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基于检查数据和物理退化模型的涡轮叶片检修策略优化
引用本文:陆晓华,左洪福,孙见忠.基于检查数据和物理退化模型的涡轮叶片检修策略优化[J].南京航空航天大学学报,2018,50(5):679-686.
作者姓名:陆晓华  左洪福  孙见忠
作者单位:南京航空航天大学民航学院, 南京, 211106
基金项目:国家自然科学基金(U1533202)资助项目。
摘    要:根据发动机涡轮叶片在日常使用过程中的损伤检修数据确定其失效概率分布函数,应用Paris公式对叶片裂纹增长进行反演分析,得到在指定阈值下可检裂纹长度与初检时间的对应关系;再模拟裂纹增长过程,得到叶片在寿命周期内各个检查时刻的状态;最后通过仿真结果的统计分析得知叶片的失效概率。案例研究结果表明:叶片在服役过程中如果初检时间太早,初检时扩展裂纹长度小,不易被检测到,后续的重复检查间隔长,在各重复检查时刻容易产生失效;如果初检时间太迟,叶片在初检时会接近甚至超过临界损伤值,也增加失效概率。在允许失效概率为10-5的条件下,涡轮叶片在计划运行周期内的最优检查次数12次,最优初检时间和重复检查间隔分别为1 371循环和307循环。所提方法和研究结果为航空公司机务维修人员和发动机工程师的风险评判和检修决策提供依据和参考。

关 键 词:检查数据  物理退化模型  航空发动机  涡轮叶片  检修间隔  优化
收稿时间:2017/10/8 0:00:00
修稿时间:2018/1/15 0:00:00

Optimizing Inspection Policy for Turbine Blades Based on Data-Driven and Physical Deterioration Model
LU Xiaohu,ZUO Hongfu,SUN Jianzhong.Optimizing Inspection Policy for Turbine Blades Based on Data-Driven and Physical Deterioration Model[J].Journal of Nanjing University of Aeronautics & Astronautics,2018,50(5):679-686.
Authors:LU Xiaohu  ZUO Hongfu  SUN Jianzhong
Affiliation:College of Civil Aviation, Nanjing University of Aeronautics & Astronautics, Nanjing, 211106, China
Abstract:The data of damage inspection and maintenance for aero-engine turbine blades is gathered to form the failure probability distribution function which can be used for inverse analysis by the Paris equation. Then the relationship of detectable crack length and initial inspection time under the specified threshold is gained. After that the degradation state of blades at each inspection moment is determined by simulating the crack growth process. Finally, the probability of failure of blades is obtained via statistical analysis for simulation results. A case is shown that the initial inspection should not be carried out too early because the crack would be too small to be easily detected and the blades would have failed at the subsequent longer repeated inspection moments. Similarly, if the initial inspection is too late to function, the damage size may be close to,or even exceed to, the allowable critical threshold and the probability of failure would be greatly increased at the initial inspection moment. On the condition of 10-5 allowable probability of failure, the optimal inspection number of times, initial inspection time and repeated inspection interval are both 12 times, and their scheduled operation cycles of turbine blades are 1 371 cycles and 307 cycles, respectively.The method and results can be acted as proofs and references on risk judgment and maintenance decision of aero-engine turbine blades for airline accendant and engineers.
Keywords:inspection data  physical deterioration model  aero-engine  turbine blades  inspection and maintenance interval  optimizing
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