檢工作中的重要性逐漸得到認可。由于輸電線路環(huán)境復雜,障礙多樣,巡檢機器人自動越障的問題日益凸顯,主要表現(xiàn)在越障穩(wěn)定性差、越障效率低等。因此,研究一種新型的提高巡檢機器人自動越障穩(wěn)定性和效率的方法具有十分重要的意義。本文在深入研究了產(chǎn)生式規(guī)則和專家系統(tǒng)理論的基礎上,充分調研了巡檢機器人控制系統(tǒng)的發(fā)展現(xiàn)狀,探討了課題研究的目標與可行性,提出了一種基于規(guī)則的專家系統(tǒng)的方法,將產(chǎn)生式規(guī)則和專家系統(tǒng)理論應用到巡檢機器人自動越障控制過程中。本文結合巡檢機器人結構、機器人自由度和傳感器信號特點,對傳感器信號采集電路、安裝布局和機器人自動越障流程進行了深入的研究,分析了巡檢機器人自動越障的功能要求,設計了自動越障專家系統(tǒng)的總體結構、功能模塊和工作流程。分析了知識的概念,知識的表示方式和獲取方式,采用直接獲取和間接獲取相結合的知識獲取方式和產(chǎn)生式規(guī)則的知識表示方式建立了專家系統(tǒng)的知識庫,并設計了知識庫的維護流程。在此基礎上探討了推理機的推理方式、推理方向、沖突消除策略和Rete匹配算法,分析比較了盲目性搜索和啟發(fā)性搜索兩種搜索方式,采用確定性推理方式、正向推理方向、盲目性搜索方式和Rete改進算法,設計了推理機的推理流程。在建立了知識庫和推理機的基礎上,以Windows7為操作系統(tǒng),采用Visual Studio 2010作為開發(fā)工具,以C#語言編寫推理程序,以SQL Server 2008作為數(shù)據(jù)庫,開發(fā)了基于規(guī)則的巡檢機器人自動越障專家系統(tǒng)。它具有良好的人機界面,實現(xiàn)了自動越障、知識庫管理、幫助等功能。在完成理論分析的基礎上,運用巡檢機器人自動越障對本專家系統(tǒng)進行了實驗,驗證了越障過程理論分析的正確性與可靠性,實驗結果表明了將專家系統(tǒng)理論應用于巡檢機器人自動越障過程控制的可行性。
[Abstract]:With the development of science and technology, especially the development of robot technology, the inspection of transmission lines is gradually transferred from manual inspection to robot inspection, and the importance of inspection robot in transmission line inspection is gradually recognized. Due to the complex environment and various obstacles of transmission lines, the problem of automatic obstacle crossing of inspection robot is increasingly prominent, which is mainly reflected in the poor stability and low efficiency of obstacle crossing. Therefore, it is of great significance to study a new method to improve the stability and efficiency of automatic obstacle crossing. On the basis of in-depth study of production rules and expert system theory, this paper makes a full investigation of the current situation of the control system of the inspection robot, and discusses the goal and feasibility of the research. In this paper, a rule-based expert system method is proposed. The production rule and expert system theory are applied to the automatic obstacle control of the inspection robot. Combined with the structure of the robot, the degree of freedom of the robot and the characteristics of the sensor signal, this paper makes a deep research on the sensor signal acquisition circuit, the installation layout and the robot automatic obstacle crossing flow. This paper analyzes the functional requirements of the automatic obstacle crossing of the inspection robot, and designs the overall structure, function module and work flow of the automatic obstacle crossing expert system. This paper analyzes the concept of knowledge, the representation and acquisition of knowledge, and establishes the knowledge base of expert system by the combination of direct acquisition and indirect acquisition and knowledge representation of production rules. The maintenance flow of knowledge base is designed. On this basis, the reasoning mode, direction, conflict resolution strategy and Rete matching algorithm of the inference engine are discussed. Two search methods, blind search and heuristic search, are analyzed and compared. The blind search method and the improved Rete algorithm are used to design the reasoning flow of the inference machine. Based on the establishment of knowledge base and inference engine, Windows7 is used as operating system, Visual Studio 2010 is used as development tool, reasoning program is written in C # language, and SQL Server 2008 is used as database. A rule-based automatic obstacle crossing expert system for inspection robot is developed. It has good man-machine interface, automatic obstacle surmounting, knowledge base management, help and other functions. On the basis of the theoretical analysis, the experiment of the expert system is carried out with the automatic obstacle surmounting of the inspection robot, and the correctness and reliability of the theoretical analysis of the obstacle surmounting process are verified. The experimental results show the feasibility of applying the expert system theory to the automatic obstacle control of the inspection robot.
【學位授予單位】：山東科技大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP242

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本文編號：1973723