针对船用二冲程低速柴油机运行状态监测，本文分析现有的柴油机状态监测方法，并指出现有方法的不足之处。提出基于AAKR模型的柴油机状态监测方法，同时阐述AAKR模型的原理。该方法具有无需故障数据、无需对模型进行训练与调参、高效快捷等优点。本文建立柴油机仿真模型，通过对柴油机模型进行模拟状态监测实验，证明基于AAKR模型的柴油机状态监测方法的有效性，最后讨论不同带宽的选择对模型性能的影响。该方法无需故障数据的特性使其具有更强的普适性，可广泛应用于船舶柴油机的在线状态监测和预警。
In view of the operational status monitoring of marine two-stroke low-speed diesel engines, this paper analyzes the existing diesel engine condition monitoring methods and points out the shortcomings of the existing methods. A diesel engine condition monitoring method based on AAKR model is proposed, and the principle of AAKR model is also expounded. The method has the advantages of no fault data, no need to train and adjust the model, and is efficient and fast. In this paper, the diesel engine simulation model is established. The simulation of the diesel engine model is carried out to verify the effectiveness of the diesel engine condition monitoring method based on the AAKR model. Finally, the influence of different bandwidth choices on model performance is discussed. The method does not require the characteristics of fault data to make it more universal, and can be widely used in online condition monitoring and early warning of marine diesel engines.
2021,43(2): 158-162 收稿日期：2019-11-15
DOI：10.3404/j.issn.1672-7649.2021.02.032
分类号：U664.121
作者简介：蒋佳炜(1992-),男,博士研究生。主要研究方向为智能故障诊断
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