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Improving EGT sensing data anomaly detection of aircraft auxiliary power unit
Alternative TitleImproving EGT sensing data anomaly detection of aircraft auxiliary power unit
Liansheng LIU1; Yu PENG1; Lulu WANG2; Yu DONG2; Datong LIU1; Qing GUO1
2020
Source PublicationChinese Journal of Aeronautics
ISSN1000-9361
Volume33Issue:2Pages:448-455
AbstractThe reliability of the on-wing aircraft Auxiliary Power Unit (APU) decides the cost and the comfort of flight to a large degree. The most important function of APU is to help start main engines by providing compressed air. Especially on the condition of sudden shutdown in the air, APU can offer additional thrust for landing. Therefore, its condition monitoring has drawn much attention from the academic and industrial field. Among the on-wing sensing data which can reflect its condition, Exhaust Gas Temperature (EGT) is one of the most important parameters. To ensure the reliability of EGT, one kind of data-driven anomaly detection framework for EGT sensing data is proposed based on the Gaussian Process Regression and Kernel Principal Component Analysis. The situations of one-dimensional and two-dimensional input data for EGT anomaly detection are considered, respectively. The cross-validation experiments are carried out by utilizing the real condition data of APU, which are provided by China Southern Airlines Company Limited Shenyang Maintenance Base. The anomalous stuck condition of EGT sensing data is also detected. Experimental results show that the proposed EGT sensing data anomaly detection method can achieve better performance of false positive ratio, false negative ratio and accuracy. Keywords: Anomaly detection, Auxiliary power unit, Condition-based maintenance, Data-driven framework, Exhaust gas temperature
KeywordMotor vehicles. Aeronautics. Astronautics TL1-4050
Indexed ByCSCD
Language英语
Funding Project[National Natural Science Foundation of China] ; [China Postdoctoral Science Foundation]
CSCD IDCSCD:6670709
Citation statistics
Cited Times:3[CSCD]   [CSCD Record]
Document Type期刊论文
Identifierhttp://ir.imr.ac.cn/handle/321006/142943
Collection中国科学院金属研究所
Affiliation1.School of Electronics and Information Engineering,Harbin Institute of Technology
2.中国科学院金属研究所
3.China Southern Airlines Engineering Technology Research Center
Recommended Citation
GB/T 7714
Liansheng LIU,Yu PENG,Lulu WANG,et al. Improving EGT sensing data anomaly detection of aircraft auxiliary power unit[J]. Chinese Journal of Aeronautics,2020,33(2):448-455.
APA Liansheng LIU,Yu PENG,Lulu WANG,Yu DONG,Datong LIU,&Qing GUO.(2020).Improving EGT sensing data anomaly detection of aircraft auxiliary power unit.Chinese Journal of Aeronautics,33(2),448-455.
MLA Liansheng LIU,et al."Improving EGT sensing data anomaly detection of aircraft auxiliary power unit".Chinese Journal of Aeronautics 33.2(2020):448-455.
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