High-level noise load identification based on Chebyshev polynomial piecewise fitting

Yu Cui; Wei Gao

doi:10.1117/12.3025571

28 February 2024 High-level noise load identification based on Chebyshev polynomial piecewise fitting

Yu Cui, Wei Gao

Proceedings Volume 13071, International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023); 1307132 (2024) https://doi.org/10.1117/12.3025571
Event: International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023), 2023, Shenyang, China

Abstract

When the telemetry data noise level is high, the traditional integral moving average processing model has a general effect on noise reduction. In order to improve the noise reduction ability and obtain higher load identification accuracy, a new noise reduction model is constructed based on the Chebyshev orthogonal polynomial and the idea of piecewise overlap. The impact load is simulated by half sine wave. Under the condition of 15 % noise, the error values of load identification results are 1.94 % and 0.76 % respectively after the treatment of integral sliding noise reduction model and Chebyshev noise reduction model. In contrast, the new Chebyshev noise reduction model under high-level noise conditions has better accuracy and wider application.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yu Cui and Wei Gao "High-level noise load identification based on Chebyshev polynomial piecewise fitting", Proc. SPIE 13071, International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023), 1307132 (28 February 2024); https://doi.org/10.1117/12.3025571

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