朱順鵬，雷強，黃洪鐘，楊亮

（電子科技大學機械電子工程學院，成都 611731）

　　摘  要：在機械構件或材料的疲勞壽命預測中，概率方法已被廣泛用于各種不確定性分析，Bayes方法提供了一個表征各種不確定性的理論基礎，依據歷史知識、經驗或數據，給出模型參數的先驗分布，并能依據現有新的知識進行信息更新，以便準確地進行壽命預估、可靠性分析和維修決策。相比確定性壽命預測方法，本文依據Bayes推理及信息更新技術，綜合考慮模型參數、模型輸入變量、材料屬性和模型等不確定性，構建了概率故障物理壽命預測理論框架，且提出了混合不確定性量化方法-White-Box方法，并探討了其在概率壽命預測的應用。最后，通過對渦輪盤材料GH4133進行概率壽命預測，對比分析了基于延性耗竭模型（VBM）、廣義能量損傷參數（GDP）、SWT模型和塑性應變能密度（PSED）法的壽命預測結果，其預測結果與實測結果均吻合較好，且基于VBM模型的壽命預測值的不確定性范圍明顯窄于SWT、GDP和PSED模型對應的不確定性范圍。

　　關鍵詞：高溫低周疲勞；不確定性；概率壽命預測；渦輪盤；Bayes推理

Probabilistic Life Prediction for Aircraft Turbine Disc Alloy Based on Hybrid-uncertainty Quantification
Shun-Peng Zhu, Qiang Lei, Hong-Zhong Huang, Liang Yang
School of Mechanical, Electronic, and Industrial Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, P.R. China

　　Abstract: Probabilistic methods have been widely used to account for uncertainty from various sources to predict fatigue life for components/materials. The Bayesian approach can potentially give more accurate estimates through combining test data with technical knowledge available from theoretical analyses and/or previous experimental results. The aim of the present paper is to develop a probabilistic methodology for high temperature low cycle fatigue life prediction using physics based models and to demonstrate the use of an efficient probabilistic method. Accordingly, a white-box approach is developed to quantify the hybrid-uncertainty for four life prediction methods （the viscosity based model （VBM）， generalized damage parameter （GDP）， SWT and plastic strain energy density （PSED）） using measured differences between experimental data and model predictions. The proposed method was verified using experimental data for turbine disc alloy GH4133 under different temperatures from literature. The results show that the uncertainty bounds using the VBM for life prediction are tighter than that of GDP, SWT and PSED methods, which leads to better decision making based on the same available knowledge.

　　Keywords: High temperature low cycle fatigue, uncertainty, probabilistic life prediction, turbine disc, Bayesian inference

　　聯系方式

　　朱順鵬：zspeng2007@uestc.edu.cn

責任編輯：趙澤南

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