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STUDY OF HYDROPOWER UNITS FAULT DIAGNOSIS BASED ON BAYESIAN NETWORK NOISY OR MODEL

机译:基于贝叶斯网络噪声或模型的水电单位故障诊断研究

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For the characteristics of complicated system structure and quantities of uncertain factors in hydropower units fault diagnosis, Bayesian network is introduced into the diagnosing analysis, a fault diagnosis system of hydropower units is built based on Bayesian network. Noisy Or model is introduced into Bayesian network system for overcoming the shortcomings of Bayesian network like considerable numbers of probabilities and difficulty in determining the probabilities. In this article, the network is constructed by applying experts' knowledge in determining the probability of each node and taking the characteristic nodes as binary nodes. Then the influence of random combinations of multiple nodes on the outcome is calculated to determine the possibility of occurrence of a certain fault. The simulation indicates that the number of conditional probabilities was needed by using the model in this paper decreases from 2~n to 2~n; it reduces the demand for data largely and raises the speed and efficiency of hydropower units' fault diagnosis.
机译:对于复杂系统结构的特点和水电单位故障诊断中不确定因素的数量,贝叶斯网络被引入诊断分析中,基于贝叶斯网络建立了水电单位故障诊断系统。嘈杂或模型被引入贝叶斯网络系统,以克服贝叶斯网络的缺点,如相当多的概率和确定概率的难度。在本文中,通过在确定每个节点的概率并将特征节点作为二进制节点进行特征节点来构造网络来构建网络。然后,计算多个节点对结果的随机组合的影响,以确定发生某个故障的可能性。模拟表明,通过在本文中使用模型需要的是,从2〜n到2〜n下降,需要有条件概率的数量;它在很大程度上降低了对数据的需求,提高了水电单位故障诊断的速度和效率。

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