基于神经网络的船舶舵桨装置状态监测  

Condition Monitoring of Steering Propellers in Tugboat with Neural Network

作　　者：殷勇辉[1] 王伟华[1] 王成焘[1] 萧汉梁[2] 

机构地区：[1]上海交通大学机械与动力工程学院,上海200030 [2]武汉理工大学可靠性工程研究所,武汉430063

出　　处：《润滑与密封》2003年第4期71-74,共4页Lubrication Engineering

摘　　要：智能化诊断是现代设备诊断技术发展的重要趋势,通过对船舶舵桨装置实施了近三年的磨损微粒监测和油液分析跟踪监测,获得了光谱、铁谱和污染度等监测数据,提出了采用神经网络模型判断舵桨装置磨损程度和油液含水量情况,通过训练和学习,结果是可信的和准确的。The intelligent diagnosis technology is a tendency toward the machinery diagnosis technology. The steering propellers was condition-monitored over a period of three years through wear debris and oil analysis. Various sophisticated techniques such as ferrography, spectrometric are used. A new approach for the prediction of wear severity and water content by using neural network is presented. The model are trained by used lubricating oil experimental data, and results are proven to be reliable and accuracy.

关 键 词：船舶 舵桨装置 状态监测 磨损微粒监测 油液分析 智能化诊断 神经网络 含水量 

分 类 号：U672[交通运输工程—船舶及航道工程] TP183[交通运输工程—船舶与海洋工程]