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Transformer Fault Analysis Based on Bayesian Networks and importance measures

Journal of Shanghai Jiaotong university(Science) 2015年第3期20卷 353-357页

作者：任方宇司书宾蔡志强张帅 School of Mechantronics Northwestern Polytechnical University

Complex environment stresses bring many uncertainties to transformer fault. The Bayesian network(BN) can represent prior knowledge in the form of probability which makes it an effective tool to deal with the uncertain problems. This paper established a BN model for the transformer fault diagnosis with practical operation dataset and expert knowledge. Then importance measures are introduced to indentify the key attributes which affect the results of transformer diagnosis most. Moreover, a strategy was proposed to reduce the number of attribute in transformer fault detection and the resource cost was saved. At last, a diagnosis case of practical transformer was implemented to verify the effectiveness of this method.

关键词： transformer fault diagnosis Bayesian network(BN) importance measures

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Fuzzy fault tree analysis of oil and gas leakage in subsea production systems

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Journal of Ocean Engineering and Science 2018年第1期3卷 38-48页

作者： A.S.Cheliyan S.K.Bhattacharyya Department of Ocean Engineering Indian Institute of Technology MadrasIndia

This paper presents a probabilistic failure analysis of leakage of the oil and gas in a subsea production system using fault tree analysis(FTA).A fault tree was constructed by considering four major areas where the leakages can be *** are:gas and oil wells,pipelines,key facilities and third party *** FTA requires precise values for the probability of failure of the basic ***,since the failure data are uncertain,a fuzzy approach to these data is taken which leads to the so-called fuzzy fault tree analysis(FFTA),a method that employs expert elicitation and fuzzy set theories to calculate the failure probabilities of the intermediate events and the top event through identification of the minimal cut sets of the fault tree.A number of importance measures for minimal cut sets and the basic events have been obtained which helps to identify the nature of dependence of the top event on the basic events and thereby can identify the weakest links that may cause leakage in the subsea production system.

关键词： Subsea production system Fuzzy fault tree analysis Failure probability importance measures

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Terrain Simplification Research in Augmented Scene Modeling

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Journal of China University of Geosciences 2001年第4期12卷 351-355页

作者： Ming Delie You Kefei Tian Jinwen Liu Jian State Key Laboratory for Image Processing and Intelligent Control, Institute for Pattern Recognition and Artificial Intelligence , Huazhong University of Science and Technology , Wuhan 430074 Wang Guangju State Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 Faculty of Information Engineering China University of Geosciences Wuhan 430074

Augmented reality is the merging of synthetic sensory information into a user's perception of a real environment. As one of the most important tasks in augmented scene modeling, terrain simplification research has gained more and more attention. In this paper, we mainly focus on point selection problem in terrain simplification using triangulated irregular network. Based on the analysis and comparison of traditional importance measures for each input point, we put forward a new importance measure based on local entropy. The results demonstrate that the local entropy criterion has a better performance than any traditional methods. In addition, it can effectively conquer the 'short-sight' problem associated with the traditional methods.

关键词： augmented reality scene modeling terrain simplification triangulated irregular network importance measures local entropy.

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