A generalized method for diagnosing multi-faults in rotating machines using imbalance datasets of different sensor modalities

Mishra, Rismaya Kumar; Choudhary, Anurag; Fatima, S.; Mohanty, A.R.; Panigrahi, B.K.

doi:10.1016/j.engappai.2024.107973

Engineering Applications of Artificial Intelligence

2024

DOI: 10.1016/j.engappai.2024.107973

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A generalized method for diagnosing multi-faults in rotating machines using imbalance datasets of different sensor modalities

Rismaya Kumar Mishra,

Anurag Choudhary,

S. Fatima

et al.

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Cited by 10 publications

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A multi-fault diagnosis method for rolling bearings

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Zhang

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SIViP

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A multi-fault diagnosis method for rolling bearings

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Zhu,

Zhang

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SIViP

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A distinguished deep learning method for gear fault classification using time–frequency representation

Nguyen,

Pham

et al. 2024

Discov Appl Sci

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Fault diagnosis of gearboxes has attracted increasing interest in recent decades due to their ubiquity and importance in the industry. Modern research trends focus on developing a diagnosis system that works automatically with the application of artificial intelligence. These previous studies have used the Deep Learning (DL) network without adequately addressing noise of the input data, requiring more data to achieve effective training. Thus, this work proposes a novel Transfer Learning method using the time–frequency representation of gear vibration signals, which enables more accurate classification in complex working conditions and reduces necessary input data to train. Using fine-tuning techniques proposed in this paper requires only a limited data set while ensuring acceptable classification results. An experiment test rig within different gear faults and load conditions was set up to evaluate the algorithm’s effectiveness.

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A new chiller fault diagnosis method under the imbalanced data environment via combining an improved generative adversarial network with an enhanced deep extreme learning machine

Yang,

Zhang,

Lim

et al. 2024

Engineering Applications of Artificial Intelligence

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A generalized method for diagnosing multi-faults in rotating machines using imbalance datasets of different sensor modalities

Cited by 10 publications

References 53 publications

A multi-fault diagnosis method for rolling bearings

A multi-fault diagnosis method for rolling bearings

A distinguished deep learning method for gear fault classification using time–frequency representation

A new chiller fault diagnosis method under the imbalanced data environment via combining an improved generative adversarial network with an enhanced deep extreme learning machine

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