基于灰色关联分析的风机故障诊断  

Blower Fault Diagnosis Based on Grey Relational Analysis

作　　者：代星 赵元松 岳永威[2] 吴垚[3] DAI Xing;ZHAO Yuansong;YUE Yongwei;WU Yao(The 91054 Unit of PLA,Shanghai 200235,China;AVIC China Aero-Polytechnology Establishment,Beijing 100028,China;The 92602 Unit of PLA,Shanghai 201900,China)

机构地区：[1]91054部队 [2]中国航空综合技术研究所 [3]92602部队

出　　处：《机电设备》2018年第5期27-30,共4页Mechanical and Electrical Equipment

摘　　要：风机作为船舶工业领域的关键设备,对正常生产有很重要的作用。当前的诊断方法尚难以对风机实现整个故障状态空间上的实时状态监测和故障诊断,通过分析风机故障诊断方法的差异,提出结合风机典型故障信号源特征,利用风机征兆和故障之间的关系建立故障样本,通过灰色关联分析法建立风机状态数据与故障数据样本的联系,利用关联程度的大小达到有效识别风机故障的目的,试验表明该方法具备正确性和可行性,能够指导风机的故障诊断工作。As the key equipment in the shipbuilding industry,the fan plays a very important role in the normal production.The current diagnosis method is difficult to realize the real-time state detection and fault diagnosis of the whole fault state space of the fan.By analyzing the difference of fan fault diagnosis methods,combined with the typical fault signal source characteristics of fan,the fault samples are established by using the relationship between the fan and fault symptom,with grey correlation analysis method to establish the fan state data and fault connection,using association degree to achieve effective recognition of fan fault.Example results show that this method has validity and feasibility,which can guide the fan fault diagnosis.

关 键 词：船舶工业 风机 状态监测 故障诊断 故障样本 灰色关联分析 

分 类 号：U664.5[交通运输工程—船舶及航道工程]