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Detection of Rotor Unbalance in Multi-Mass Systems Using FFT and Bispectrum Cover

Detection of Rotor Unbalance in Multi-Mass Systems Using FFT and Bispectrum

Power Electronics and Drives
Volume 11 (2026): Issue 1 (January 2026)
By: ,   and    
Open Access
|Jun 2026
Figures & tables

Figures & Tables

Figure 1.

Graphical illustration of rotor unbalance, (a) generation of centrifugal force, (b) generation of a moment of force.

Figure 2.

The principal domain and symmetry regions of the bispectrum.

Figure 3.

Photograph of laboratory stand for unbalance research in two-mass system. PMSM, permanent magnet synchronous motors.

Figure 4.

Block diagram of the control system including modules for measuring current and mechanical vibration acceleration.

Figure 5.

Three-dimensional bispectra of mechanical vibration acceleration signal measured along the Y-axis of the drive with an installed test mass of 45 g: (a) single-mass system, (b) two-mass system.

Figure 6.

Three-dimensional bispectra of the IqREF current signal of the drive with an installed test mass of 45 g: (a) single-mass system, (b) two-mass system.

Figure 7.

Summary of changes in the amplitude of kfr symptoms derived from the spectrum of mechanical vibration acceleration.

Figure 8.

Summary of changes the amplitudes of characteristic symptoms (kfr, kfr) derived from the bispectral analysis of mechanical vibration acceleration.

Figure 9.

Difference between the amplitudes of the symptoms (kfr, kfr) derived from the bispectral analysis of mechanical vibration acceleration for the motor without an installed test mass (m = 0 g) and an installed test mass m = 45 g.

Figure 10.

Summary of changes in the amplitude of kfr symptoms derived from the spectrum of the IqREF current.

Figure 11.

Summary of changes in the amplitudes of characteristic symptoms (kfr, kfr) derived from the bispectral analysis of the IqREF current signal.

Figure 12.

Difference between the amplitudes of the symptoms (kfr, kfr) derived from the bispectral analysis of the IqREF current for the motor without an installed test mass (m = 0 g) and an installed test mass m = 45 g.

Figure 13.

Summary of changes in the amplitude of kfr symptoms derived from the spectrum of mechanical vibration acceleration.

Figure 14.

Summary of changes in the amplitudes of characteristic symptoms (kfr, kfr) derived from the bispectral analysis of mechanical vibration acceleration.

Figure 15.

Difference between the amplitudes of the symptoms (kfr, kfr) derived from the bispectral analysis of mechanical vibration acceleration for the two-mass system without an installed test mass (m = 0 g) and an installed test mass m = 45 g.

Figure 16.

Summary of changes in the amplitude of kfr symptoms derived from the spectrum of the IqREF current.

Figure 17.

Summary of changes in the amplitudes of characteristic symptoms (kfr, kfr) derived from the bispectral analysis of the IqREF current signal.

Figure 18.

Difference between the amplitudes of the symptoms (kfr, kfr) derived from the bispectral analysis of the IqREF current for a two-mass system without an installed test mass (m = 0 g) and an installed test mass m = 45 g.

Figure 19.

Summary of changes in the amplitudes of characteristic symptoms (kfr, kfr) derived from the bispectral analysis and kfr derived from the FFT analysis of mechanical vibration acceleration.

Figure 20.

Summary of changes in the amplitudes of characteristic symptoms (kfr, kfr) derived from the bispectral analysis and kfr derived from the FFT analysis of the IqREF current signal.

Summary of parameters in the bispectrum analysis_

Bispectrum parametersValue/method
Bispectrum estimatorDirect FFT (Direct FFT-based averaged segment method)
Segment length2000
Overlap50%
Window typeHamming
Averaging/smoothing strategyEnsemble averaging
Scaling/normalisationRaw bispectrum
DOI: https://doi.org/10.2478/pead-2026-0019 | Journal eISSN: 2543-4292 | Journal ISSN: 2451-0262
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Language: English
Page range: 316 - 333
Submitted on: Mar 9, 2026
Accepted on: May 26, 2026
Published on: Jun 22, 2026
Published by: Wroclaw University of Science and Technology
In partnership with: Paradigm Publishing Services
Keywords:
unbalance,
two – mass system,
FFT,
bispectrum
Related subjects:
Computer sciences,
Artificial intelligence,
Engineering,
Electrical engineering,
Electronics

© 2026 Paweł Ewert, Bartłomiej Wicher, Tomasz Pajchrowski, published by Wroclaw University of Science and Technology
This work is licensed under the Creative Commons Attribution 4.0 License.

Volume 11 (2026): Issue 1 (January 2026)
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