Role of image feature enhancement in intelligent fault diagnosis for mechanical equipment: A review
Y Sun, W Wang - Engineering Failure Analysis, 2024 - Elsevier
In the modern manufacturing industry, mechanical equipment plays a crucial role.
Equipment working in harsh environments for a long time is more likely to break down …
Equipment working in harsh environments for a long time is more likely to break down …
Monthly runoff prediction based on a coupled VMD-SSA-BiLSTM model
X Zhang, X Wang, H Li, S Sun, F Liu - Scientific Reports, 2023 - nature.com
The accurate prediction of monthly runoff in the lower reaches of the Yellow River is crucial
for the rational utilization of regional water resources, optimal allocation, and flood …
for the rational utilization of regional water resources, optimal allocation, and flood …
Boosting short term electric load forecasting of high & medium voltage substations with visibility graphs and graph neural networks
N Giamarelos, EN Zois - Sustainable Energy, Grids and Networks, 2024 - Elsevier
Modern power grids are faced with a series of challenges, such as the ever-increasing
demand for renewable energy sources, extensive urbanization, climate and energy crisis …
demand for renewable energy sources, extensive urbanization, climate and energy crisis …
Utilizing virtual power plants to support main grid for frequency regulation
In this paper, a new control architecture of virtual power plants (VPP) is proposed for the
frequency regulation (FR) in main grid. Firstly, to address the power prediction of …
frequency regulation (FR) in main grid. Firstly, to address the power prediction of …
A Virtual Reality Environment Based on Infrared Thermography for the Detection of Multiple Faults in Kinematic Chains
AI Alvarado-Hernandez, D Checa, RA Osornio-Rios… - Electronics, 2024 - mdpi.com
Kinematic chains are crucial in numerous industrial settings, playing a key role in various
processes. Over recent years, several methods have been developed to monitor and …
processes. Over recent years, several methods have been developed to monitor and …
Detection of simultaneous bearing faults fusing cross correlation with multikernel SVM
Detection of simultaneous bearing faults for condition monitoring (CM) of bearings using
time-domain analysis is quite challenging and open area, particularly in noisy environment …
time-domain analysis is quite challenging and open area, particularly in noisy environment …
A CNN-BILSTM monthly rainfall prediction model based on SCSSA optimization
X Zhang, Y Yang, J Liu, Y Zhang… - Journal of Water and …, 2024 - iwaponline.com
Meteorological conditions play an important role in China's national production, and the
accurate prediction of precipitation is of great significance for social production, flood …
accurate prediction of precipitation is of great significance for social production, flood …
ORgram: semi-supervised learning framework for inline bearing diagnosis in varying speed
CY Hung, CY Lee, CH Tsai, JM Wu - The International Journal of …, 2024 - Springer
Based on the fast kurtogram, many previous studies have focused on frequency band
selection (FBS) affected by interference due to impulsive noise and varying speed …
selection (FBS) affected by interference due to impulsive noise and varying speed …
An Anti-Noise Feature Extraction and Improved Harris Hawks Optimization for On-Load Tap Changer Mechanical Fault Diagnosis
X Liang, Y Wang, H Gu - IEEE Sensors Journal, 2024 - ieeexplore.ieee.org
Traditional on-load tap changer (OLTC) mechanical fault diagnosis methods often focus on
vibration burst data in the diverter switch moving stage but neglect the entire vibration signal …
vibration burst data in the diverter switch moving stage but neglect the entire vibration signal …
A symmetric adaptive visibility graph classification method of orthogonal signals for automatic modulation classification
Visibility graph methods allow time series to mine non‐Euclidean spatial features of
sequences by using graph neural network algorithms. Unlike the traditional fixed‐rule …
sequences by using graph neural network algorithms. Unlike the traditional fixed‐rule …