Improved force identification with augmented Kalman filter based on the sparse constraint

Abstract The excitation force identification of multiple devices in railway vehicles is studied. The vertical dynamic coupling model between the flexible car body of high-speed train and the under-chassis active device with excitation itself is established based on the modal superposition method. The excitation force from device is identified based on Kalman filter. A modal order selection method is developed for improving the identification accuracy based on tolerance index. The identification effects of single and multiple active devices including single-frequency steady-state, multi-frequency steady-state, impact, sawtooth wave and square wave excitation forces are analyzed. An error limit range of 5% is defined to evaluate the identification results. The results show that the method is suitable for the identification of various steady-state and transient-state excitation forces, and the identification results of excitation forces of single and multiple active devices have good accuracy.

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The Application of the Modified Sage-Husa Adaptive Kalman Filter in the Excitation Force Identification of Under-Chassis Active Equipment for Railway Vehicles

Journal of Vibration and Acoustics ◽

10.1115/1.4048552 ◽

2020 ◽

Vol 143 (3) ◽

Author(s):

Jiangxue Chen ◽

Jinsong Zhou ◽

Dao Gong ◽

Wenjing Sun ◽

Yu Sun ◽

...

Keyword(s):

Kalman Filter ◽

Experimental Result ◽

Engineering Practice ◽

Adaptive Kalman Filter ◽

Pass Filter ◽

Low Pass Filter ◽

Force Identification ◽

Railway Vehicles ◽

Noise Characteristics ◽

Excitation Force

Abstract Excitation force of under-chassis active equipment of railway vehicles has a significant impact on the floor vibration of the car body. In order to improve the accuracy of the excitation force identification of active equipment in engineering practice, a new excitation force identification method was proposed by applying modified Sage-Husa adaptive Kalman filter (MSHAKF). First, the advantages of the MSHAKF over conventional Kalman filter (CKF) are introduced. Simulation shows that the MSHAKF has excellent exactness and robustness for active equipment excitation force identification. Finally, a test device for identifying excitation force was established. The infinite impulse response (IIR) low-pass filter is designed by using the bilinear transformation method to eliminate the identification error caused by the frequency multiplication components in the response signal. The experimental result shows that the proposed method is very effective in engineering practice without mastering the noise characteristics of the system.

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