船舶柴油机润滑系统智能监测与故障预警技术研究

Research on Intelligent Monitoring and Fault Early Warning Technology for Marine Diesel Engine Lubrication Systems

摘要

本章阐述了船舶柴油机润滑系统智能监测及故障预警技术研究思路，在传感器方面介绍了介电常数、粘度、磨损颗粒等原理的在线监测传感器设计以及湿式和干式油底壳系统的安装方案，重点介绍了一种融合趋势相似性与欧式距离改进的灰色关联算法以提高滤清器堵塞、冷却器积垢等典型故障诊断准确率，并通过实船案例验证该技术体系能够有效实现异常磨损早期识别和精确定位，为船舶柴油机从定期维修向视情维护转变提供了技术支持。

Abstract

This chapter elaborates on the research ideas of intelligent monitoring and fault warning technology for marine diesel engine lubrication systems. In terms of sensors, it introduces the design of online monitoring sensors based on principles such as dielectric constant, viscosity, and wear particles, as well as the installation schemes of wet and dry oil pan systems. It focuses on a grey correlation algorithm that integrates trend similarity and Euclidean distance improvement to improve the accuracy of typical fault diagnosis such as filter blockage and cooler fouling. Through real ship cases, it is verified that this technology system can effectively achieve early identification and precise positioning of abnormal wear, providing technical support for the transformation of marine diesel engines from regular maintenance to on-demand maintenance.

关键词

船舶柴油机 / 润滑系统 / 智能监测 / 故障预警

Key words

marine diesel engine / Lubrication system / Intelligent monitoring / Fault warning

参考文献

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[2] 任东平. 船舶柴油机润滑系统故障诊断研究[D]. 大连海事大学, 2020.

[3] 牛新朋, 张文权, 温金羽, 孟雪锋, 张京辉, 魏铭扬. 某3 L柴油机润滑系统优化提升研究[J]. 拖拉机与农用运输车, 2025, 52 (02): 50-53.