Jun 14, 2021 · In this article, we propose a data generation method based on generative adversarial networks (GANs) to solve the problem of data imbalance and ...

To tackle the imbalanced fault data problem of harmonic drive, we propose an intelligent fault diagnosis framework called GAN-DSM-MSCNN to effectively augment ...

Aug 29, 2024 · In this article, we propose a data generation method based on Generative Adversarial Networks (GAN) to solve the problem of data imbalance and ...

The fault diagnosis method based on GAN network is used to construct a small-sample training set of fault signals for GAN training, which simulates the ...

A deep convolutional conditional generative adversarial network (DCCGAN) is constructed to mitigate the impact of imbalanced samples on fault diagnosis.

A novel Multi-resolution Fusion Generative Adversarial Network (MFGAN) is proposed for the imbalanced fault diagnosis of rolling bearings via data augmentation.

Feb 1, 2020 · Enhanced generative adversarial networks for bearing imbalanced fault diagnosis of rotating machinery · Improved generative adversarial network ...

Mar 27, 2024 · This paper provides a comprehensive review of GAN for mechanical fault diagnosis. Firstly, the development of GAN-based mechanical fault diagnosis.

Fault diagnosis of harmonic drive with imbalanced data using generative adversarial network IEEE Trans Instrum Meas. 2021 70 1-11. Crossref · Google Scholar.

Abstract. A frequency-focused sound data generator was developed for the in situ fault sound diagnosis of industrial robot reducers.