Study on the application of improved morphological component analysis method in the analysis of vehicle half-axle load

Xicheng Wang; Yufan Cheng; Tianxiang Yu; Bifeng Song

doi:10.1117/12.2683839

14 June 2023 Study on the application of improved morphological component analysis method in the analysis of vehicle half-axle load

Xicheng Wang, Yufan Cheng, Tianxiang Yu, Bifeng Song

Author Affiliations +

Proceedings Volume 12708, 3rd International Conference on Internet of Things and Smart City (IoTSC 2023）; 1270806 (2023) https://doi.org/10.1117/12.2683839
Event: 3rd International Conference on Internet of Things and Smart City (IoTSC 2023）, 2023, Chongqing, China

Abstract

The measured torque signal of the vehicle half-axle is a periodic signal with rotational frequency and harmonics as the main components and interspersed with burr interference. Therefore, it is necessary to remove burrs from the measured signals for noise reduction before transforming them into bench load spectra based on the measured road signals. In this paper, we propose a method based on the improved morphological component and apply it to the burr removal of the measured signals of rotating components to achieve the separation of the actual half-axis load signals from the burr signals. The morphological component analysis based on fast adaptive step iterative shrinkage and P-index threshold noise reduction is proposed to address the drawback of slow convergence and poor noise reduction of the MCA algorithm based on iterative soft threshold shrinkage method. The simulation and the calculation results of a pure electric vehicle half-axle measured torque signal show that the improved morphological component analysis is significantly better than the traditional morphological component analysis in terms of convergence speed, and can effectively separate the burr components in the half-axle load signal.

Citation Download Citation

Xicheng Wang, Yufan Cheng, Tianxiang Yu, and Bifeng Song "Study on the application of improved morphological component analysis method in the analysis of vehicle half-axle load", Proc. SPIE 12708, 3rd International Conference on Internet of Things and Smart City (IoTSC 2023）, 1270806 (14 June 2023); https://doi.org/10.1117/12.2683839

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KEYWORDS

Denoising

Signal processing

Associative arrays

Reconstruction algorithms

Wavelets

Interference (communication)

Electronic filtering

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