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Comparison of dynamic bayesian network approaches for online diagnosis of aircraft system

Journal of Central South University 2016年第11期23卷 2926-2934页

作者：于劲松冯威唐荻音刘浩 School of Automation Science and Electrical Engineering Beihang University Collaborative Innovation Center of Advanced Aero-Engine Beihang University Unit 93 Army 95809 of PLA

The online diagnosis for aircraft system has always been a difficult problem. This is due to time evolution of system change, uncertainty of sensor measurements, and real-time requirement of diagnostic inference. To address this problem, two dynamic bayesian network(DBN) approaches are proposed. One approach prunes the DBN of system, and then uses particle filter(PF) for this pruned DBN(PDBN) to perform online diagnosis. The problem is that estimates from a PF tend to have high variance for small sample sets. Using large sample sets is computationally expensive. The other approach compiles the PDBN into a dynamic arithmetic circuit(DAC) using an offline procedure that is applied only once, and then uses this circuit to provide online diagnosis recursively. This approach leads to the most computational consumption in the offline procedure. The experimental results show that the DAC, compared with the PF for PDBN, not only provides more reliable online diagnosis, but also offers much faster inference.

关键词： online diagnosis dynamic bayesian network particle filter dynamic arithmetic circuit

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Prediction of visibility in the Arctic based on dynamic bayesian network analysis

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Acta Oceanologica Sinica 2022年第4期41卷 57-67页

作者： Shijun Zhao Yulong Shan Ismail Gultepe College of Meteorology and Oceanography National University of Defense TechnologyNanjing 211101China Cloud Physics and Severe Weather Research Environment and Climate Change CanadaToronto M4Y1M7Canada

With the accelerated warming of the world,the safety and use of Arctic passages is receiving more *** visibility in the Arctic has been a hot topic in recent years because of navigation risks and opening of ice-free northern *** weather prediction and statistical prediction are two methods for predicting *** microphysical parameterization schemes for visibility are so sophisticated,visibility prediction using numerical weather prediction models includes large *** the development of artificial intelligence,statistical prediction methods have received increasing *** this study,we constructed a statistical model with a physical basis,to predict visibility in the Arctic based on a dynamic bayesian network,and tested visibility prediction over a 1°×1°grid area averaged *** results show that the mean relative error of the predicted visibility from the dynamic bayesian network is approximately 14.6%compared with the inferred visibility from the artificial neural ***,dynamic bayesian network can predict visibility for only 3 ***,with an increase in predicted area and period,the uncertainty of the predicted visibility becomes *** the same time,the accuracy of the predicted visibility is positively correlated with the time period of the input evidence *** is concluded that using a dynamic bayesian network to predict visibility can be useful over Arctic regions for projected climatic changes.

关键词： Arctic visibility prediction artificial neural network dynamic bayesian network

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A reconfigurable dynamic bayesian network for digital twin modeling of structures with multiple damage modes

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Theoretical & Applied Mechanics Letters 2023年第4期13卷 251-260页

作者： Yumei Ye Qiang Yang Jingang Zhang Songhe Meng Jun Wang Xia Tang School of Mechanical Technology Wuxi Institute of TechnologyWuxi 214121China National Key Laboratory of Science and Technology for National Defence on Advanced Composites in Special Environments Harbin Institute of TechnologyHarbin 150001China Beijing Institute of Astronautical Systems Engineering Beijing 100076China

dynamic bayesian networks(DBNs)are commonly employed for structural digital twin *** present,most researches only consider single damage mode *** is not sufficient for a reusable spacecraft as various damage modes may occur during its service life.A reconfigurable DBN method is proposed in this *** structure of the DBN can be updated dynamically to describe the interactions between different *** common damages(fatigue and bolt loosening)for a spacecraft structure are considered in a numerical *** results show that the reconfigurable DBN can accurately predict the acceleration phenomenon of crack growth caused by bolt loosening while the DBN with time-invariant structure cannot,even with enough *** definition of interaction coefficients makes the reconfigurable DBN easy to track multiple damages and be extended to more complex *** method also has a good physical interpretability as the reconfiguration of DBN corresponds to a specific *** predictions do not require precise knowledge of reconfiguration conditions,making the method more practical.

关键词： dynamic bayesian network Reusable spacecraft Damage Reconfiguration

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dynamic bayesian network model for inflation risk warning

Dynamic Bayesian network model for inflation risk warning

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2009中国控制与决策会议

作者： Wang Shuangcheng~(1,2),Cheng Xinzhang~2,Leng Cuiping~1 1.School of mathematics and information,Shanghai Lixin University of Commerce,Shanghai 201620,China 2.Opening Economy & Trade Research Center,Shanghai Lixin University of Commerce,Shanghai 201620,China

＜正＞At present,the methods of risk warning emphasize static function dependency or dynamic propagation of time series,which results in a unconsistent combination of the static and dynamic ***,this paper puts forward a dynamic hierarchical naive bayesian network classifier for warning inflation *** an example is presented to explain the process of inflation risk warning and method of contribution analysis to risk rank *** model features universality and can be widely used in other risk warning domains.

关键词： inflation risk warning dynamic bayesian network classifier Markov chain

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Time-change Reliability Assessment and Analysis of Cryogenic Pneumatic Valve Based on dynamic bayesian network Theory

Time-change Reliability Assessment and Analysis of Cryogenic...

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作者： Yongtao Qin Le Sun Liping Tang Jianfang Wang The 165

In order to fully identify the root cause of cryogenic pneumatic valve failure in the process of liquid rocket engine test,and to analyze the dynamic time change of the process of cryogenic pneumatic valve reliability analysis,this paper first analyzes the failure factors of low temperature pneumatic valve in the test process of liquid rocket engine according to the human-machine environment system *** introducing the dynamic bayesian network theory,and by means of analyzing the time-change failure failure mode of cryogenic pneumatic valve,constructing the time-change reliability model of cryogenic pneumatic valve was constructed in the test process of liquid rocket engine,and the reliability growth technology of cryogenic pneumatic valve was researched by the optimal failure search ***,the validity and accuracy of this method are verified by the *** method can provide a method guide for quantitative analysis and improvement of the reliability of cryogenic pneumatic valve,and provide support for the accurate and objective evaluation and development of liquid rocket engine performance.

关键词： dynamic bayesian network Cryogenic pneumatic valves Reliability

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Situation Assessment for Beyond-Visual-Range Air Combat Situation Assessment Based on dynamic bayesian network 25th

Situation Assessment for Beyond-Visual-Range Air Combat Situ...

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第25届中国控制与决策会议

作者： Li Fu Jianbo Liu Feihu Chang Guanglei Meng Faculty of Aerospace Engineering Shenyang Aerospace University Academy of Automation Shenyang Aerospace University

ISBN: (纸本)9781467355339

Aiming at the characteristics of the process of beyond-visual-range air combat, a model for beyond-visual-range air combat of situation assessment is established. The model is based on dynamic bayesian network and makes threat events as input. And a simulation assessment for threats and advantages that aircraft faced in the process of two fighters beyond-visual-range combat is performed. The simulation results demonstrate that the model for BVR air combat assessment is consistent with the actual situation.

关键词： dynamic bayesian network Situation Assessment Beyond-Visual-Range Air Combat and Missile Attack

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Target Damage Rank Assessment Based on dynamic bayesian network

Target Damage Rank Assessment Based on Dynamic Bayesian Netw...

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2010 Chinese Control and Decision Conference

作者： Yanyan Huang~1,Hang Li~2,Weiwei Ji~1 1.School of Automation,Nanjing University of Science and Technology,Nanjing,210094 2.Training Lab of Naval Equipment Institute,Beijing,102308

Target damage rank assessment(TDR) is an important part of the direction decision-making for the CI system,and the fast and effective damage assessment for the target is the main basis for judging the necessity of continuous target attacking.A method of the target damage rank assessment based on the dynamic bayesian network(DBN) is used to evaluate the operational situation in this *** an example,the operational weapon equipment is analyzed by this method,and the results show the method feasible.

关键词： dynamic bayesian network Target Damage Rank Assessment Characteristic Parameter simulation

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A Noise Robust dynamic bayesian network Model for Speech Recognition

A Noise Robust Dynamic Bayesian Network Model for Speech Rec...

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2010 4th International Conference on Intelligent Information Technology Application (IITA2010)

作者： S. Ghasempour F. Sobhanmanesh R. Rohani A. Kazemi Department of Computer Science and Engineering Shiraz University Shiraz

ISBN: (纸本)9781424484669

In this paper we have investigated the role of dynamic bayesian network （DBN） in a speech recognition context. At first we compare it with HMM （both of them, implemented using the bayesian network Toolkit （BNT））, and then we show how various features of data can be captured with some states in DBN. Finally we propose a DBN model, suitable to be used in noisy environments. The model works well even in the presence of various noise types and SNR values. Results from implementation of model on Multi Modal Verification for Teleservices and Security applications （M2VTS） database indicate that DBN would utilize various features of data which results in a more powerful tool for modeling a complex system.

关键词： speech recognition, noise robustness bayesian network dynamic bayesian network

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Fault Prognosis for Data Incomplete Systems: A dynamic bayesian network Approach

Fault Prognosis for Data Incomplete Systems: A Dynamic Bayes...

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第24届中国控制与决策会议

作者： Zhu Jinlin, Zhang Zhengdao * Key Laboratory of Advanced Process Control for Light Industry, Ministry of Education, Jiangnan University, Wuxi 214122

For the cases that data samples are partially missing in control systems, analysis are given to determine the type of missing data mechanisms, then a dynamic bayesian network approach is used to model the general fault prognosis problem in control systems, after that we proposed the method of dynamic bayesian network to deal with real-time fault prognosis of nonlinear systems with missing data. Our approach is demonstrated on a benchmark continuous stirred tank reactor （CSTR） problem, with which we show the process of constructing the dynamic bayesian network model and use the model for the simulation of fault prognosis. Results show that though data samples are noisy and partially missing, combined with effective treatment of missing data, dynamic bayesian networks can efficiently predict the system failures.

关键词： Fault prognosis Data missing dynamic bayesian network

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A Maneuver-Prediction Method Based on dynamic bayesian network in Highway Scenarios

A Maneuver-Prediction Method Based on Dynamic Bayesian Netwo...

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第30届中国控制与决策会议

作者： Junxiang Li Xiaohui Li Bohan Jiang Qi Zhu College of Mechatronic Engineering and Automation National University of Defense Technology

The accurate maneuver prediction for dynamic vehicles can enhance driving safety in complex *** paper presents a maneuver prediction method for dynamic vehicles in highway scenarios. The method effectively combines multi-frame vehicle states, road structures and interactions among vehicles. With a novel extraction algorithm of environment feature, the method infers the probability of each driving maneuver by using a dynamic bayesian network. The experimental results demonstrate that our method can predict lane-change maneuvers at least 2 seconds before they occur in real environments with an accuracy of 84.9%.

关键词： Autonomous driving maneuver prediction feature extraction dynamic bayesian network

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