Rotating machinery fault diagnosis based on parameter-optimized variational mode decomposition

Du, Haoran; Wang, Jixin; Qian, Wenjun; Zhang, Xunan; Wang, Qi

doi:10.1016/j.dsp.2024.104590

Digital Signal Processing

2024

DOI: 10.1016/j.dsp.2024.104590

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Rotating machinery fault diagnosis based on parameter-optimized variational mode decomposition

Haoran Du,

Jixin Wang,

Wenjun Qian

et al.

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Cited by 7 publications

References 48 publications

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A multi-rate sensor fusion and multi-task learning network for concurrent fault diagnosis of hydraulic systems

Chen,

Zheng,

2025

Digital Signal Processing

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A multi-rate sensor fusion and multi-task learning network for concurrent fault diagnosis of hydraulic systems

Chen,

Zheng,

2025

Digital Signal Processing

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Damage identification method for jacket platform based on dual-channel model

Wu,

Gao,

Wei

et al. 2025

Digital Signal Processing

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A robust optimization strategy for brushless DC motor repetitive controller based on H-infinity

Wang,

Yuan,

Bai

2024

AIP Advances

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The control of Brushless DC (BLDC) motor has many challenges. A large number of harmonics are generated during motor operation, while it is susceptible to external disturbances such as noise. The large torque ripple is also a constraint to the large-scale popularity of BLDC motors in some high-end industries. Taking the BLDC motor control system as the research object, this paper proposes a control method of H-infinity repetitive control. First, the state space expression is derived from the mathematical model of the BLDC motor. Then, the parameters of the low-pass filter in the internal mode link are obtained for the design of the internal mode link in the repetitive control. In addition, the H-infinity repetitive control system for the BLDC motor is constructed and converted into the standard form of the H-infinity system. Finally, bringing the generalized controlled object in the standard form of the H-infinity into MATLAB to derive the compliant compensator. The simulation results show that the proposed method can not only suppress harmonics but also improve the robustness of the BLDC motor control system.

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Rotating machinery fault diagnosis based on parameter-optimized variational mode decomposition

Cited by 7 publications

References 48 publications

A multi-rate sensor fusion and multi-task learning network for concurrent fault diagnosis of hydraulic systems

A multi-rate sensor fusion and multi-task learning network for concurrent fault diagnosis of hydraulic systems

Damage identification method for jacket platform based on dual-channel model

A robust optimization strategy for brushless DC motor repetitive controller based on H-infinity

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