李秋红

Associate Professor   Supervisor of Master's Candidates

Gender:Female

Alma Mater:南京航空航天大学

Education Level:南京航空航天大学

Degree:Doctoral Degree in Engineering

School/Department:College of Energy and Power Engineering

Discipline:Aerospace Propulsion Theory and Engineering. Power Machinery and Engineering

Business Address:A10-512

E-Mail:


Paper Publications

Aero-engine gas path fault diagnosis based on broyden algorithm

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Affiliation of Author(s):能源与动力学院

Journal:Tuijin Jishu

Abstract:To solve the problems of slow response speed and poor accuracy in multi-fault diagnosis and off-design point fault diagnosis which arise in aero-engine gas path fault diagnosis based on Kalman filter, an equation-solving fault diagnosis method using the improved Broyden algorithm was proposed. For turbo-shaft engine, the gas path fault diagnosis equations were built. They include 3 equations based on the principle that the model outputs should consist with the engine outputs and 2 balance equations from engine model. The improved Broyden algorithm was used to solve the equations to get the component performance degradation factor and the model guess value. Simulation results show that the max steady-state fault diagnosis error based on the proposed method is less than 0.35% in the envelop for both single fault diagnosis and multi-fault diagnosis, and the maximum operation time of single step is less than 2ms. The result is much better than that of Kalman filter, which shows the advantage of the proposed method. © 2017, Editorial Department of Journal of Propulsion Technology. All right reserved.

ISSN No.:1001-4055

Translation or Not:no

Date of Publication:2017-01-01

Co-author:Pan, Yang,Wang Yuan

Correspondence Author:LI qiuhong

Pre One:航空发动机气动热力系统模型求解方法研究

Next One:An Exact Derivative Based Aero-Engine Modeling Method

Profile

现任南京航空航天大学能源与动力学院副教授,硕士生导师。

主讲本科生课程《自动控制原理》和研究生课程《线性系统理论与设计》,具有20多年教学经验,本科教学评估连续优秀,被研究生评选为我最喜爱的导师。

研究方向为航空发动机建模、控制和故障诊断。主持及参与国家自然科学基金、航空科学基金、国防预研、国防基础、两机专项等项目20余项,已培养硕士研究生30余名,在国内外核心及以上期刊上发表论文50多篇,获得科技进步奖两项,授权发明专利30余项,参与编写《航空燃气涡轮发动机控制》专著一部、参与翻译《燃气轮机建模、仿真与控制-基于人工神经网络的方法》教材。所获国防科技进步奖“航空发动机多变量智能鲁棒控制”,排名第二,为主要完成人。完成多项多变量鲁棒控制验证项目研究,完成多项航空发动机传感器及气路故障诊断研究工作。建立了常规涡扇、涡轴发动机的数学模型,并完成了模型修正研究工作。完成了先进变循环发动机、涡轮冲压组合发动机、短距起飞垂直降落发动机的建模和多变量控制研究,开展了智能发动机的智能直接推力控制研究和验证工作。

目前致力于将人工智能技术和航空发动机建模、控制和故障诊断相结合,利用人工智能的在线学习能力,提高发动机控制系统的性能。

硕士招生方向:

学术型I:航空宇航推进理论科学与技术

学术型II:动力机械及工程热物理

专业型I:能源与动力