摘要
利用传统方法对工程船舶机械运行故障进行诊断时,存在诊断正确率、效率双低的情况。针对上述情况,研究一种基于振动信号的工程船舶机械运行故障诊断方法。该方法分为2个阶段,第1阶段为监测阶段,对船舶机械运行的振动信号进行检测并去噪,提取故障特征;第2阶段为诊断阶段,利用K最近邻算法对第1阶段提取出的故障特征进行识别,确定故障类型。结果表明:与文献[1–3]诊断方法相比,本诊断方法的正确率和效率都更高,平均综合正确率达到96.7%,故障诊断时间仅需3.5 min。
When using traditional methods to diagnose the operation faults of construction ship machinery, the diagnostic accuracy and efficiency are low. In view of the above situation, a fault diagnosis method based on vibration signal magnitude for engineering machinery operation is studied. The method is divided into two stages: the first stage is the monitoring stage, which detects and denoises the vibration signals of ship machinery, and extracts the fault features;the second stage is the diagnosis stage, which uses the K-nearest neighbor algorithm to identify the fault features extracted in the first stage and determine the fault types. The results show that the diagnostic accuracy and efficiency of this method are higher than those of literature (1 – 3)The average comprehensive accuracy rate is 96.7%, and the time of fault diagnosis is only 3.5 minutes.
作者
史洪松
SHI Hong-song(Jiangxi University of Engineering, Xinyu 338000, China)
出处
《舰船科学技术》
北大核心
2018年第12X期172-174,共3页
Ship Science and Technology
关键词
工程船舶
机械故障
诊断方法
振动信号
engineering ship
mechanical fault
diagnosis method
vibration signal
作者简介
史洪松(1983–),男,硕士,讲师,研究方向为机械设计制造及其自动化。
