Real-Time Signal Denoising Algorithm in Wheel Force Transducer

Dong Wang; Guo Yu Lin; Wei Gong Zhang

doi:10.4028/www.scientific.net/AMM.615.244

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 615Real-Time Signal Denoising Algorithm in Wheel...

Real-Time Signal Denoising Algorithm in Wheel Force Transducer

Abstract:

The wheel force transducer (WFT) is used to measure dynamic wheel loads. Unlike other force sensors, WFT is rotating with the wheel. For this reason, the outputs and the inputs of the transducer are nonlinearly related, and traditional Kalman Filter is not suitable. In this paper, a new real-time filter algorithm utilizing Quadrature Kalman Filter (QKF) is proposed to solve this problem. In Quadrature Kalman Filter, Singer model is introduced to track the wheel force, and the observation function is established for WFT. The simulation results illustrate that the new filter outperforms the traditional Unscented Kalman Filter (UKF) and Extended Kalman Filter (EKF).

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Periodical:

Applied Mechanics and Materials (Volume 615)

Pages:

244-247

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.615.244

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Online since:

August 2014

Authors:

Dong Wang, Guo Yu Lin*, Wei Gong Zhang

Keywords:

Monte-Carlo Method, QKF, Singer Model, WFT

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References

[1] Dong W, Guoyu L, Wei-gong Z, Ning Z, Han P, The new method of initial calibration with the wheel force transducer, Sensor Review, (2014) Vol. 34 Iss: 1, p.98 – 109.

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