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Clustering of decomposed strain signal energy for durability classification

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Abstract

This paper presents clustering of automotive spring fatigue life for failure classification based on K-means approach. For safety promotion of buses, fatigue life prediction of the spring is needed to be classified for maintenance. In this analysis, the strain signals of a heavy vehicle leaf spring were collected from two common roads and analyzed using Hilbert Huang transform. The strain amplitude was used to obtain fatigue life of the leaf spring. Subsequently, the instantaneous frequencies, energies and fatigue lives were clustered into three groups according to the K-means approach. Numerous classification trees were trained with the clustered group as target while the instantaneous frequencies, energies and fatigue lives datasets as input. The trained classification trees were evaluated using receiver operating characteristic curve which shown an acceptable prediction of classes. This classification tree serves as a tool to evaluation automotive leaf spring design for fatigue failure prevention without destroying the component.

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Acknowledgments

The authors wish to acknowledge Universiti Kebangsaan Malaysia research grants FRGS/1/2019/TK03/UKM/01/3 and GUP-2018-077 for the research funding.

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Authors and Affiliations

  1. Department of Mechanical and Manufacturing Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM, Bangi, Selangor, Malaysia

    Y. S. Kong, Shahrum Abdullah & S. S. K. Singh

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  1. Y. S. Kong
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  2. Shahrum Abdullah
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  3. S. S. K. Singh
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Corresponding author

Correspondence to Shahrum Abdullah.

Additional information

Yat Sheng Kong is a Ph.D. graduate from Universiti Kebangsaan Malaysia and University of Duisburg-Essen, Germany. He is a Technical Solution Specialist at Quantarad Technologies Sdn Bhd. His research interests include data analysis, vibrations, structure durability and vehicle dynamics.

Shahrum Abdullah is a Professor at Department of Mechanical and Manufacturing Engineering, UKM, Malaysia. He received his Ph.D. from the University of Sheffield, UK in 2005. His research interests are fatigue analysis, fracture mechanics, signal processing and engineering design.

Salvinder Singh Karam Singh is a Senior Lecturer at Department of Mechanical and Manufacturing Engineering, UKM, Malaysia. He received his Ph.D. from Universiti Kebangsaan Malaysia in 2016. His research interests are reliability and fatigue design.

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Kong, Y.S., Abdullah, S. & Singh, S.S.K. Clustering of decomposed strain signal energy for durability classification. J Mech Sci Technol 35, 2061–2072 (2021). https://doi.org/10.1007/s12206-021-0422-6

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  • DOI: https://doi.org/10.1007/s12206-021-0422-6

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