本文選題：熱力系統(tǒng)　切入點：符號有向圖　出處：《太原理工大學(xué)》2012年碩士論文　論文類型：學(xué)位論文

【摘要】：在火電機組故障中,熱力系統(tǒng)發(fā)生故障的機率很大,因此熱力系統(tǒng)的安全性會對機組整體運行的安全經(jīng)濟性產(chǎn)生巨大影響。由于熱力系統(tǒng)結(jié)構(gòu)復(fù)雜、運行工況多變,在進行故障診斷過程中難以建立和完善故障知識庫,因此對熱力系統(tǒng)進行故障診斷研究十分必要。 本文將圖論和粗糙圖理論與符號有向圖(SDG)相結(jié)合,使得SDG模型更加易于診斷,從而提高SDG故障診斷的準(zhǔn)確性。首先針對SDG多義性推理導(dǎo)致的分辨率低,大系統(tǒng)診斷速度慢、實時性差等問題,將故障傳播圖與SDG兩種方法結(jié)合起來描述系統(tǒng),提出了一種分層符號有向圖(SDG)故障診斷模型。該分層符號有向圖故障診斷模型既具有SDG自身的完備性,又具有故障傳播圖的固有屬性,可以反映系統(tǒng)部件之間的連接關(guān)系,同時將分層技術(shù)、節(jié)點壓縮技術(shù)、約束傳播技術(shù)和對中尋優(yōu)技術(shù)四種優(yōu)選測試點技術(shù)加入改進的符號有向圖模型來構(gòu)建分層SDG模型,并采用回溯搜索策略搜索獨立相容通路進行故障診斷。以上幾種優(yōu)選測試點技術(shù)利用了系統(tǒng)設(shè)備內(nèi)部各個部件之間故障傳播的特性,在推理過程中可以減少候選測試點集合,提高搜索故障源的效率。該方法能夠區(qū)分相同故障模式下診斷不明且難分辨的故障及可能出現(xiàn)的“組合爆炸”問題,所得結(jié)論與傳統(tǒng)SDG診斷結(jié)果進行對比,表明該方法較傳統(tǒng)方法優(yōu)越。最后將該方法應(yīng)用到離心泵與液位系統(tǒng),驗證了其方法的正確性和有效性。 其次,針對使用SDG進行故障分析時所獲信息不完備、不精確的特征,將粗糙集挖掘不確定性問題的優(yōu)點加入SDG故障診斷過程中,提出了一種基于粗糙圖的分層SDG故障診斷模型。該模型包括部件節(jié)點粗糙關(guān)系圖、粗糙分層SDG的故障圖生成算法及故障最大流分析算法三部分。實例驗證和模型分析表明該模型較傳統(tǒng)SDG故障診斷模型更能反映實際情況,所獲診斷結(jié)論更加準(zhǔn)確。最后,將基于粗糙圖的分層SDG故障診斷模型用于熱力系統(tǒng),對其不同關(guān)系層面之間的故障進行診斷,結(jié)果表明該模型能夠降低熱力設(shè)備動態(tài)特性故障知識獲取的復(fù)雜度,及時準(zhǔn)確識別熱力系統(tǒng)早期故障和輕微故障,這些改進都能在很大程度上提高熱力系統(tǒng)診斷效率,促進熱力系統(tǒng)故障診斷技術(shù)不斷的向前發(fā)展。 本文將系統(tǒng)分層理論和粗糙圖、粗糙網(wǎng)絡(luò)理論引入SDG故障診斷,提出了一種基于粗糙圖的分層SDG故障診斷模型,使得SDG搜索推理發(fā)生沖突的概率在一定程度上減少甚至避免,提高了傳統(tǒng)SDG故障診斷搜索推理的分辨率。該方法用于熱力系統(tǒng),實例結(jié)論表明其行之有效、具有良好的通用性,對提高機組運行的安全性和經(jīng)濟性起到一定作用,推動了故障診斷智能化的不斷發(fā)展。
[Abstract]:In the fault of thermal power unit, the probability of thermal system failure is very large, so the safety of thermal system will have a great impact on the safety and economy of the whole operation of the unit, because the structure of the thermal power system is complex and the operating conditions are changeable. In the process of fault diagnosis, it is difficult to establish and perfect the fault knowledge base, so it is necessary to study the fault diagnosis of thermal system. In this paper, graph theory and rough graph theory are combined with symbolic directed graph (SDG) to make the SDG model easier to diagnose and improve the accuracy of SDG fault diagnosis. Firstly, because of the low resolution caused by SDG polysemy reasoning, the diagnosis speed of large system is slow. In this paper, the fault propagation graph and SDG are combined to describe the system, and a hierarchical symbolic directed graph (SDG) fault diagnosis model is proposed, which has the completeness of SDG itself. It also has the inherent properties of the fault propagation graph, which can reflect the connection relationship between the system components, and at the same time, it will be stratified technology, node compression technology, The constraint propagation technique and the four kinds of test point optimization techniques, which include the improved symbolic directed graph model, are added to construct the hierarchical SDG model. And the backtracking search strategy is used to search the independent compatible path for fault diagnosis. The above techniques make use of the characteristics of fault propagation between the components of the system equipment, and can reduce the set of candidate test points in the reasoning process. To improve the efficiency of searching fault sources, this method can distinguish the unknown and difficult faults in the same fault mode from the "combined explosion" problem that may occur. The results obtained are compared with the traditional SDG diagnosis results. It is shown that this method is superior to the traditional method. Finally, the method is applied to the centrifugal pump and liquid level system, and the correctness and effectiveness of the method are verified. Secondly, aiming at the incomplete and inaccurate information obtained in fault analysis with SDG, the advantages of rough set mining uncertainty problem are added to the process of SDG fault diagnosis. A hierarchical SDG fault diagnosis model based on rough graph is proposed. There are three parts of fault graph generation algorithm and fault maximum flow analysis algorithm of rough layered SDG. The example verification and model analysis show that the model can reflect the actual situation better than the traditional SDG fault diagnosis model, and the diagnosis results are more accurate. The hierarchical SDG fault diagnosis model based on rough graph is applied to the fault diagnosis of thermal system. The results show that the model can reduce the complexity of fault knowledge acquisition of thermal equipment dynamic characteristics. These improvements can improve the efficiency of thermal system diagnosis to a great extent and promote the continuous development of thermal system fault diagnosis technology. In this paper, the hierarchical theory of system, rough graph and rough network theory are introduced into SDG fault diagnosis, and a hierarchical SDG fault diagnosis model based on rough graph is proposed, which can reduce or even avoid the probability of collision of SDG search reasoning to a certain extent. The resolution of traditional SDG fault diagnosis search reasoning is improved. The method is used in thermal system. The example shows that the method is effective, has good generality, and plays a certain role in improving the safety and economy of unit operation. It promotes the development of fault diagnosis intelligence.
【學(xué)位授予單位】：太原理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2012
【分類號】：TM621;TH165.3

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