taptap下载安装安卓学报

• 民用航空 • 上一篇    下一篇

基于数据融合的航空发动机排气温度测量

雷伟   

  1. (厦门航空有限公司飞机维修工程部,福建 厦门 361006)
  • 收稿日期:2017-09-15 修回日期:2017-11-10 出版日期:2018-04-25 发布日期:2018-05-02
  • 作者简介:雷伟(1988—),男,陕西西安人,工程师,硕士研究生,研究方向为航空器可靠性、安全性工程.
  • 基金资助:
    国家自然科学基金项目(U1533128)

Research on aeroengine exhaust temperature measurement based on data fusion

LEI Wei   

  1. (Aircraft Maintenance & Engineering Department, Xiamen Airlines, Xiamen 361006,Fujian, China)
  • Received:2017-09-15 Revised:2017-11-10 Online:2018-04-25 Published:2018-05-02

摘要: 针对某型飞机发动机排气温度测量采用传感器配置不合理尧算法存在局限性,不能对故障传感器进行有效识别等问题,对传感器重新布局设计,通过小波变换对数据进行预处理,去除其中的噪声因素,利用多传感器数据融合技术进行深入优化,并检验了在传感器故障情况下各算法的辨识性。最后通过实验对5 种算法进行对比分析,结果表明基于数据融合的处理方法具有更高的精确度和故障识别能力。

关键词: 航空发动机排气温度, 多传感器, 数据融合

Abstract: Aiming at problems such as irrational configuration of aeroengine exhaust temperature sensor, limitation of the existing algorithms, fail of fault sensor recognition for a certain type of aircraft, sensors are re-distributed, by using wavelet transform for data prepossessing and removing noise factors among them. Multi-sensor data fusion technology is used for a deeper optimization, and the algorithm identifiability is tested under condition of sensor fault. Finally, five kinds of algorithms are compared and analyzed through experiment. Results show that algorithms based on data fusion can obtain higher accuracy and better fault identification capability.

Key words: aeroengine exhaust temperature, multi-sensor, data fusion

中图分类号: 

Baidu
map