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Remote intelligent expert system for operation state of marine gas turbine engine

机译:船舶燃气轮机运行状态远程智能专家系统

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A distributed networked remote fault prognostic and diagnostic expert system for marine gas turbine is introduced which can realize cross-regional, multi-expert involved in collaborative decision-making mechanism. The expert system includes four layers namely the field data collection layer, the local condition monitoring layer, the network communication layer and the long-distance expert supports layer. The expert system uses artificial neural network to carry out real-time fault prognostic analysis for the operational status of key equipment to discover hidden or impending equipment faults, so as to effectively avoid the occurrence of the “lack of maintenance” and “excess maintenance”. The integration of fault diagnosis mechanism based on rough set and artificial neural network is used, which effectively solve the problems of typical fault diagnosis for a long time and a high false alarm rate. Finally, this paper describes the main characteristics and application of expert system to the remote fault prognosis and diagnosis of a gas turbine fuel system as an example for testing its capabilities and main features.
机译:分布式联网远程故障船用燃气轮机引入可实现参与协作决策机制交叉区域,多专家预测和诊断专家系统。所述专家系统包括四个层即现场数据采集层,所述本地状态监测层,网络通信层和长途专家支撑层。该专家系统采用人工神经网络进行实时故障预测分析的关键设备的运行状况,以发现隐藏的或即将发生的设备故障,从而有效地避免了“缺乏维修发生”和“过剩维修” 。基于粗糙集和人工神经网络的故障诊断机制的整合使用,从而有效地解决了典型故障诊断的问题很长一段时间,高误报率。最后,本文描述了用于测试其功能和主要特征的示例燃气涡轮机燃料系统的远程故障预后和诊断的主要特点和专家系统的应用。

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