Wyniki wyszukiwania - BazTech

Ograniczanie wyników

1 2024

Powiadomienia systemowe

Sesja wygasła!

Znaleziono wyników: 1

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: sample imbalance

Sortuj według:

Ogranicz wyniki do:

Fault Diagnosis of Centrifugal fan Bearings Based on I-CNN and JMMD in the Context of Sample Imbalance

Gao Yang, Li Xueyi

Eksploatacja i Niezawodność

2024

Vol. 26, no. 4

art. no. 191459

Bearing fault diagnosis is an effective technical means to improve the reliability of centrifugal fan bearings. In this paper, a transfer learning-based fault diagnosis method for Centrifugal fan bearings is proposed, utilizing the improved CNN (I-CNN) and Joint Maximum Mean Discrepancy (JMMD) algorithms. The raw vibration signals of bearings are enhanced through fast Fourier transform for feature representation. The enhanced signals are then processed by parallel multi-scale CNNs with an embedded Squeeze-and-Excitation (SE) attention mechanism to extract and focus on key features. Furthermore, the JMMD is introduced as a metric for quantifying the disparity between the source and target domains, thereby mitigating domain shift. In the loss function, weight factors and scaling factors are introduced to increase attention on minority samples and easily confused samples within the imbalanced dataset. The proposed method is validated on the Centrifugal fan bearing dataset from Jiangnan University and the CWRU dataset.