A Fault Diagnosis Method of Rolling Bearings Based on Parameter Optimization and Adaptive Generalized S-Transform
نویسندگان
چکیده
As for the fault diagnosis of rolling bearings under strong background noises, whether feature extraction is comprehensive and accurate critical, especially data-driven methods. To improve comprehensiveness accuracy extraction, a method proposed based on parameter optimization Adaptive Generalized S-Transform (AGST). The AGST used to solve problem incomplete bearing faults. Particle Swarm Brain Storm Optimization algorithm Discussion Mechanism (PSDMBSO) VMD, which can better separate complete components. effectiveness in this paper verified by comparison with other
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ژورنال
عنوان ژورنال: Machines
سال: 2022
ISSN: ['2075-1702']
DOI: https://doi.org/10.3390/machines10030207