本文選題：符號有向圖　切入點：多塊核主元分析　出處：《中南大學(xué)》2013年碩士論文

【摘要】：摘要：故障診斷是工業(yè)生產(chǎn)特別是流程工業(yè)中的一個重要問題,在過去的幾十年中有大量致力于這方面的研究�；诜栍邢驁D(Signed Directed Graph, SDG)模型的故障診斷方法,由于具有表達(dá)復(fù)雜因果關(guān)系和包容大規(guī)模潛在信息的能力,完備性好、適應(yīng)性強,同時可提供故障傳播路徑和演變解釋,得到了學(xué)者們的廣泛關(guān)注。然而,基于SDG模型的故障診斷方法作為純定性方法存在分辨率低且所建SDG模型精確度、可靠性不高等問題。針對SDG存在的問題,將傳遞熵、多塊核主元分析(Multiblock Kernel Principal Component Analysis, MBKPCA)、概率論等定量處理方法與SDG相結(jié)合,開展基于SDG的故障診斷方法研究,具有科學(xué)意義和應(yīng)用價值。論文主要研究工作及創(chuàng)新成果如下： (1)針對傳統(tǒng)SDG建模方法中過程知識不完備、錯誤以及精確數(shù)學(xué)模型缺失的不足,引入傳遞熵進(jìn)行SDG建模�？紤]到系統(tǒng)中各變量之間的傳遞熵既能量化變量之間的依賴性,又能測量變量之間的方向性,充分利用過程歷史數(shù)據(jù),基于傳遞熵構(gòu)建變量節(jié)點鏈模型,實現(xiàn)SDG建模,從而提高SDG建模的準(zhǔn)確性和可靠性。 (2)針對大規(guī)模工業(yè)過程變量之間關(guān)系復(fù)雜,故障難確定難診斷的特點,提出一種基于MBKPCA口SDG的故障診斷方法。首先,提出基于SDG和優(yōu)先級的分塊策略,以強連通元SCC為最高優(yōu)先級、多入＼出度節(jié)點群為次高優(yōu)先級、節(jié)點鏈為最低優(yōu)先級對過程進(jìn)行分塊；在此基礎(chǔ)上,采用MBKPCA進(jìn)行過程監(jiān)控,對于檢測到的故障,先確定故障發(fā)生在哪一個數(shù)據(jù)塊,再觸發(fā)SDG在故障塊內(nèi)完成故障定位。所提方法克服了MBKPCA故障隔離不完全和SDG推理過程中組合爆炸的缺點,可提高復(fù)雜工業(yè)過程故障診斷的準(zhǔn)確度與速度。 (3)對于存在正反饋回路而無法使用上述方法實現(xiàn)故障完全隔離的特殊情況,進(jìn)一步提出改進(jìn)的概率符號有向圖(Probabilistic Signed Digraph, PSDG)方法,提出新的環(huán)狀結(jié)構(gòu)打開方法并確定打開后的支路概率,根據(jù)計算出的后驗概率對可能的故障根源進(jìn)行排序,以此概率排序為依據(jù)隔離故障,確保SDG故障診斷流程的完整性。 基于Tennessee Eastman過程的仿真研究驗證了所提故障診斷方法的有效性。論文共有圖37幅,表7個,參考文獻(xiàn)80篇。
[Abstract]:Absrtact: fault diagnosis is an important problem in industrial production, especially in process industry.The method of fault diagnosis based on symbolic directed graph signed Directed Graph (SDGs) model, because of its ability to express complex causality and contain large scale potential information, is good in completeness and adaptability, and can also provide the path of fault propagation and explanation of evolution.It has received extensive attention from scholars.However, as a pure qualitative method, the fault diagnosis method based on SDG model has some problems, such as low resolution, accuracy and reliability of the established SDG model.Aiming at the problems existing in SDG, combining the quantitative processing methods such as transfer entropy, multiblock Kernel Principal Component analysis, MBKPCAA and probability theory with SDG, it is of scientific significance and application value to develop the research of SDG based fault diagnosis method.The main research work and innovative results are as follows:1) aiming at the defects of incomplete process knowledge, errors and lack of accurate mathematical models in traditional SDG modeling methods, transfer entropy is introduced to model SDG.Considering that the transfer entropy of each variable in the system can not only quantify the dependence between variables, but also measure the directivity of variables, make full use of the process history data, construct the model of the node chain of variables based on the transfer entropy, and realize the SDG modeling.In order to improve the accuracy and reliability of SDG modeling.A fault diagnosis method based on MBKPCA port SDG is proposed to overcome the complex relationship between variables in large-scale industrial process and the difficulty of fault diagnosis.Firstly, a block strategy based on SDG and priority is proposed, in which the strongly connected element SCC is the highest priority, the multi-input / output node group is the next high priority, and the node chain is the lowest priority to block the process.The MBKPCA is used to monitor the process. For the detected faults, it is determined which data block the fault occurs, and then the SDG is triggered to complete the fault location in the fault block.The proposed method overcomes the shortcomings of incomplete MBKPCA fault isolation and combined explosion in SDG reasoning process and can improve the accuracy and speed of fault diagnosis in complex industrial processes.3) for the special case where there is a positive feedback loop and the above method can not be used to achieve complete fault isolation, an improved probabilistic Signed graph (PSDG) method is proposed.A new opening method of annular structure is proposed and the open branch probability is determined. According to the calculated posteriori probability, the possible fault source is sorted in order to isolate the faults according to the probabilistic ranking to ensure the integrity of the SDG fault diagnosis process.Simulation results based on Tennessee Eastman process verify the effectiveness of the proposed fault diagnosis method.There are 37 pictures, 7 tables and 80 references.
【學(xué)位授予單位】：中南大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：TH165.3

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