Intelligent Algorithm for Variable Scale Adaptive Feature Separation of Mechanical Composite Fault Signals
With the development of modern industry and scientific technology, production equipment plays an increasingly important role in military and industrial production, and the fault detection signal of gears and bearings state in transmission equipment becomes very important. Therefore, this paper propo...
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| Auteurs principaux: | , , , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
MDPI AG
2021
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/efc0bb6fb0a44c0f8b3be222af63f6c3 |
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| Résumé: | With the development of modern industry and scientific technology, production equipment plays an increasingly important role in military and industrial production, and the fault detection signal of gears and bearings state in transmission equipment becomes very important. Therefore, this paper proposes a gear-bearing composite fault signal decomposition and reconstruction method, which combines the marine predator algorithm (MPA) and variational mode decomposition (VMD) technologies. For the parameters’ selection of VMD, the optimization algorithm allows us to quickly and accurately obtain the results with the best kurtosis correlation index after signal decomposition and reconstruction. The experiments demonstrate the excellent performance of our method in the field of separation and denoising mixed gear-bearing fault signals. |
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