Affiliation:
1. Moscow State Technical University of Civil Aviation
Abstract
The article deals with issues related to the use of parametric information of the transient-state gas turbine engines (GTE) operation conditions for diagnosing their technical condition during the operation. A review of general approaches to computational algorithms for the recognition and classification of the condition applicable to aircraft GTE has been carried out. The significance of analytical models in modern algorithms for assessing the technical GTE condition is emphasized. The construction of a linearized mathematical model for the transient-state condition of the generalized-scheme aircraft GTE operation has been considered. It represents a system of equations analytically combining the relative parameter divergences measured during the engine operation with the relative divergences of unmeasured thermogasdynamic parameters and geometric gas-air flow duct parameters allowing for the technical condition of gas-air channel elements to be classified. A method for constructing mathematical and diagnostic engine models, using the transient response data, has been formulated. The capability of employing a method of insignificant divergences, used to build linear (linearized) mathematical and diagnostic GTE models for the steady-state conditions of its operation, has been demonstrated as well. It is shown that, despite the structural similarity of linear models of the steady and transient-state processes, diagnostics by means of the stated above processes is based on completely different principles – under the steady-state condition, the classification of a technical condition is determined by the variation in the value of the group of controlled responses, and under the transient-state condition, this operation is based on correlating the change in the transient-state behavior. To ensure the versatility of employing proposed methods regarding various GTE designs installed on modern civil aircraft, a generalized-design aircraft GTE model – a three-shaft bypass turbojet engine with mixing flows in a common jet nozzle, has been considered.
Publisher
Moscow State Institute of Civil Aviation
Reference24 articles.
1. Zaidan, M.A., Mills, A.R., Harrison, R.F., Fleming, P.J. (2016). Gas turbine engines prognostics using bayesian hierarchical models: A variational approach. Mechanical Systems and Signal Processing, vol. 70–71, pp. 120–140. DOI: 10.1016/j.ymssp.2015.09.014
2. Zaidan, M.A., Relan, R., Mills, A.R., Harrison, R.F. (2015). Prognostics of gas turbine engine: An integrated approach. Expert Systems with Applications, vol. 42, issue 22, pp. 8472–8483. DOI: 10.1016/j.eswa.2015.07.003
3. Marins, M.A., Ribeiro, F.M.L., Netto, S.L., Da Silva, E.A.B. (2018). Improved similarity-based modeling for the classification of rotating-machine failures. Journal of the Franklin Institute, vol. 355, issue 4, pp. 1913–1930. DOI: 10.1016/j.jfranklin.2017.07.038
4. Vaezipour, A., Mosavi, A., Seiger‐ roth, U. (2013). Machine learning integrated optimization for decision-making. In: 26th European Conference on Operational Research, Rome. Available at: https://www.semanticscholar.org/paper/Machine-learning-integrated-optimization-for-making-Vaezipour-Mosavi/c1ad5937eecf961a3be64d18889d5ffeb888de50 (accessed: 27.12.2022).
5. Sina Tayarani-Bathaie, S., Khorasani, K. (2015). Fault detection and isolation of gas turbine engines using a bank of neural networks. Journal of Process Control, vol. 36, pp. 22–41. DOI: 10.1016/j.jprocont.2015.08.007
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献