【摘要】：目前,計(jì)算機(jī)智能已經(jīng)在故障診斷中得到了廣泛應(yīng)用。粗糙集理論是波蘭教授Z.Pawlak提出的,是一種研究不精確知識(shí)及不完整數(shù)據(jù)的表達(dá)、學(xué)習(xí)、歸納的數(shù)學(xué)工具。人工神經(jīng)網(wǎng)絡(luò)是模擬人類思維的非線性動(dòng)力學(xué)系統(tǒng),具有并行協(xié)同處理和可學(xué)習(xí)能力,可以實(shí)現(xiàn)識(shí)別與分類、優(yōu)化計(jì)算、聯(lián)想記憶、知識(shí)處理等功能。 注水泵機(jī)組的振動(dòng)數(shù)據(jù)含有注水泵機(jī)組工作狀態(tài)的大量信息,是注水泵機(jī)組故障診斷的重要資料。本文利用粗糙集的屬性約簡、知識(shí)處理和神經(jīng)網(wǎng)絡(luò)的可學(xué)習(xí)、分類、并行處理的能力,建立粗糙集神經(jīng)網(wǎng)絡(luò)完成注水泵機(jī)組的故障診斷。 本文融合粗糙集與神經(jīng)網(wǎng)絡(luò)的研究成果,先利用粗糙集理論有效降低樣本特征的維數(shù),再利用約簡后樣本構(gòu)造網(wǎng)絡(luò),減少神經(jīng)網(wǎng)絡(luò)學(xué)習(xí)和運(yùn)行的時(shí)間。最后利用MATLAB軟件建注水泵機(jī)組故障診斷系統(tǒng)。 網(wǎng)絡(luò)診斷結(jié)果表明對于已學(xué)習(xí)過的樣本知識(shí),仿真結(jié)果與實(shí)際相吻合,表明該網(wǎng)絡(luò)能夠正確地進(jìn)行故障診斷,粗糙集神經(jīng)網(wǎng)絡(luò)在注水泵機(jī)組故障診斷中的的研究具有一定的理論意義和實(shí)踐價(jià)值。
[Abstract]:At present, computer intelligence has been widely used in fault diagnosis. Rough set theory is a mathematical tool for studying imprecise knowledge and incomplete data representation, learning and induction, which is proposed by Z.Pawlak, a Polish professor. Artificial neural network (Ann) is a nonlinear dynamic system that simulates human thinking. It has the ability of parallel cooperative processing and learning. It can realize the functions of recognition and classification, optimization calculation, associative memory, knowledge processing and so on. The vibration data of the water injection pump unit contain a lot of information about the working state of the water injection pump unit, and it is an important data for the fault diagnosis of the water injection pump unit. In this paper, the ability of attribute reduction, knowledge processing and neural network for learning, classification and parallel processing of rough set is used to establish rough set neural network to complete fault diagnosis of water injection pump unit. In this paper, the research results of rough set and neural network are combined. Firstly, rough set theory is used to effectively reduce the dimension of the sample feature, then the network is constructed by using the reduced sample to reduce the learning and running time of the neural network. Finally, the fault diagnosis system of water injection pump unit is built by MATLAB software. The results of network diagnosis show that the simulation results are in agreement with the actual situation for the sample knowledge that has been learned, which shows that the network can correctly diagnose the faults. The research of rough set neural network in fault diagnosis of water injection pump unit has certain theoretical significance and practical value.
【學(xué)位授予單位】：西安石油大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：TH165.3;TP183

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本文編號(hào)：2129845