增强稀疏分解及其在叶片振动参数识别中的应用

doi:10.3901/JME.2019.19.019

机械工程学报 ›› 2019, Vol. 55 ›› Issue (19): 19-27.doi: 10.3901/JME.2019.19.019

• 特邀专栏：高端透平机械动力学 • 上一篇

增强稀疏分解及其在叶片振动参数识别中的应用

吴淑明¹, 胡海峰², 赵志斌¹, 杨志勃¹, 杨来浩¹, 田绍华¹, 陈雪峰¹

1. 西安交通大学机械制造系统工程国家重点实验室西安 710049;
2. 国防科技大学装备综合保障技术重点实验室长沙 410073

收稿日期:2018-09-18 修回日期:2019-06-08 发布日期:2020-01-07
通讯作者: 陈雪峰(通信作者),男,1975年出生,教授,博士研究生导师。主要研究方向为航空发动机故障诊断与健康管理。E-mail:chenxf@mail.xjtu.edu.cn
作者简介:吴淑明,女,1993年出生,博士研究生。主要研究方向为叶端定时及欠采样信号处理。E-mail:wushuming@stu.xjtu.edu.cn
基金资助:
国家重点基础研究发展计划资助项目（973计划，2015CB057400）。

Enhancing Sparse Decomposition Based Blade Vibration Parameter Identification

WU Shuming¹, HU Haifeng², ZHAO Zhibin¹, YANG Zhibo¹, YANG Laihao¹, TIAN Shaohua¹, CHEN Xuefeng¹

1. State Key Laboratory for Manufacturing and System Engineering, Xi'an Jiaotong University, Xi'an 710049;
2. Laboratory of Science and Technology on Integrated Logistics Support, National University of Defense Technology, Changsha 410073

Received:2018-09-18 Revised:2019-06-08 Published:2020-01-07

摘要/Abstract

摘要： 叶端定时是发动机叶片监测有效手段，相比于传统的应变片测量方式，叶端定时不仅可以同时监测所有叶片的振动状态，而且不会对叶片本身的振动造成影响。但是叶端定时采样数据存在高度欠采样的特点，针对该问题，提出基于增强稀疏分解(Enhancing sparse decomposition,ESD)的叶片振动参数辨识技术。稀疏分解是一种在冗余字典中对信号进行分解，通过求解优化问题得到信号在冗余字典下最稀疏解的信号处理方法。增强稀疏分解相比于传统的基追踪算法，可以得到更为稀疏的解。在建立了增强稀疏优化模型后采用原对偶内点法对优化问题进行求解，从而实现信号特征参数的有效辨识。将提出的基于增强稀疏分解的叶片振动参数辨识技术应用于不同类型的仿真数据和转子叶片试验台参数辨识，并与传统的MUSIC算法和最小二乘拟合相对比，提出的算法可以有效避免频谱混叠和泄露现象，并滤除其他频率成分的干扰，得到更清晰的谱图。

关键词: 叶端定时, 增强稀疏分解, 欠采样, 参数辨识

Abstract: Blade tip timing is an engine blade monitoring method proposed in recent years, compared with the traditional strain gauge measurement method, it can not only simultaneously monitor the vibration state of all blades, but also will not affect the vibration condition of blades. However, due to the high undersampling characteristics of blade tip timing data, a blade parameter identification technology is proposed based on enhancing sparse decomposition. Sparse decomposition is a signal processing method that decomposes the signal into a sparse solution via a redundant dictionary. Enhancing sparse decomposition improves the traditional basic pursuit whose solution is not sparse enough, and the enhancing sparse decomposition method can effectively reduce the sampling rate. After the enhancing sparse optimization model is established, the original dual intra-point method is used to solve the optimization problem. The proposed blade parameter identification technology based on enhancing sparse decomposition is applied to different types of simulation data and rotor blade test rig to identify blades' parameter, the effectiveness of the algorithm has been verified.

Key words: blade tip timing, enhancing sparse decomposition, undersampling, parameter identification

中图分类号:

TH17

吴淑明, 胡海峰, 赵志斌, 杨志勃, 杨来浩, 田绍华, 陈雪峰. 增强稀疏分解及其在叶片振动参数识别中的应用[J]. 机械工程学报, 2019, 55(19): 19-27.

WU Shuming, HU Haifeng, ZHAO Zhibin, YANG Zhibo, YANG Laihao, TIAN Shaohua, CHEN Xuefeng. Enhancing Sparse Decomposition Based Blade Vibration Parameter Identification[J]. Journal of Mechanical Engineering, 2019, 55(19): 19-27.

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增强稀疏分解及其在叶片振动参数识别中的应用

Enhancing Sparse Decomposition Based Blade Vibration Parameter Identification

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