A review on machine learning forecasting growth trends and their real-time applications in different energy systems
T Ahmad, H Chen - Sustainable Cities and Society, 2020 - Elsevier
Energy forecasting and planning play an important role in energy sector development and
policy formulation. The forecasting model selection mostly based on the availability of the …
policy formulation. The forecasting model selection mostly based on the availability of the …
Basic research on machinery fault diagnostics: Past, present, and future trends
Machinery fault diagnosis has progressed over the past decades with the evolution of
machineries in terms of complexity and scale. High-value machineries require condition …
machineries in terms of complexity and scale. High-value machineries require condition …
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 …
Multisynchrosqueezing transform
G Yu, Z Wang, P Zhao - IEEE Transactions on Industrial …, 2018 - ieeexplore.ieee.org
Time-frequency (TF) analysis (TFA) method is an important tool in industrial engineering
fields. However, restricted to Heisenberg uncertainty principle or unexpected cross terms …
fields. However, restricted to Heisenberg uncertainty principle or unexpected cross terms …
A hybrid attention-based multi-wavelet coefficient fusion method in RUL prognosis of rolling bearings
Wavelet transform, a time-frequency analysis method for evaluating non-stationary signals,
can assist in representing equipment degradation over prolonged usage. However, a single …
can assist in representing equipment degradation over prolonged usage. However, a single …
A novel fault diagnosis method based on integrating empirical wavelet transform and fuzzy entropy for motor bearing
W Deng, S Zhang, H Zhao, X Yang - IEEE access, 2018 - ieeexplore.ieee.org
Motor bearing is subjected to the joint effects of much more loads, transmissions, and shocks
that cause bearing fault and machinery breakdown. A vibration signal analysis method is the …
that cause bearing fault and machinery breakdown. A vibration signal analysis method is the …
A concentrated time–frequency analysis tool for bearing fault diagnosis
G Yu - IEEE Transactions on Instrumentation and …, 2019 - ieeexplore.ieee.org
In industrial rotating machinery, the transient signal usually corresponds to the failure of a
primary element, such as a bearing or gear. However, faced with the complexity and …
primary element, such as a bearing or gear. However, faced with the complexity and …
Initial center frequency-guided VMD for fault diagnosis of rotating machines
Variational mode decomposition (VMD), an effective signal decomposing technique, has
attracted considerable attention in recent years. The successful applicability of the VMD …
attracted considerable attention in recent years. The successful applicability of the VMD …
Time-reassigned synchrosqueezing transform: The algorithm and its applications in mechanical signal processing
Synchrosqueezing transform (SST) is an effective post-processing time-frequency analysis
(TFA) method in mechanical signal processing. It improves the concentration of the time …
(TFA) method in mechanical signal processing. It improves the concentration of the time …
Matching synchrosqueezing transform: A useful tool for characterizing signals with fast varying instantaneous frequency and application to machine fault diagnosis
Synchrosqueezing transform (SST) can effectively improve the readability of the time-
frequency (TF) representation (TFR) of nonstationary signals composed of multiple …
frequency (TF) representation (TFR) of nonstationary signals composed of multiple …