基于神经网络和红外线成像技术的船用柴油机故障诊断方法研究

Research on fault diagnosis method of marine diesel engine based on neural network and infrared imaging technology

柴油发动机是通用船舶广泛使用的动力装置,在复杂恶劣的海上环境中,较易发生故障,传统检测方法主要依靠经验,故障定位较为耗时,其时效性差,需要进行改进。随着计算科学的发展,智能故障定位方法逐渐应用至船用柴油机故障定位系统中,如神经网络﹑模糊算法及大数据分析等。本文分析了船舶柴油机各功能部件,利用红外线对故障部件进行成像检测,设计了基于神经网络的柴油机故障诊断方法,最后对设计模型进行仿真分析。

WDiesel engine has been widely used transmitter power plant general ship, in complex sea environment, the transaction fails, the traditional detection method mainly depends on the experience, the fault location is more time consuming, the timeliness, need to be improved. With the development of computational science, intelligent fault location method is gradually applied to marine diesel engine fault location system, such as neural network, fuzzy algorithm and big data analysis. This paper analyses the function of marine diesel engine parts, imaging detection of fault components by using infrared,the final design of the neural network fault diagnosis method for diesel engine based on the simulation analysis.