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Application of energies of optimal frequency bands for fault diagnosis based on modified distance function

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Abstract

Low-dimensional relevant feature sets are ideal to avoid extra data mining for classification. The current work investigates the feasibility of utilizing energies of vibration signals in optimal frequency bands as features for machine fault diagnosis application. Energies in different frequency bands were derived based on Parseval's theorem. The optimal feature sets were extracted by optimization of the related frequency bands using genetic algorithm and a Modified distance function (MDF). The frequency bands and the number of bands were optimized based on the MDF. The MDF is designed to a) maximize the distance between centers of classes, b) minimize the dispersion of features in each class separately, and c) minimize dimension of extracted feature sets. The experimental signals in two different gearboxes were used to demonstrate the efficiency of the presented technique. The results show the effectiveness of the presented technique in gear fault diagnosis application.

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Authors and Affiliations

  1. Department of Mechanical Engineering, Bobby B. Lyle School of Engineering, Southern Methodist University, Dallas, TX, 75205, USA

    Amir Hosein Zamanian

  2. Department of Mechanical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Hafez Ave., 424 Tehran, Iran

    Amir Hosein Zamanian & Abdolreza Ohadi

Authors
  1. Amir Hosein Zamanian
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  2. Abdolreza Ohadi
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Corresponding author

Correspondence to Abdolreza Ohadi.

Additional information

Recommended by Associate Editor Eung-Soo Shin

Amir Hosein Zamanian received his B.Sc. from Bu-Ali Sina University in 2006, and his M.Sc. from Amirkabir University of Technology (Tehran Polytechnic) in 2010 both in Mechanical Engineering. He is currently pursuing his Ph.D. in Mechanical Engineering at Southern Methodist University. His research interests are robotics, dynamics and vibrations, signal processing, control, and soft computing.

Abdolreza Ohadi is a Professor of Mechanical Engineering in Amirkabir University of Technology (Tehran Polytechnic). He is interested in noise and vibrations, structural dynamics, noise and vibration control, rotor dynamics and fault detection. He received his B.Sc. and M.Sc. from Amirkabir University of Technology and his Ph.D. from Sharif University, all in Mechanical Engineering.

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Zamanian, A.H., Ohadi, A. Application of energies of optimal frequency bands for fault diagnosis based on modified distance function. J Mech Sci Technol 31, 2701–2709 (2017). https://doi.org/10.1007/s12206-017-0513-6

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  • DOI: https://doi.org/10.1007/s12206-017-0513-6

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