2024
DOI: 10.1088/1361-6501/ad662d
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Semi-supervised adaptive anti-noise meta-learning for few-shot industrial gearbox fault diagnosis

Junwei Hu,
Chao Xie

Abstract: Real-time and accurate predictive maintenance of industrial equipment is fundamental for ensuring the safety and stability of advanced manufacturing processes. Current fault diagnosis methods based on data mining rely on a large number of labeled samples, and obtaining sufficient labeled data for diagnosing industrial equipment faults is challenging. Meta-learning can achieve the diagnosis of few-shot samples to a certain extent, but the effect is not ideal. Semi-supervision can effectively leverage a large nu… Show more

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