Remaining Useful Life Prediction Method for High Temperature Blades of Gas Turbines Based on 3D Reconstruction and Machine Learning Techniques
Abstract
:1. Introduction
2. Methodology
2.1. Reconstructed Geometric Model of the Turbine Blade Based on 3D Scanning Data
2.2. Three-Dimensional Numerical Simulation
2.2.1. Numerical Methods in Simulation
2.2.2. Governing Equations and Boundary Conditions
2.2.3. Selection of Checkpoints
2.3. Data Set of Fatigue-Creep Lifetime
2.4. Surrogate Model Based on the Lifetime Dataset
3. Results and Discussion
3.1. Validation of Lifetime Data Sets
3.1.1. Checkpoint Acquisition for Lifetime Calculation
3.1.2. Calculation and Verification of Lifetime
3.2. Prediction Effect of Different Surrogate Models
3.3. Application of the Life Prediction Method
4. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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No. | Reason for Check |
---|---|
1 | Equivalent stress value is maximum |
2 | Equivalent strain value is maximum |
3 | Temperature is maximum |
4 | Special geometric features |
No. | Equivalent Stress | Temperature | Equivalent Strain |
---|---|---|---|
Stationary blade | |||
1 | 1481.51 MPa | 1033.34 K | 0.006926 |
2 | 1300.34 MPa | 1198.93 K | 0.006033 |
3 | 800.83 MPa | 900.29 K | 0.005503 |
Stationary blade | |||
4 | 1308.44 MPa | 1220.02 K | 0.009332 |
5 | 1376.43 MPa | 1393.42 K | 0.009482 |
6 | 1385.02 MPa | 1300.23 K | 0.009744 |
No. | (rpm) | (kPa) | (kPa) | (kg/s) | (K) | EOH Increments (h) |
---|---|---|---|---|---|---|
1 | 0.047599 | 0.002423 | 0.000000 | 0.123522 | 0.40163 | 0.000000 |
2 | 0.000000 | 0.000000 | 0.010254 | 0.714323 | 0.266652 | 0.125527 |
3 | 0.646053 | 0.211596 | 0.103201 | 0.761335 | 0.059797 | 0.221033 |
4 | 0.667572 | 0.215596 | 0.122717 | 0.855482 | 0.141488 | 0.264292 |
5 | 0.667456 | 0.21525 | 0.126121 | 0.118456 | 0.134114 | 0.329359 |
6 | 0.969942 | 0.982835 | 0.970026 | 0.488695 | 0.000000 | 0.469595 |
7 | 0.907062 | 0.936506 | 0.91264 | 0.114499 | 0.377102 | 0.487253 |
8 | 0.927423 | 0.900578 | 0.958006 | 0.000000 | 0.67072 | 0.642145 |
9 | 0.976506 | 0.905042 | 0.916885 | 0.106072 | 0.706214 | 0.707132 |
10 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 0.880289 |
11 | 0.992645 | 0.990454 | 0.984139 | 0.739875 | 0.897642 | 0.932550 |
12 | 0.992288 | 0.988131 | 0.980131 | 0.701384 | 0.884362 | 1.000000 |
No. | Relative Error | No. | Relative Error |
---|---|---|---|
1 | 0.687% | 7 | 0.887% |
2 | 0.468% | 8 | 0.746% |
3 | 0.446% | 9 | 0.676% |
4 | 0.424% | 10 | 0.636% |
5 | 0.986% | 11 | 0.543% |
6 | 0.894% | 12 | 0.541% |
Activation Function | Number of Hidden Layers | |
---|---|---|
BP | Tansig for the hidden layer, Purelin for the output layer | 9 |
DNN | ReLU | 3 |
LSTM | Sigmoid for the input gate and the forget gate, Tanh for the candidate memory cell | 2 |
Maximum Relative Error | R2 | RMSE | MAE | |
---|---|---|---|---|
BP | 0.030% | 0.9601 | 0.1130 | 0.0819 |
DNN | 0.019% | 0.9734 | 0.0863 | 0.0629 |
LSTM | 0.014% | 0.9899 | 0.0511 | 0.0372 |
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Xiao, W.; Chen, Y.; Zhang, H.; Shen, D. Remaining Useful Life Prediction Method for High Temperature Blades of Gas Turbines Based on 3D Reconstruction and Machine Learning Techniques. Appl. Sci. 2023, 13, 11079. https://doi.org/10.3390/app131911079
Xiao W, Chen Y, Zhang H, Shen D. Remaining Useful Life Prediction Method for High Temperature Blades of Gas Turbines Based on 3D Reconstruction and Machine Learning Techniques. Applied Sciences. 2023; 13(19):11079. https://doi.org/10.3390/app131911079
Chicago/Turabian StyleXiao, Wang, Yifan Chen, Huisheng Zhang, and Denghai Shen. 2023. "Remaining Useful Life Prediction Method for High Temperature Blades of Gas Turbines Based on 3D Reconstruction and Machine Learning Techniques" Applied Sciences 13, no. 19: 11079. https://doi.org/10.3390/app131911079
APA StyleXiao, W., Chen, Y., Zhang, H., & Shen, D. (2023). Remaining Useful Life Prediction Method for High Temperature Blades of Gas Turbines Based on 3D Reconstruction and Machine Learning Techniques. Applied Sciences, 13(19), 11079. https://doi.org/10.3390/app131911079