A hybrid LSTM random forest model with grey wolf optimization for enhanced detection of multiple bearing faults
Bearing degradation is the primary cause of electrical machine failures, making reliable
condition monitoring essential to prevent breakdowns. This paper presents a novel hybrid …
condition monitoring essential to prevent breakdowns. This paper presents a novel hybrid …
A domain generalization network for imbalanced machinery fault diagnosis
Y Guo, G Ju, J Zhang - Scientific Reports, 2024 - nature.com
Abstract Traditional models for Imbalanced Fault Diagnosis (IFD) face challenges in
practical applications due to domain shifts caused by varying working conditions and …
practical applications due to domain shifts caused by varying working conditions and …
High-fidelity nuclear coherent population transfer via mixed-state inverse engineering
Y Wang, FQ Dou - Physical Review C, 2024 - APS
Nuclear coherent population transfer (NCPT) plays an important role in the exploration and
application of atomic nuclei. How to achieve high-fidelity NCPT remains so far challenging …
application of atomic nuclei. How to achieve high-fidelity NCPT remains so far challenging …
A novel design of journal bearings for stability under shock loads
SH Hong - Scientific Reports, 2024 - nature.com
Mechanical systems are expected to operate under various load conditions, and it is
necessary to use a lubrication system to achieve reliability and stable performance. Journal …
necessary to use a lubrication system to achieve reliability and stable performance. Journal …
[HTML][HTML] An Optimal Spatio-Temporal Hybrid Model Based on Wavelet Transform for Early Fault Detection
J Xing, F Li, X Ma, Q Qin - Sensors, 2024 - mdpi.com
An optimal spatio-temporal hybrid model (STHM) based on wavelet transform (WT) is
proposed to improve the sensitivity and accuracy of detecting slowly evolving faults that …
proposed to improve the sensitivity and accuracy of detecting slowly evolving faults that …
Residual Attention Single-Head Vision Transformer Network for Rolling Bearing Fault Diagnosis in Noisy Environments
Rolling bearings play a crucial role in industrial machinery, directly influencing equipment
performance, durability, and safety. However, harsh operating conditions, such as high …
performance, durability, and safety. However, harsh operating conditions, such as high …
Application of Elman-AdaBoost Neural Network in Predicting Aeroengine Flight Thrust
Z Wei, Z Liu, Y Yang, Z Guo - 2024 6th International …, 2024 - ieeexplore.ieee.org
As we all know flight thrust is one of the most important performance parameters of
aeroengines. However, flight thrust is difficult to measure. To predict aircraft engine flight …
aeroengines. However, flight thrust is difficult to measure. To predict aircraft engine flight …
A Electric Vehicle Reducer Bearing Fault Diagnosis Method Based on Space-Time Aware Convolution and Transformer Structure
W Li, T Liu, Y Jiang, F Chen - 2024 5th International …, 2024 - ieeexplore.ieee.org
The reliability and efficiency of industrial machinery are critically dependent on the early
detection of faults in critical components such as reducer bearings. This paper presents a …
detection of faults in critical components such as reducer bearings. This paper presents a …