船用柴油机处于复杂的工作环境中易引发运行故障,为加强对柴油机运行数据的监控,跟踪运行数据预测柴油机运行状态,有必要建立起预测精度高的网络诊断模型。运用神经网络算法迭代处理运行数据,提取有价值的特征值,对柴油机运行状态精准预测。本文论述了船用柴油机运行数据优化的实施要点,加强对柴油机燃油系统运行数据的优化,在此基础上针对燃油系统运行构建神经网络模型预测运行数据,判断柴油机故障类型,为及时排除故障提供依据。
Marine diesel engines are prone to operating failures in a complex working environment. In order to strengthen the monitoring of diesel engine operating data and track the operating data to predict the operating state of the diesel engine, it is necessary to establish a network diagnostic model with high prediction accuracy and use neural network algorithms to iteratively process the operating data, extract valuable eigenvalues, and accurately predict the operating state of the diesel engine. This paper discusses the main points of the implementation of marine diesel engine operation data optimization, strengthens the optimization of diesel engine fuel system operation data, and builds a neural network model for the fuel system operation to predict the operation data, determine the type of diesel engine failure, and provide a basis for timely troubleshooting.
2022,44(11): 136-139 收稿日期:2022-02-12
DOI:10.3404/j.issn.1672-7649.2022.11.028
分类号:U667.65
作者简介:任志伟(1986-),男,硕士,讲师,主要从事数据挖掘、智能优化算法及应用研究
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