基于动态标准彩色图谱的航空发动机健康状态监控

doi:10.13196/j.cims.2013.12.dudangdang.3068.7.20131218

摘要/Abstract

摘要： 针对航空发动机性能数据的高耦合性、高维性、非线性和非等效性,为从宏观层面动态化、直观化、精细化地快速把握航空发动机的健康状态,提出一种基于动态标准彩色图谱监控航空发动机健康状态的方法。根据航空发动机的实时运行数据,建立时空分布矩阵,通过归一化方法,将时空分布矩阵转化为标准矩阵,进而经过动态化处理,将标准矩阵转变为动态标准化矩阵;将动态标准化矩阵映射至一个由二维欧氏空间和三维彩色空间联合构成的彩色相空间,从而生成反映航空发动机健康状态的彩色图谱。设计并开发了某型发动机彩色图谱健康状态监控分析系统。结合应用实例,证明了该方法的有效性和实用性。

关键词: 航空发动机, 健康状态监控, 彩色图谱, 动态标准化矩阵

Abstract: Aiming at the high coupling,high-dimension,non-linear and non-equivalence features of the performance parameters,a kind of health state monitoring method based on dynamic standard color-picture of aero-engine was proposed,which promoted the fast mastering health state of aero-engine on a macro level dynamically,visually and precisely.According to the real-time performance data of aero-engine,space-time distribution matrix was established and transformed into standard matrix by using normalization,and the dynamic standard matrix was generated by using dynamic process of the standard matrix.The dynamic standard matrix was mapped to the color phase space which was created by two-dimensional Euclidean space and three-dimensional color space,thus a dynamic standard color-picture reflecting health state of aero-engine was produced.An aero-engine health state monitoring system based on dynamic standard color-picture was designed and realized.The effectiveness and feasibility of this method were illustrated by an application case.

Key words: aero-engine, health state monitoring, color-picture, dynamic standard matrix

中图分类号:

V236

杜党党,,贾晓亮 . 基于动态标准彩色图谱的航空发动机健康状态监控[J]. , DOI: 10.13196/j.cims.2013.12.dudangdang.3068.7.20131218.

DU Dang-dang,,JIA Xiao-liang. Health state monitoring for aero-engine based on dynamic standard color-picture [J]. , DOI: 10.13196/j.cims.2013.12.dudangdang.3068.7.20131218.

参考文献

［1］ZHENG Bo,ZHU Xinyu.Aero-engine performance monitoring and forecasting［J］.Aviation Maintenance and Engineering,2009(4):33-35 (in Chinese).［郑波,朱新宇.航空发动机性能监控与预测［J］.航空维修与工程,2009(4):33-35.］
[2]ZHONG Shisheng,LUAN Shenggang.Aeroengine condition monitoring and maintenance data processing system oriented to lifecycle management［J］.Computer Integrated Manufacturing Systems,2006,12(8):1273-1278 (in Chinese).［钟诗胜,栾圣罡.面向航空发动机全寿命周期管理的航线数据处理系统［J］.计算机集成制造系统,2006,12(8):1273-1278.］
[3]MAURYA M R,RENGASWAMY R,VENKATASUB-RAMANIAN V.A signed directed graph and qualitative trend analysis-based framework for incipient fault diagnosis［J］.Chemical Engineer Research and Design,2007,85(10):1407-1422.
[4]ZHANG Chunxiao,NAN Wang.Aero-engine condition monitoring based on support vector machine［J］.Physics Procedia,2012,24:1546-1552.
[5]DAI Jing,ZHANG Ping,LIXingshan,etal.Research on healh assessment of integrated vehicle health management［J］.Journal of Astronautics,2009,30(4):1711-1721 (in Chinese).［代京,张平,李行善,等.综合运载器健康管理健康评估技术研究［J］.宇航学报,2009,30(4):1711-1721.］
[6]WANG Yankai, LIAO Mingfu.Study on grading of health condition of aerospace propulsion system［J］.Journal of Aerospace Power,2008,23(5):939-945 (in Chinese).［王俨剀,廖明夫.航空发动机健康等级综合评价方法［J］.航空动力学报,2008,23(5):939-945.］
[7]SHAN Xiaoming,SONG Yunfeng,HUANG Jinquan,et al.Condition monitoring of aero-engine based on neural network and fuzzy logic［J］.Journal of Aerospace Power,2009,24(10):2356-2361 (in Chinese).［单晓明,宋云峰,黄金泉,等.基于神经网络和模糊逻辑的航空发动机状态监视［J］.航空动力学报,2009,24(10):2356-2361.］
[8]YANG Zhou,JING Bo,ZHANG Jie.Variable precision rought set decision-method for health assessment of aero-engine［J］.Journal of Aerospace Power,2013,28(2):283-289 (in Chinese).［杨洲,景博,张劼.航空发动机健康评估变精度粗糙集决策方法［J］.航空动力学报,2013,28(2):283-289.］
[9]LI Xiaobai,CUI Xiuling,LANG Rongling.Forecasting method for aeroengine performance parameters［J］.Journal of Beijing University of Aeronautics and Astronautics,2008,34(3):253-256 (in Chinese).［李晓白,崔秀伶,郎荣玲.航空发动机性能参数预测方法［J］.北京航空航天大学学报,2008,34(3):253-256.］
[10]JIANG Caihong,SUN Zhiyan,WANG Xi.Critical technologies for aero-engine prognostics and health management systems development［J］.Journal of Aerospace Power,2009,24(11):2589-2594 (in Chinese).［姜彩虹,孙志岩,王曦.航空发动机预测健康管理系统设计的关键技术［J］.航空动力学报,2009,24(11):2589-2594.］
[11]ZHANG Ying,ZUO Hongfu,REN Shuhong,et al.Research on an algorithm for prediction of aeroengine performance deterioration［J］.China Mechanical Engineering,2011,22(9):1009-1013 (in Chinese).［张营,左洪福,任淑红,等.一种航空发动机性能衰退预测的优化算法［J］.中国机械工程,2011,22(9):1009-1013.］
[12]GUO Xin,YANG Zhijun.Study of Aero engine Starting Tests at High/Low Temperatures and at Plateau［J］.Journal of Aerospace Power,2003,18(3):327-330 (in Chinese).［郭昕,杨志军.航空发动机高、低温起动及高原起动试验技术探讨［J］.航空动力学报,2003,18(3):327-330.］
[13]LI Benwei,HU Guocai,GAO Guosheng,et al.Study of Selecting Parameters and Fault Diagnosis for Turboshaft［J］.Journal of Aerospace Power,2002,17(2):160-164 (in Chinese).［李本威,胡国才,高国胜,等.涡轴发动机监视参数选择与诊断方法研究［J］.航空动力学报,2002,17(2):160-164.］
[14]SUN Kai,GAO Jianmin,GAO Zhiyong.Health State Analysis of Modern Industry System through System Color Picture Based on the Data-driven［J］.Journal of Mechanical Engineering,2012,48(18):186-191 (in Chinese).［孙锴,高建民,高智勇.基于数据驱动的系统彩色图谱分析现代工业系统健康状态［J］.机械工程学报,2012,48(18):186-191.］
[15]XU Chengdong,PEI Xin,LIU Yingbo,et al.Requirment analysis and architecture of maintenance,repair and overhaul/operations information system for helicopters［J］.Computer Integrated Manufacturing Systems,2010,16(10) :2285-2292 (in Chinese).［许承东,裴鑫,刘英博,等.直升机MRO信息系统需求分析与体系结构［J］.计算机集成制造系统,2010,16(10) :2285-2292.］

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