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Combined rotor fault diagnosis in rotating machinery using empirical mode decomposition

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Abstract

Unbalance, misalignment, partial rub, looseness and bent rotor are one of the most commonly observed faults in rotating machines. These faults cause breakdowns in rotating machinery and create undesired vibrations while operating. In this study, an approach to detect combined fault of unbalance and bent rotors for advance detection of the features of the fault rotors diagnosis is proposed. Empirical mode decomposition (EMD) is used efficiently to decompose the complex vibration signals of rotating machinery into a known number of intrinsic mode functions so that the fault characteristics of the unbalanced and bowed shaft can be examined in the time-frequency Hilbert spectrum. A test bench of Spectra-Quest has been used for performing experiments to illustrate the unbalance and the bent rotor conditions as well as the healthy rotor condition. Analysis of the results shows the usefulness of proposed approach in diagnosing the unbalance and bowed fault of the shaft in rotating machinery.

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Authors and Affiliations

  1. School of Mechanical Materials and Energy Engineering, Indian Institute of Technology (IIT), Ropar Rupnagar, 140001, Punjab, India

    Sukhjeet Singh & Navin Kumar

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  1. Sukhjeet Singh
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  2. Navin Kumar
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Correspondence to Navin Kumar.

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Recommended by Editor Yeon June Kang

Navin Kumar is an Assistant Professor in the School of Mechanical Materials and Energy Engineering at Indian Institute of Technology (IIT), Ropar, India. Prior to joining IIT Ropar, he was working as a Research Scientist at Stevens Institute of Technology, New Jersey, USA. He did Masters in Mechanical Engineering from Indian Institute of Technology, Kharagpur, India and Ph.D. (Mechanical Engineering). Dr. Navin Kumar’s research interests are related to smart structures and materials, fault diagnosis and condition monitoring.

Sukhjeet Singh is a Research Scholar in the School of Mechanical Materials and Energy Engineering at Indian Institute of Technology, Ropar, India. He received his Bachelor’s (Mech Engg) and Master’s degree (Machine design) from the Punjab Technical University, Jalandhar, Punjab, India. His research interests include experimental aspects of vibration analysis, rotor dynamics, signal processing and machine learning techniques.

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Singh, S., Kumar, N. Combined rotor fault diagnosis in rotating machinery using empirical mode decomposition. J Mech Sci Technol 28, 4869–4876 (2014). https://doi.org/10.1007/s12206-014-1107-1

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  • DOI: https://doi.org/10.1007/s12206-014-1107-1

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