水下推进器电流转速信号的模糊聚类故障检测方法研究  

FCM-Based Fault Detection Method of Current and Speed Signals of Underwater Thruster

作　　者：张文霞 袁健 ZHANG Wenxia;YUAN Jian(Department of Mechanical and Electrical Engineering,Qingdao Institute of Techology,Qingdao 266300,Shandong,China;Institute of Oceanographic Instrumentation,Qilu University of Technology(Shandong Academy of Sciences),Shandong Provincial Key Laboratory of Ocean Environment Monitoring Technology,National Engineering and Technological Research Center of Marine Monitoring Equipment,Qingdao 266100,Shandong,China)

机构地区：[1]青岛工学院机电工程学院,山东青岛266300 [2]齐鲁工业大学(山东省科学院)海洋仪器仪表研究所,山东青岛266100

出　　处：《汕头大学学报（自然科学版）》2023年第4期33-43,共11页Journal of Shantou University：Natural Science Edition

基　　金：自然资源部重点实验室基金资助项目(2021klootA10)。

摘　　要：为解决水下推进器在异物缠绕情形下故障诊断方法仅使用单一信号而无法综合利用多传感器相关性信息等问题,提出一种基于电流、转速信号相关分析与模糊C均值聚类相结合的水下推进器故障诊断方法.首先对采集到的水下推进器在不同状态下的电流、转速信号进行归一化操作;其次计算归一化后的电流、转速信号的相关度并组成相关度矩阵;最后以相关度矩阵作为特征使用数据聚类方法进行诊断.为验证该方法的有效性,使用推进器缠绕情形下故障数据对所提方法进行了验证.结果表明,相比仅使用单一信号的故障诊断方法,该方法能充分提取水下推进器多传感器相关度信息,特征提取更充分,有效提高了水下推进器故障诊断正确率.The fault diagnosis with a single sensor cannot comprehensively use the multi-sensor correlation information of underwater thruster.In order to solve the problem that in the case of entanglement,a kind of fault diagnosis method of underwater thruster based on the combination of current and rotational speed signal correlation analysis and support vector machine is proposed.Firstly,the collected current and speed signals of underwater thrusters under different states are normalized.Secondly,the correlation of normalized current and speed signals is calculated and the correlation matrix is formed.Finally,a kind of fuzzy C-means clustering method is used to diagnose with correlation matrix.To verify the effectiveness of the proposed method,the fault data in the case of propeller winding is used to verify the proposed method.The results show that compared with the fault diagnosis method using only one signal,the proposed method can fully extract the multi-sensor correlation information of underwater thrusters,and the feature extraction is more sufficient,effectively improving the accuracy of underwater thruster fault diagnosis.

关 键 词：水下推进器 异物缠绕 故障检测 相关分析 模糊C均值聚类 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]