The Experts below are selected from a list of 87 Experts worldwide ranked by ideXlab platform
Xu We - One of the best experts on this subject based on the ideXlab platform.
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method for fault diagnosis of bayesian network inference in marine Lube oil System
Journal of Sichuan Ordnance, 2015Co-Authors: Xu WeAbstract:Aiming at dealing with the fault status of Lube System in power plant,common faults of the tree structure in the Lube System was established,meanwhile,the Bayesian network model for fault state reasoning was constructed and the procedure of Bayesian reasoning was analyzed deeply in typical state of Lube System,through which a new method was provided to the fast fault diagnosis.
Fan Ming Zeng - One of the best experts on this subject based on the ideXlab platform.
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applied information technology in fault diagnosis of marine Lube oil System based on bayesian network inference
Applied Mechanics and Materials, 2014Co-Authors: Wei Xu, Gang Cheng, Yu Tao Chen, Fan Ming ZengAbstract:Aiming at the fault status of Lube System in power plant, common faults of the tree stucture in the Lube System is established, meanwhile, the bayesian network model for fault state reasoning is constructed and the procedure of bayesian reasoning is analysised deeply in typical state of Lube System,a new method is provided to the fault diagnosis fastly.
Wei Xu - One of the best experts on this subject based on the ideXlab platform.
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applied information technology in fault diagnosis of marine Lube oil System based on bayesian network inference
Applied Mechanics and Materials, 2014Co-Authors: Wei Xu, Gang Cheng, Yu Tao Chen, Fan Ming ZengAbstract:Aiming at the fault status of Lube System in power plant, common faults of the tree stucture in the Lube System is established, meanwhile, the bayesian network model for fault state reasoning is constructed and the procedure of bayesian reasoning is analysised deeply in typical state of Lube System,a new method is provided to the fault diagnosis fastly.
Shuying Li - One of the best experts on this subject based on the ideXlab platform.
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Modeling and diagnosis for gas turbine Lube System
Proceeding of the 11th World Congress on Intelligent Control and Automation, 2014Co-Authors: Henan Zhao, Ningbo Zhao, Shuying LiAbstract:Lube System is one important auxiliary System of the gas turbine, and its operation stability directly related to the security and reliability of gas turbine. Typical faults and its mechanism are analyzed and the mathematic model of Lube System is established in MATLAB/Simulink simulation environment, and the variable characteristic parameters of 4 typical faults which are cooler failure, filter block, flow loss due to leakage and damage of Lube pump are obtained. Base on the analyzing of signed directed graph (SDG) modeling mythology, the SDG qualitative model of Lube System is presented. The states of nodes and branches of Lube System SDG Model are quantified by the typical faults simulation results, and the fault diagnostic rule database of Lube System are formed. Finally, simulation experiment shows that the SDG fault diagnostic method is feasibility and effective.
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A study on fault diagnostic method for the Lube oil System of gas turbine based on rough sets theory
2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), 2014Co-Authors: Shuang Yi, Ningbo Zhao, Shuying Li, Zhiqiang XuAbstract:Lube oil System is very important to ensure the normal and stable operation of gas turbine. The faults of Lube oil System would affect the performance of the whole gas turbine unit, and even lead to shut down. Through analyzing the operating characteristics and typical faults of Lube oil System, this paper found that Lube oil System possesses a nature of the diverse fault information, and the vague and uncertain relationship between fault causes and fault symptoms. According to lubrication oil System characteristics, this paper proposed a fault diagnostic method for Lube System based on rough sets theory. Rough sets theory can get the important parameters which characterizes the equipment operating status from complex multivariate information. This theory can extract fault diagnostic rules by making use of reduction algorithm. The results show that the method can improve the accuracy of diagnosis.
Zhiqiang Xu - One of the best experts on this subject based on the ideXlab platform.
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A study on fault diagnostic method for the Lube oil System of gas turbine based on rough sets theory
2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), 2014Co-Authors: Shuang Yi, Ningbo Zhao, Shuying Li, Zhiqiang XuAbstract:Lube oil System is very important to ensure the normal and stable operation of gas turbine. The faults of Lube oil System would affect the performance of the whole gas turbine unit, and even lead to shut down. Through analyzing the operating characteristics and typical faults of Lube oil System, this paper found that Lube oil System possesses a nature of the diverse fault information, and the vague and uncertain relationship between fault causes and fault symptoms. According to lubrication oil System characteristics, this paper proposed a fault diagnostic method for Lube System based on rough sets theory. Rough sets theory can get the important parameters which characterizes the equipment operating status from complex multivariate information. This theory can extract fault diagnostic rules by making use of reduction algorithm. The results show that the method can improve the accuracy of diagnosis.
