利用随机共振的叶片裂纹微弱信息增强方法

被引：14

作者：

李宏坤

张晓雯

贺长波

徐福健

张学峰

机构：

[1] 大连理工大学机械工程学院

来源：

机械工程学报 | 2016年 / 52卷 / 01期

关键词：

离心式压缩机; 叶片裂纹; 信号滤波; 随机共振;

D O I：

暂无

中图分类号：

TH452 [离心式];

学科分类号：

摘要：

离心式压缩机叶片作为压缩机内最重要部件,长期承受周期性振动和流动诱使激励的作用。而叶片的故障将对压缩机的运行以及现场安全可靠性有严重的影响,因此如何有效地识别压缩机叶片裂纹早期故障显得尤为重要。由于叶片裂纹故障属于低频微弱故障,通常被调制到叶片通过频率处,但是故障频率难以识别,清晰度较低。首先在叶片通过频率处进行信号滤波,然后应用Woods-Saxon and Gaussian Potential随机共振模型对特征频率进行加强,从而得到叶片裂纹故障频率。通过在叶片裂纹附近安装压力脉动传感器,利用压力脉动信号对叶片裂纹信息进行监测。实现模拟叶片裂纹的信号测试,验证了WSG随机共振模型在叶片裂纹早期故障识别中的有效性以及可靠性。同时通过应变试验进行验证此方法的有效性。

引用

页码：94 / 101

页数：8

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