Application of the Regularization Chaos Prediction Model in Aero-Engine Performance Parameters

Abstract:

Based on the research of complexity and non-linearity of aero-engine exhaust gas temperature (EGT) system, a regularization chaotic prediction model was proposed to build short time forecasting model of EGT. In this paper, in order to gain the best parameter to improve the accuracy of the forecasting model, a simple search algorithm arithmetic was adopted. The simulation analysis shows that the proposed forecasting model obviously exceeded the traditional chaotic forecasting model on prediction accuracy. Therefore, this arithmetic is efficient and feasible for a short-term prediction of aero-engine exhaust gas temperature

• Periodical: Advanced Materials Research (Volumes 424-425)
• Pages: 347-351
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.424-425.347
• Online since: January 2012
• Authors: Yong Sheng Shi, Jun Jie Yue, Yun Xue Song
• Keywords: Aeroengine, Chaotic Prediction, Exhaust Gas Temperature (EGT), Principal Components Regression (PCR), Regularization, Ridge Regression (RR)

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