Yanlei Gao

Title: Innovations by Yanlei Gao in Turbofan Engine Technology

Introduction

Yanlei Gao, an inventor based in Liaoning, China, has made significant contributions to the field of turbofan engine technology. His innovative methods aim to enhance the accuracy of health parameter estimation for turbofan engines, addressing critical challenges in monitoring engine performance.

Latest Patents

Yanlei Gao holds a patent for the "Stochastic Configuration Network Based Turbofan Engine Health Parameter Estimation Method." This innovative approach combines a model-based Kalman filter algorithm with a data-driven stochastic configuration network. By utilizing the output from the stochastic configuration network as compensation for the Kalman filter, this method aims to improve the estimation accuracy when the measurable parameters are fewer than the health parameters that need to be estimated.

Career Highlights

Gao's affiliation with Dalian University of Technology underlines his commitment to advancing research in engineering and technology. His patent reflects his skill in bridging theoretical algorithms with practical applications in the aviation sector, focusing on enhanced accuracy in turbofan engine monitoring.

Collaborations

Throughout his career, Yanlei Gao has collaborated with notable colleagues in the field, including Yanhua Ma and Xian Du. Together, they contribute to vital research initiatives that push the boundaries of knowledge in engine health monitoring systems.

Conclusion

Yanlei Gao's innovative work in developing advanced methods for turbofan engine health parameter estimation showcases the importance of creativity and technical expertise in engineering. His contributions not only enhance the reliability of modern engines but also pave the way for future advancements in aeronautics.