An Intelligent Fault Diagnosis Method Of Marine Seawater Cooling System Based On SOM Neural Network

Lei Guo, Jun-dong Zhang, Y. Zou, Guochang Qi, Keyu Guo, Yanghui Tan
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引用次数: 1

Abstract

To solve marine seawater cooling system's faults better, the fault pattern recognition model of marine seawater cooling system is established. Firstly, the structure and typical faults of seawater cooling system are analyzed, and fault modes are divided. Then the LMS learning rules are selected as the learning algorithm of SOM neural network, and the fault sample set of marine seawater cooling system is constructed by using the relevant state parameters collected from the real ship to train the SOM neural network. The training results show that the model has satisfactory clustering effect. Finally, the fault identification model is verified by the real ship test data, and the results show that the model can accurately diagnose the fault mode of the marine seawater cooling system.
基于SOM神经网络的船用海水冷却系统故障智能诊断方法
为了更好地解决海洋海水冷却系统的故障,建立了海洋海水冷却系统故障模式识别模型。首先,分析了海水冷却系统的结构和典型故障,并划分了故障模式。然后选择LMS学习规则作为SOM神经网络的学习算法,利用从实际船舶上采集到的相关状态参数构建海洋海水冷却系统故障样本集,对SOM神经网络进行训练。训练结果表明,该模型具有满意的聚类效果。最后,通过实船试验数据对故障识别模型进行了验证,结果表明该模型能够准确诊断船用海水冷却系统的故障模式。
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