材料工程与机械制造

基于机匣应变信号的航空发动机转静碰摩部位识别

  • 于明月 ,
  • 陈果 ,
  • 刘永泉 ,
  • 姜广义 ,
  • 李成刚 ,
  • 冯国全 ,
  • 王德友
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  • 1. 南京航空航天大学民航学院, 江苏 南京 210016;
    2. 中航工业沈阳发动机设计研究所, 辽宁 沈阳 110015
于明月 女, 博士研究生。主要研究方向: 信号处理, 微弱信号检测, 故障诊断。 E-mail: yumingyue211@163.com;陈果 男, 博士, 教授, 博士生导师。主要研究方向: 航空发动机智能诊断及专家系统, 航空发动机整机振动与转子动力学。 Tel: 025-84891850 E-mail: cgzyx@263.net;刘永泉 男, 博士, 研究员。主要研究方向: 航空发动机, 结构强度与振动;姜广义 男, 硕士, 高级工程师。主要研究方向: 航空发动机, 转子动力学;李成刚 男, 硕士, 研究员。主要研究方向: 航空发动机, 振动测试与诊断。 E-mail: lichenggang606@163.com;冯国全 男, 博士, 研究员。主要研究方向: 转子动力学, 航空发动机整机振动分析。 E-mail: feng2004606@163.com;王德友 男, 博士, 研究员。主要研究方向: 转子动力学, 航空发动机, 振动测试与诊断。 E-mail: saeriem@mail.sy.ln.cn

收稿日期: 2012-05-29

  修回日期: 2013-01-24

  网络出版日期: 2013-02-19

基金资助

国家自然科学基金(61179057);国家安全重大基础研究项目(613139)

Aero-engine Rotor-stator Rubbing Position Identification Based on Casing Strain Signals

  • YU Mingyue ,
  • CHEN Guo ,
  • LIU Yongquan ,
  • JIANG Guangyi ,
  • LI Chenggang ,
  • FENG Guoquan ,
  • WANG Deyou
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  • 1. College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;
    2. AVIC Shenyang Aero-engine Design Institute, Shenyang 110015, China

Received date: 2012-05-29

  Revised date: 2013-01-24

  Online published: 2013-02-19

Supported by

National Natural Science Foundation of China (61179057); National Basic Research Program of China (613139)

摘要

为有效识别航空发动机转静碰摩部位,提出基于机匣应变信号的航空发动机转静碰摩部位识别技术。以应变片为敏感元件,采用沿机匣轴向、周向粘贴应变片两种实验方案,利用航空发动机转子试验器模拟大量不同碰摩部位的样本,采集航空发动机转子试验器机匣上的应变信号,提取应变的均值特征,利用支持向量机,识别不同碰摩位置。结果表明:沿机匣周向的应变均值特征可有效识别转静碰摩部位,且鲁棒性较好,且仅需在机匣的4个位置粘贴应变片即可对4个不同碰摩部位达到100%的识别率。沿机匣轴向的应变均值特征也可识别不同的碰摩部位,但识别效果不如沿机匣周向效果理想。

本文引用格式

于明月 , 陈果 , 刘永泉 , 姜广义 , 李成刚 , 冯国全 , 王德友 . 基于机匣应变信号的航空发动机转静碰摩部位识别[J]. 航空学报, 2013 , 34(6) : 1474 -1484 . DOI: 10.7527/S1000-6893.2013.0080

Abstract

In order to effectively identify aero-engine rotor-stator rubbing positions, an identification method based on casing strain signals is proposed. Two experiment projects are proposed and compared. One is to paste the strain foils along the casing axial direction, the other is to paste them along the casing circumference. A rotor experiment rig of an aero-engine is used to simulate rubbing faults of different radial rubbing positions. The casing strain signals of the rotor experiment rig of the aero-engine is collected and the strain mean features of the two experiment projects are extracted, which are then input into a support vector machine to identify the different rubbing positions. The results show that the strain mean features based on the experiment project which paste strain foils along the casing circumference can effectively identify the rotor-stator rubbing positions of the aero-engine, and the recognition can reach 100%. But the strain mean features based on the project which paste strain foils along the casing axial direction has a lower recognition rate.

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