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Applications of machine learning to machine fault diagnosis: A review and roadmap
Intelligent fault diagnosis (IFD) refers to applications of machine learning theories to
machine fault diagnosis. This is a promising way to release the contribution from human …
machine fault diagnosis. This is a promising way to release the contribution from human …
A review on vibration-based condition monitoring of rotating machinery
Monitoring vibrations in rotating machinery allows effective diagnostics, as abnormal
functioning states are related to specific patterns that can be extracted from vibration signals …
functioning states are related to specific patterns that can be extracted from vibration signals …
Multi-input CNN based vibro-acoustic fusion for accurate fault diagnosis of induction motor
Induction motor (IM) is a highly efficient prime mover in industrial applications. To maintain
an uninterrupted operation, accurate fault diagnosis system of IM is required. It can help to …
an uninterrupted operation, accurate fault diagnosis system of IM is required. It can help to …
Deep convolutional generative adversarial network with semi-supervised learning enabled physics elucidation for extended gear fault diagnosis under data limitations
Fault detection and diagnosis of gear systems using vibration measurements play an
important role in ensuring their functional reliability and safety. Computational intelligence …
important role in ensuring their functional reliability and safety. Computational intelligence …
Integrated intelligent fault diagnosis approach of offshore wind turbine bearing based on information stream fusion and semi-supervised learning
Offshore wind turbines play a vital role in transferring wind energy to electricity, which could
help relieve the energy crisis and improve the global climate. In general, offshore wind …
help relieve the energy crisis and improve the global climate. In general, offshore wind …
Data-driven methods for predictive maintenance of industrial equipment: A survey
W Zhang, D Yang, H Wang - IEEE systems journal, 2019 - ieeexplore.ieee.org
With the tremendous revival of artificial intelligence, predictive maintenance (PdM) based on
data-driven methods has become the most effective solution to address smart manufacturing …
data-driven methods has become the most effective solution to address smart manufacturing …
Planetary gearbox fault diagnosis using bidirectional-convolutional LSTM networks
Gearbox fault diagnosis is expected to significantly improve the reliability, safety and
efficiency of power transmission systems. However, planetary gearbox fault diagnosis …
efficiency of power transmission systems. However, planetary gearbox fault diagnosis …
A deep learning method for bearing fault diagnosis based on cyclic spectral coherence and convolutional neural networks
Accurate fault diagnosis is critical to ensure the safe and reliable operation of rotating
machinery. Data-driven fault diagnosis techniques based on Deep Learning (DL) have …
machinery. Data-driven fault diagnosis techniques based on Deep Learning (DL) have …
Data fusion and machine learning for industrial prognosis: Trends and perspectives towards Industry 4.0
The so-called “smartization” of manufacturing industries has been conceived as the fourth
industrial revolution or Industry 4.0, a paradigm shift propelled by the upsurge and …
industrial revolution or Industry 4.0, a paradigm shift propelled by the upsurge and …
Deep learning for smart manufacturing: Methods and applications
Smart manufacturing refers to using advanced data analytics to complement physical
science for improving system performance and decision making. With the widespread …
science for improving system performance and decision making. With the widespread …