The cross-domain fault diagnosis with various types of noisy labels is investigated. •. Kernel aggregated convolutional layers are proposed to amplify ...

Recent efforts following adversarial domain adaptation attempt to learn with label noise conditioned on the classifier predictions. However, an essential flaw ...

Recent efforts following adversarial domain adaptation attempt to learn with label noise conditioned on the classifier predictions. However, an essential flaw ...

This label noise introduces strict requirements for label-noise tolerance and the learning capabilities of fault diagnosis algorithms. This paper presents a ...

Apr 11, 2024 · This study presents an adaptive fully convolutional network (AFCN) for identifying bearing defects in noisy environments. First, we use a novel ...

Mar 13, 2024 · A New Deep Learning Model for Fault Diagnosis with Good Anti-Noise and Domain Adaptation Ability on Raw Vibration Signals. Sensors. 2017;17 ...

Ma, Convolutional kernel aggregated domain adaptation for intelligent fault diagnosis with label noise, Reliab Eng Syst Saf, № 227; Xu, Machine learning for ...

Jan 23, 2023 · Fault diagnosis and prognosis (FDP) tries to recognize and locate the faults from the captured sensory data, and also predict their failures ...

Ma, Convolutional kernel aggregated domain adaptation for intelligent fault diagnosis with label noise, Reliab. Eng. Syst. Saf., № 227 https://doi.org ...

Jul 5, 2019 · The proposed method can accurately diagnose bearing fault signal under strong noise environment. 3. The proposed method has strong adaptive ...