Intelligent state evaluation method of marine engine room system

Hui Cao, Yifan Liu, Yiru Wang, Ran Li
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Abstract

Based on system state classification and recognition, an intelligent state evaluation method was proposed for the intelligent maintenance and management in marine engine room. The method can be adopted to realize the condition-based maintenance and improve the efficiency and safety of ship operation. First, the radial basis function neural network was used to establish the state identification model of the marine engine room system to realize the state classification and identification of the system; Second, the recognized state was evaluated comprehensively by using the fuzzy analytical hierarchy process method; Finally, the validity of the results of the state identification and the fuzzy comprehensive evaluation was verified based on an actual ship system data. With the support of the system state data, the evaluation result shows a good match with the actual system state and has a high degree of credibility. On the premise of convenient data collection, the proposed method can further conduct a large-scale system state evaluation for multiple marine engine room systems. The process of the method proposed provides a new idea for the application of intelligent technology in the field of ships.
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船舶机舱系统状态智能评估方法
提出了一种基于系统状态分类与识别的船舶机舱智能维修管理智能状态评估方法。该方法可实现船舶状态维修,提高船舶运行效率和安全性。首先,利用径向基函数神经网络建立船舶机舱系统的状态识别模型,实现系统的状态分类与识别;其次,采用模糊层次分析法对识别状态进行综合评价;最后,基于实际船舶系统数据,验证了状态识别和模糊综合评价结果的有效性。在系统状态数据的支持下,评价结果与实际系统状态吻合较好,具有较高的可信度。在数据采集方便的前提下,该方法可以进一步对多个船舶机舱系统进行大规模的系统状态评估。该方法的提出过程为智能技术在船舶领域的应用提供了新的思路。
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