Outline
- Abstract
- I. Introduction
- II. Blade Tip Clearance
- III. Failure Risk Assessment
- IV. Failure Analysis by Statistical Treatments
- V. Summary
رئوس مطالب
- چکیده
- 1. مقدمه
- 2. فاصله آزاد لبه تیغه
- 3. ارزیابی ریسک خرابی
- 4. تحلیل خرابی از طریق عملیات آماری
- 5. خلاصه
Abstract
Algorithmic approaches for failure risk assessment, anomaly detection and life prognosis of gas turbine blade are discussed. Modeling of blade tip clearance and Monte Carlo simulation considering creep, vibration and other damaging effects lead to two probabilistic distributions with blade tip clearance data. Failure risk can be determined during blade life usage based on blade tip tolerance limits. Statistical treatments considering percentile ranking of sample mean and regression analysis of blade tip clearance data for anomaly detection and usage life analysis respectively are also discussed.
SUMMARY
Engine efficiency and integrity are the two major concerns with turbine blade performance. An algorithmic approach for modeling and simulations for blade tip clearance is discussed. Two probabilistic distributions (lognormal and normal) of blade tip clearance data with life usage are proposed for statistical failure risk assessment. As an alternative approach, operational blade tip clearance data can be monitored using sensors, processed and statistically treated to determine percentile ranking of mean for anomaly detection. The BTC data can be further treated with regression analysis for turbine blade life prognosis.