基于神经网络参数优化的舰船柴油机故障诊断  

Fault diagnosis of ship diesel engine based on neural network parameter optimization

作　　者：张坚实 ZHANG Jian-shi(School of Changchun Polytechnic,Changchun 130033,China)

机构地区：[1]长春职业技术学院信息学院,吉林长春130033

出　　处：《舰船科学技术》2021年第18期124-126,共3页Ship Science and Technology

摘　　要：柴油机是舰船的重要组成部分之一,与运行安全密切相关。当柴油机发生故障后,必须及时查明故障原因,采取相应的方法消除故障,使柴油机恢复正常工作,为舰船安全航行提供保障。舰船柴油机的运行可靠性直接关系到航行安全性,而各种故障是影响柴油机可靠性的主要因素,所以对故障进行准确诊断显得尤为必要。为提高诊断的准确性,可对神经网络加以合理运用,通过网络参数优化,能够使精度得到保障,并进一步缩短诊断时间,这对于舰船柴油机故障诊断效率和质量的提升意义重大。Diesel engines are one of the important components of ships,and are closely related to operational safety.When a diesel engine malfunctions,it is necessary to find out the cause of the malfunction in time,and take corresponding measures to eliminate the malfunction,so that the diesel engine can resume normal operation and provide a guarantee for the safe navigation of the ship.The operational reliability of ship diesel engines is directly related to the safety of navigation,and various faults are the main factors affecting the reliability of diesel engines,so it is particularly necessary to diagnose faults accurately.In order to improve the accuracy of diagnosis,the neural network can be used reasonably.Through the optimization of network parameters,the accuracy can be guaranteed and the diagnosis time can be further shortened.This is of great significance to the improvement of the efficiency and quality of marine diesel engine fault diagnosis.

关 键 词：柴油机 舰船 故障诊断 

分 类 号：U665[交通运输工程—船舶及航道工程]