Articles | Volume 15, issue 2
https://doi.org/10.5194/ms-15-445-2024
https://doi.org/10.5194/ms-15-445-2024
Research article
 | 
13 Aug 2024
Research article |  | 13 Aug 2024

Fault identification of the vehicle suspension system based on binocular vision and kinematic decoupling

Hong Wei, Fulong Liu, Guoxing Li, Xingchen Yun, Muhammad Yousaf Iqbal, and Fengshou Gu

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Cited articles

Abubakar, S., Ahmad, I. S., Gambo, F. L., and Gadanya, M. S.: A Rule-Based Expert System for Automobile Fault Diagnosis, International Journal on Perceptive and Cognitive Computing (IJPCC), 7, 20–25, 2021. 
Alcantara, D. H., Morales-Menendez, R., and Amezquita-Brooks, L.: Fault diagnosis for an automotive suspension using particle filters, in: 2016 European Control Conference (ECC), Aalborg, Denmark, 29 June–1 July 2016, IEEE 1898–1903, https://doi.org/10.1109/ECC.2016.7810568, 2016. 
Arun Balaji, P. and Sugumaran, V.: A Bayes learning approach for monitoring the condition of suspension system using vibration signals, IOP Conf. Ser.-Mat. Sci., 1012, 012029, https://doi.org/10.1088/1757-899X/1012/1/012029, 2021. 
Bai, Y., Sezen, H., Yilmaz, A., and Qin, R.: Bridge vibration measurements using different camera placements and techniques of computer vision and deep learning, ABEN, 4, 25, https://doi.org/10.1186/s43251-023-00105-1, 2023. 
Białkowski, P. and Krężel, B: Diagnostic of shock absorbers during road test with the use of vibration FFT and cross-spectrum analysis, Diagnostyka, 18, 79–86, 2017. 
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Short summary
Vibration measurement technology based on binocular vision and kinematic decoupling is a new method which can effectively extract vertical vibration signal. The proposed method has the advantages of real-time measurement and low cost and overcomes the limitations of traditional measurement methods in error accumulation.
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