BP神经网络技术在船舶起锚机离合器故障检测中的应用  

Application of BP neural network technology in fault detection of marine windlass clutch

作　　者：耿瑞焕 周书强 GENG Rui-huan;ZHOU Shu-qiang(Hebi Institute of Engineering and Technology,Henan Polytechnic University,Hebi 458030,China)

机构地区：[1]河南理工大学鹤壁工程技术学院,河南鹤壁458030

出　　处：《舰船科学技术》2022年第23期165-168,共4页Ship Science and Technology

摘　　要：当船舶起锚机离合器出现故障时,需要采用有效的故障诊断技术判断其故障类型以及故障元器件。BP神经网络是一种具有自主学习能力的记忆网络,可以实现线性和非线性函数之间的映射,并以此为基础对网络中存储的记忆进行训练,从而提高起锚机离合器的精检测。本文从BP神经网络技术入手,论述其在船舶起锚机离合器故障信号检测的应用,为故障检测提供实用操作价值。When the clutch fails, effective fault diagnosis technology is needed to judge its fault type and fault components. BP neural network is a kind of memory network with self-learning ability, which can realize the mapping between linear and nonlinear functions, and train the memory stored in the network on this basis, so as to improve the precision detection of ship windlass clutch. Therefore, this paper starts with the BP neural network technology and discusses its rapid application in the fault signal of the marine windlass clutch, which will bring practical operation value in the future fault detection.

关 键 词：BP神经网络 离合器 故障 

分 类 号：U667.5[交通运输工程—船舶及航道工程]