基于小波分析的油田机械传动装置振动信号识别方法  

A Method for Vibration Signal Identification of the Oilfield's Mechanical Gear Based on Wavelet Analysis

作　　者：赵磊 ZHAO Lei(Liaohe Oilfield Material Company,Panjin,Liaoning Province,124010 China)

机构地区：[1]辽河油田物资公司,辽宁盘锦124010

出　　处：《科技资讯》2023年第5期55-58,共4页Science & Technology Information

摘　　要：为提高油田机械设备运行的稳定性与高效性,分析传动装置的运行特性,该研究设计了一种基于小波分析的油田传动装置振动信号识别方法。应用小波分析方法采集机械传动装置的振动信号,为振动信号的识别提供数据基础。然后对采集到的振动信号进行卷积预处理,根据Hilbert变换、小波变换原理,从振动信号的时域特征、频域特征以及时频特征等方面出发,识别传动装置的振动信号。实验结果显示:经过小波分析后的3组振动信号频率均变得更加简洁,保留的关键频率特征为85.11 Hz,与实际传动频率85.399 Hz非常接近,表明该文方法通过将复杂的信号简化,能够有效地识别装置振动的振动信号特征,便于对油田机械传动装置的运行状态进行判断。In order to improve the stability and efficiency of oilfield's mechanical equipment operation and analyze the running characteristics of the gear,a method of vibration signal identification of the oilfield's mechanical gear based on wavelet analysis is designed in this study.It uses the wavelet analysis method to collect the vibration signal of the mechanical gear and provides the data basis for the identification of vibration signals,then performs convolution pre-processing of the collected vibration signal,and according to the principle of Hilbert transform and wavelet transform,identifies the vibration signal of the gear from the time-domain characteristics,frequency-domain characteristics and time-frequency characteristics of vibration signals and other aspects.The experimental results show that the frequencies of the three groups of vibration signals are all more concise after wavelet analysis,the key frequency characteristic retained is 85.11 Hz,which is very close to the actual transmission frequency of 85.399 Hz,indicating by simplifying the complex signals,the method in this paper can effectively identify the characteristics of the vibration signal of the device vibration,and is convenient to judge the running state of the oilfield's mechanical gear.

关 键 词：小波分析 智能化油田 机械传动装置 振动信号识别 传动信号 支持向量机 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置]