[HTML][HTML] Fault Diagnosis Method for Tractor Transmission System Based on Improved Convolutional Neural Network–Bidirectional Long Short-Term Memory
L Xu, G Zhao, S Zhao, Y Wu, X Chen - Machines, 2024 - mdpi.com
In response to the problems of limited algorithms and low diagnostic accuracy for fault
diagnosis in large tractor transmission systems, as well as the high noise levels in tractor …
diagnosis in large tractor transmission systems, as well as the high noise levels in tractor …
Computer numerical control machine tool wear monitoring through a data-driven approach
The susceptibility of tools in Computer Numerical Control (CNC) machines makes them the
most vulnerable elements in milling processes. The final product quality and the operations …
most vulnerable elements in milling processes. The final product quality and the operations …
[PDF][PDF] Performance Evaluation of Feature Extraction and SVM for Brain Tumor Detection Using MRI Images
The aim of this study is to develop an automatic detection of brain tumors from magnetic
resonance images based on artificial intelligence. The developed approach comprises three …
resonance images based on artificial intelligence. The developed approach comprises three …
Enhancing gearbox condition monitoring using randomized singular value decomposition and K-nearest neighbor
Efficient gear and bearing diagnosis has become a critical requirement across diverse
industrial applications precisely due to their complex design and exposure to difficult …
industrial applications precisely due to their complex design and exposure to difficult …
Automated Fault Diagnosis Using Maximal Overlap Discret Wavelet Packet Transform and Principal Components Analysis
Bearings and gears are components most susceptible to failure in electromechanical
systems, especially rotating machines. Therefore, fault detection becomes a crucial step, as …
systems, especially rotating machines. Therefore, fault detection becomes a crucial step, as …
An unsupervised transfer learning gear fault diagnosis method based on parameter-optimized VMD and residual attention networks
J Ma, H Lv, Q Liu, L Yan - 2024 - researchsquare.com
Traditional gear intelligent fault diagnosis methods require a large amount of labeled
training data. It is challenging to train a high-precision fault diagnosis model due to the issue …
training data. It is challenging to train a high-precision fault diagnosis model due to the issue …
SeqAttention-Net: Design of a Deep Neural Network for Bearing Fault Detection Based on Small Sample Datasets
H Fan, C Huang, C Ren - International Conference on Intelligent …, 2024 - Springer
As critical components of mechanical equipment, bearings play a vital role in ensuring the
stability and safety of equipment operation. However, traditional fault diagnosis methods …
stability and safety of equipment operation. However, traditional fault diagnosis methods …