Modelling Fatigue Crack Propagation with Kalman Filtering
Xiaoming Nasser
Georgia Institute of Technology
Sadia Bose
Bangladesh University of Engineering and Technology
Deepak Park
Rajshahi University of Engineering & Technology
Abstract
There remains a pressing need for cost-effective methods to assess fatigue crack propagation in aerospace structures. The workflow applies Kalman filtering to several years of historical records collected from aerospace structures. The optimised configuration extended service life by an estimated 10%. The approach is particularly well suited to settings where data and resources are limited.
Keywords:
fatigue crack propagationKalman filteringfinite element analysisgenetic algorithmcarbon fibre
References
- Diallo, M., Wang, H., & Singh, A. (2002). Shape memory alloys in metal additive manufacturing. Composites Part B: Engineering, 47(4), 35-42.
- Hossain, R., Novak, I., & Islam, S. (2016). Fluidised bed reactors in building energy efficiency. IEEE Transactions on Neural Networks and Learning Systems, 37(1), 87-103.
- Novak, K., & Liu, R. (2005). Voltage stability of transmission networks in semiconductor fabrication. Energies, 28(1), 94-100.
- Schmidt, M. (1996). Vibration of rotating shafts in cyber-physical systems. International Conference on Electrical, Computer and Communication Engineering (ECCE), 17(3), 635-645.
- Tran, F., & Ahmadi, S. (1996). Voltage stability of transmission networks in coastal and offshore engineering. IEEE Internet of Things Journal, 40(5), 340-358.
- Sato, R. (1996). Network intrusion detection in Internet of Things deployments. Energies, 27(2), 500-514.
- Muller, S. (2004). Grid-connected photovoltaic systems in textile manufacturing. Expert Systems with Applications, 42(1), 199-207.