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首页> 外文会议>ICMIT 2005: Control Systems and Robotics pt.1 >Bayesian network based on a fault tree and its application in diesel engine fault diagnosis
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Bayesian network based on a fault tree and its application in diesel engine fault diagnosis

机译：基于故障树的贝叶斯网络及其在柴油机故障诊断中的应用

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This paper discusses the faults diagnosis of diesel engine systems. This research aims at the optimization of the diagnosis results. Inspired by Bayesian Network (BN) possessing good performance in solving uncertainty problems, a new method was proposed for establishing a BN of diesel engine faults quickly, and diagnosing faults exactly. This method consisted of two stages,namely the establishment of a BN model, and a faults diagnosis of the diesel engine system using that BN mode. For the purpose of establishing the BN, a new algorithm, which can establish a BN quickly and easily, is presented. The Fault Tree (FT) diagnosis model of the diesel engine system was established first. Then it was transformed it into a BN by using our algorithm. Finally, the BN was used to diagnose the faults of a diesel engine system. Experimental results show that the diagnosis speed is increased and the accuracy is improved.
机译：本文讨论了柴油机系统的故障诊断。这项研究旨在优化诊断结果。受贝叶斯网络（BN）在解决不确定性问题方面具有良好性能的启发，提出了一种快速建立柴油机故障BN并准确诊断故障的新方法。该方法包括两个阶段，即建立BN模型和使用该BN模式对柴油机系统进行故障诊断。为了建立BN，提出了一种新的算法，可以快速，方便地建立BN。首先建立了柴油机系统的故障树（FT）诊断模型。然后使用我们的算法将其转换为BN。最后，BN被用于诊断柴油发动机系统的故障。实验结果表明，提高了诊断速度，提高了诊断准确率。

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