YANG Yang 1 ,LI Zhong-sheng 2 ,WANG Yi 1 ,WAN Li-yong 1 ,LIU Hui-juan 1 ,ZHANG Xin-yu 3.Prediction of Aeroengine MTBF Using Regression Analysis of Performance Parameters[J].航空发动机,2023,49(1):34-40
Prediction of Aeroengine MTBF Using Regression Analysis of Performance Parameters
DOI:
Key Words:Mean Time Between Failures (MTBF)  reliability prediction  regression analysis  performance parameters  aeroengine
Author NameAffiliationE-mail
YANG Yang 1 ,LI Zhong-sheng 2 ,WANG Yi 1 ,WAN Li-yong 1 ,LIU Hui-juan 1 ,ZHANG Xin-yu 3 1.AECC Shenyang Engine Research InstituteShenyang 110015China2.Second Military Representative Office of Air Force Equipment Department Stationed in Shenyang AreaShenyang 110043China
3.AVIC Shenyang Aircraft Corporation(Group)Ltd.
Shenyang 110034China 
1024373164@qq.com 
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Abstract:There are many methods to predict the Mean Time Between Failures(MTBF)of the aeroengine reliability index . In the case of lacking data during the engine project demonstration,it is recommended to give priority to the statistical regression method to predict the overall reliability index MTBF. To predict the reliability level of the engine in the preresearch stage,by introducing correction coefficients to modify the regression prediction formula from abroad,a new regression prediction formula could be obtained. However,this formula has a disadvantage that it cannot be applied if the aircraft parameters are not clear. Therefore,a new prediction formula was obtained based on the multiple linear statistical regression analysis using only the engine performance parameters. The results show that the new regression formula can preliminarily estimate the whole engine MTBF level by using engine performance parameters only without the need of knowing aircraft parameters,and the prediction efficiency is high,which can provide a reference for the reliability index MTBF of the engine to sup? port the demonstration for project approval. In summary,this method can realize the rapid prediction of the reliability index MTBF of the whole engine according to the aircraft parameters and engine performance parameters during the demonstration for project approval.
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