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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 …
Multistability phenomenon in signal processing, energy harvesting, composite structures, and metamaterials: A review
Multistability is the phenomenon of multiple coexistent stable states, which are highly
sensitive to perturbations, initial conditions, system parameters, etc. Multistability has been …
sensitive to perturbations, initial conditions, system parameters, etc. Multistability has been …
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 …
Bearing fault diagnosis method based on adaptive maximum cyclostationarity blind deconvolution
Blind deconvolution has been proved to be an effective method for fault detection since it
can recover periodic impulses from mixed fault signals convoluted by noise and periodic …
can recover periodic impulses from mixed fault signals convoluted by noise and periodic …
Development of intelligent fault-tolerant control systems with machine learning, deep learning, and transfer learning algorithms: a review
Abstract Intelligent Fault-Tolerant Control (IFTC) refers to the applications of machine
learning algorithms for fault diagnosis and design of Fault-Tolerant Control (FTC). The …
learning algorithms for fault diagnosis and design of Fault-Tolerant Control (FTC). The …
Vibration signal-based early fault prognosis: Status quo and applications
Abstract To implement Prognostics and Health Management (PHM) for industrial systems, it
is paramount to conduct early fault prognosis on the systems to ensure the stability and …
is paramount to conduct early fault prognosis on the systems to ensure the stability and …
Coupled neurons with multi-objective optimization benefit incipient fault identification of machinery
Organisms can sense subtle changes in the environment around them such as temperature,
vibration and magnetic field. That is because biological neural network interconnected …
vibration and magnetic field. That is because biological neural network interconnected …
Noise-boosted weak signal detection in fractional nonlinear systems enhanced by increasing potential-well width and its application to mechanical fault diagnosis
Noise is seen as the annoying something for weak signal detection, but noise is beneficial to
enhance weak signals of interest embedded in noise in nonlinear systems. Moreover, the …
enhance weak signals of interest embedded in noise in nonlinear systems. Moreover, the …
An intelligent fault diagnosis method enhanced by noise injection for machinery
Machinery generally operates under severe and complex conditions, and therefore, the
monitoring signals acquired from machinery would inevitably be accompanied by various …
monitoring signals acquired from machinery would inevitably be accompanied by various …
A rotating machinery fault diagnosis method based on multi-scale dimensionless indicators and random forests
Fault diagnosis methods based on dimensionless indicators have long been studied for
rotating machinery. However, traditional dimensionless indicators frequently suffer a low …
rotating machinery. However, traditional dimensionless indicators frequently suffer a low …