| CUI Jingsong,XIAO Kaiwen,YAO Yi,LI Bing,ZHANG Dayi,HUANG Xingrong.Prediction of Turbine Bearing Misalignment Failure Probability Based on Dimension ChainUncertainty Quantification[J].航空发动机,2026,52(1):168-174 |
| Prediction of Turbine Bearing Misalignment Failure Probability Based on Dimension ChainUncertainty Quantification |
| DOI：10.12482/ISSN.1672-3147.20231115001 |
| Key Words:failure probability prediction tolerance accumulation calculation assembly dimension chain polynomial chaotic expan⁃
sion uncertainty quantification |
| Author Name | Affiliation | | CUI Jingsong | School General Engineering ,Beihang University,Beijing 100191, China | | XIAO Kaiwen | School General Engineering ,Beihang University,Beijing 100191, China | | YAO Yi | School General Engineering ,Beihang University,Beijing 100191, China | | LI Bing | The Second Military Representative Office of the Air Force Equipment Department in Chengdu, Chengdu 610503, China | | ZHANG Dayi | School of Energy and Power Engineering ,Beihang University,Beijing 100191, China；Beijing Key Laboratory of Aero-engine Structure and Strength, Beijing 100191, China | | HUANG Xingrong | School General Engineering ,Beihang University,Beijing 100191, China；Research Institute of Aero-Engine ,Beihang University,Beijing 100191,China |
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| Abstract:The accumulation of assembly and geometric tolerance in turbine equipment can lead to misalignment issues in the rotor,
subsequently causing excessive misalignment reaction forces in the bearings. This may result in accelerated wear, reduced lifespan, or even
failure of the bearings. To enhance the reliability of a engine turbine rotor testing apparatus, research was conducted to assess the prob?
ability of bearing failure due to misalignment. Uncertainty quantification methods were used to evaluate the likelihood of bearing failure
and to select the optimal tolerance distribution for the bearing supports. Initially, bearing supports models with different tolerance were
chosen to establish assembly dimension chains for the calculation of tolerance accumulation. Subsequently, the probability distribution of
misalignment values for different dimension chains of bearing supports were assessed using Monte Carlo and Polynomial Chaos Expansion
(PCE) method. Moreover, based on the maximum permissible misalignment value determined by simulations, the failure probability of bear?
ings under different tolerance conditions was calculated to determine the best tolerance distribution plan. The results show that compared
with the Monte Carlo method, the PCE method calculates the misalignment distribution with less error and significantly improves the
computational efficiency. The tolerance distribution scheme obtained is of significant importance for enhancing the reliability of the engine
turbine rotor testing apparatus. The PCE uncertainty quantification method provides an important practical reference for predicting the
failure probability caused by tolerance accumulation. |
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