Instantaneous Frequency Analysis Based on High-Order Multisynchrosqueezing Transform on Motor Current and Application to RV Gearbox Fault Diagnosis
Motor current analysis is useful for ensuring the safety and reliability of electromechanical systems. However, for gearboxes, the commonly used methods of detecting faulty frequency sidebands are easily disturbed by installation errors, inherent harmonics, and fundamental frequency with high amplit...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
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| Series: | Machines |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-1702/13/3/223 |
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| Summary: | Motor current analysis is useful for ensuring the safety and reliability of electromechanical systems. However, for gearboxes, the commonly used methods of detecting faulty frequency sidebands are easily disturbed by installation errors, inherent harmonics, and fundamental frequency with high amplitude. Aiming at this problem, this study presents instantaneous frequency polarview (IFpolarview), which diagnoses faults based on motor angle and motor current frequency modulation (FM) features. Firstly, to address the problem of the limited analysis order of higher-order synchrosqueezing transform (HSST), the higher-order multisynchrosqueezing transform (HMSST) is introduced to improve the instantaneous frequency (IF) estimation accuracy and reveal the transient fault features from the motor current without further increasing the order and algorithm difficulty. Then, based on the motor angle and accurate motor current IF extracted from HMSST, the IFpolarview is proposed to visualize gear faults through detecting the FM of motor current synchronized with the faulty gear mesh. In the simulation, the IF estimation error of HMSST is 2.51%, which is smaller than other methods. The experimental results show that the HMSST has the smallest Rényi entropy value of 9.13, implying that the most aggregated time–frequency representation (TFR) of the energy is obtained. HMSST can enhance the resolution of fault characteristics, and IFpolarview concentrates the abnormal IF fluctuations with periodicity into a small angular interval, which highlights the fault features and demonstrates greater intuitiveness and reliability in comparison to the frequency sideband detection method. |
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| ISSN: | 2075-1702 |