基于粒计算的SDG故障诊断关键问题研究
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摘要
本文研究工作属于粒计算、图论及其在故障检测与诊断领域中的应用研究,是计算机学、信息学、图论学的交叉和前沿研究领域。本文研究成果对于实际生产中复杂系统的故障检测与诊断的理论研究和应用研究有重大意义。
本研究将粒计算理论与符号有向图相结合,提出了一种全新的故障诊断方法,并将其应用于田纳西-伊斯曼过程(Tennessee-Eastman Process, TEP)的故障诊断。具体研究内容包括：
(1)提出了基于粒的SDG模型,用粒来形式化描述SDG模型中的元素,这是一种描述SDG模型的新方法；
(2)将粒计算与系统分层理论、图论引入SDG故障诊断,提出了一种基于分层SDG粒图的故障诊断模型,该模型具有SDG的完备性,能够反映系统部件之间的连接关系,并且简化了模块之间的关系,使得SDG模型更加易于诊断；将该模型应用于高加给水系统和TEP系统,仿真结果表明了新方法的有效性。
(3)对现有粒矩阵知识约简算法进行了改进,提出了基于节点重要性和基于粒度熵的知识约简算法,能更好的找出最小相对属性约简和最优诊断规则集；
(4)提出了一种基于相似度的搜索推理算法,通过计算最大相似度寻找现场采集信息对应的决策,可以有效减少推理结果冲突的概率,提高分辨率；
(5)将模糊理论应用于节点状态和支路状态的定义,实现定性SDG模型的定量模糊化,提出了基于模糊理论的相容支路判决算法,生成了基于模糊-SDG的故障诊断方法；
(6)开发了基于组态软件的实时故障预测诊断仿真实验系统,最后经TEP系统案例,表明该方法及系统的有效性和实用性。
本文的创新性成果如下：
(1)提出了分层SDG粒图的故障诊断模型；
(2)提出了基于节点重要性和粒度熵的知识约简算法；
(3)提出了一种基于相似度的搜索推理算法；
(4)开发了基于组态软件的实时故障预测诊断仿真实验系统并将其应用到TEP仿真系统的故障诊断中。
This study focus on the Granular Computing (GrC), Graph Theory, Singed Directed Graph (SDG) and their applications in fault detection and diagnosis. The research reaches the cross-frontier of the computer science, information science and graph theory. The research results have great significance both for theoretical study and industrial applications of fault detection and diagnosis for complex systems in the real world.
Combined with GrC, Graph Theory and SDG together, a new fault diagnosis method was presented in this paper, which has been successfully applied to the Tennessee-Eastman process (TEP).
The research mainly includes but not limited in the following sections:
(1) Granule-based SDG model was established and granule was applied to describe the elements in SDG, this is a new description method for SDG model.
(2) By introducing GrC, system hierarchical theory, and graph theory into SDG fault diagnosis method, a new hierarchical SDG granular graph model was presented, which not only keep the completeness of the SDG but also simplify the interconnect relation among the system elements. Furthermore, the model was applied to High Pressure Heater System and TEP. The simulation results showed the effectiveness of the proposed algorithm.
(3) Improving the existing Granular Matrix-based knowledge reduction algorithm by proposed node important-based and granlularity entropy-based knowledge reduction algorithm, which can help find the minimal attribute set and optimal diagnosis rule base.
(4) A similarity based researching and reasoning algorithm was proposed, which can obtain the most possible fault sources by computing and sorting the similarity. This method can improve resolution by effectively reducing or even avoiding conflict probability of reasoning results.
(5) By applying Fuzzy theory to the definition of the node state and tributary state, realizing the quantitative fuzzification of qualitative SDG model. Fuzzy set-based consistent path decision making algorithm was also proposed, which result in a fuzzy-SDG-based fault diagnosis method.
(6) Design and develop a real time fault predictive diagnosis system based on configuration software, which realize the simulation for TEP, and prove the efficiency of the proposed algorithm.
The innovations of this paper are as follows:
(1) Proposed a hierarchical SDG fault diagnosis model and established hierarchical SDG model for High Pressure Heater System and TEP.
(2) Proposed two knowledge reduction algorithms respectively based on node importance and granularity entropy;
(3) Proposed a research and reasoning algorithm based on similarity;
(4) Developed a real time predictive fault diagnosis method based on configuration software, which has been successfully applied to the TEP diagnosis.
本研究将粒计算理论与符号有向图相结合,提出了一种全新的故障诊断方法,并将其应用于田纳西-伊斯曼过程(Tennessee-Eastman Process, TEP)的故障诊断。具体研究内容包括：
(1)提出了基于粒的SDG模型,用粒来形式化描述SDG模型中的元素,这是一种描述SDG模型的新方法；
(2)将粒计算与系统分层理论、图论引入SDG故障诊断,提出了一种基于分层SDG粒图的故障诊断模型,该模型具有SDG的完备性,能够反映系统部件之间的连接关系,并且简化了模块之间的关系,使得SDG模型更加易于诊断；将该模型应用于高加给水系统和TEP系统,仿真结果表明了新方法的有效性。
(3)对现有粒矩阵知识约简算法进行了改进,提出了基于节点重要性和基于粒度熵的知识约简算法,能更好的找出最小相对属性约简和最优诊断规则集；
(4)提出了一种基于相似度的搜索推理算法,通过计算最大相似度寻找现场采集信息对应的决策,可以有效减少推理结果冲突的概率,提高分辨率；
(5)将模糊理论应用于节点状态和支路状态的定义,实现定性SDG模型的定量模糊化,提出了基于模糊理论的相容支路判决算法,生成了基于模糊-SDG的故障诊断方法；
(6)开发了基于组态软件的实时故障预测诊断仿真实验系统,最后经TEP系统案例,表明该方法及系统的有效性和实用性。
本文的创新性成果如下：
(1)提出了分层SDG粒图的故障诊断模型；
(2)提出了基于节点重要性和粒度熵的知识约简算法；
(3)提出了一种基于相似度的搜索推理算法；
(4)开发了基于组态软件的实时故障预测诊断仿真实验系统并将其应用到TEP仿真系统的故障诊断中。
This study focus on the Granular Computing (GrC), Graph Theory, Singed Directed Graph (SDG) and their applications in fault detection and diagnosis. The research reaches the cross-frontier of the computer science, information science and graph theory. The research results have great significance both for theoretical study and industrial applications of fault detection and diagnosis for complex systems in the real world.
Combined with GrC, Graph Theory and SDG together, a new fault diagnosis method was presented in this paper, which has been successfully applied to the Tennessee-Eastman process (TEP).
The research mainly includes but not limited in the following sections:
(1) Granule-based SDG model was established and granule was applied to describe the elements in SDG, this is a new description method for SDG model.
(2) By introducing GrC, system hierarchical theory, and graph theory into SDG fault diagnosis method, a new hierarchical SDG granular graph model was presented, which not only keep the completeness of the SDG but also simplify the interconnect relation among the system elements. Furthermore, the model was applied to High Pressure Heater System and TEP. The simulation results showed the effectiveness of the proposed algorithm.
(3) Improving the existing Granular Matrix-based knowledge reduction algorithm by proposed node important-based and granlularity entropy-based knowledge reduction algorithm, which can help find the minimal attribute set and optimal diagnosis rule base.
(4) A similarity based researching and reasoning algorithm was proposed, which can obtain the most possible fault sources by computing and sorting the similarity. This method can improve resolution by effectively reducing or even avoiding conflict probability of reasoning results.
(5) By applying Fuzzy theory to the definition of the node state and tributary state, realizing the quantitative fuzzification of qualitative SDG model. Fuzzy set-based consistent path decision making algorithm was also proposed, which result in a fuzzy-SDG-based fault diagnosis method.
(6) Design and develop a real time fault predictive diagnosis system based on configuration software, which realize the simulation for TEP, and prove the efficiency of the proposed algorithm.
The innovations of this paper are as follows:
(1) Proposed a hierarchical SDG fault diagnosis model and established hierarchical SDG model for High Pressure Heater System and TEP.
(2) Proposed two knowledge reduction algorithms respectively based on node importance and granularity entropy;
(3) Proposed a research and reasoning algorithm based on similarity;
(4) Developed a real time predictive fault diagnosis method based on configuration software, which has been successfully applied to the TEP diagnosis.
引文
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