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Fault Diagnosis of Diesel Engine Lubrication System Based on Bayesian Network

机译:基于贝叶斯网络的柴油机润滑系统故障诊断。

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The existing fault diagnosis techniques are mostly manual inspections. In recent years, support vector machines have been used for fault diagnosis. However, this method is a classification method, which can only judge whether the fault is faulty and cannot diagnose the specific fault cause. In order to achieve accurate positioning of diesel engine lubrication system fault diagnosis, avoid more serious faults of diesel engine. Proposes a fault diagnosis method for Bayesian networks. Taking a diesel engine as the research object, the fault analysis of the lubrication system is carried out to establish a fault tree, and then the Bayesian network diagnosis model of the lubrication system is established by transforming the fault tree into the Bayesian network. Finally, the model is verified by an example. The actual case verification shows that the Bayesian network can be used for fault diagnosis of the oil system, which can realize the fast and accurate positioning of the fault cause. This method can be used for fault diagnosis of marine diesel engines.
机译:现有的故障诊断技术主要是人工检查。近年来,支持向量机已用于故障诊断。但是,这种方法是分类方法,只能判断故障是否有故障,无法诊断出具体的故障原因。为了实现柴油机润滑系统精确定位的故障诊断,避免柴油机出现更严重的故障。提出了贝叶斯网络的故障诊断方法。以柴油机为研究对象,对润滑系统进行故障分析,建立故障树,然后将故障树转化为贝叶斯网络,建立润滑系统的贝叶斯网络诊断模型。最后,通过实例验证了该模型。实际案例验证表明,贝叶斯网络可用于油系统的故障诊断,可实现故障原因的快速,准确定位。该方法可用于船用柴油机的故障诊断。

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