LSTM-based node-gated graph neural network for cross-condition few-shot bearing fault diagnosis
Y Jiang, L Zheng, C Tang, J Sun, Z Shi… - IEEE Sensors …, 2024 - ieeexplore.ieee.org
In practical scenarios, the working conditions of bearings change with the variation of work
tasks, making it extremely challenging to collect a large number of fault samples for each …
tasks, making it extremely challenging to collect a large number of fault samples for each …
不平衡转子系统弯扭耦合复杂故障智能诊断
李舜酩， 陆建涛， 沈涛 - 重庆理工大学学报(自然科学), 2023 - clgzk.qks.cqut.edu.cn
弯曲振动与扭转振动耦合在旋转机械实际运行中往往不可避免. 考虑不平衡转子不同复杂工况的
弯扭耦合情况, 利用深度学习技术的优势, 构建了基于一维卷积神经网络的诊断模型 …
弯扭耦合情况, 利用深度学习技术的优势, 构建了基于一维卷积神经网络的诊断模型 …
Adaptive Dynamic Threshold Graph Neural Network: A Novel Deep Learning Framework for Cross-Condition Bearing Fault Diagnosis
L Zheng, Y Jiang, H Jiang, C Tang, W Jiao, Z Shi… - Machines, 2023 - mdpi.com
Recently, bearing fault diagnosis methods based on deep learning have achieved
significant success. However, in practical engineering applications, the limited labeled data …
significant success. However, in practical engineering applications, the limited labeled data …
An insulating composite material defects detection CNN model using knowledge-based 2D structured ultrasonic signals
X Liu, Z Li, S Song, H Li, H Suo, W Liu… - Engineering …, 2024 - iopscience.iop.org
Defects detection of insulators is crucial for the safe operation of power grid. A strategy of
domain knowledge-assisted convolutional neural network is implemented for evaluating …
domain knowledge-assisted convolutional neural network is implemented for evaluating …
Multi-Scale Convolutional LSTM with Transfer Learning for Anomaly Detection in Cellular Networks
The rapid growth in mobile broadband usage and increasing subscribers have made it
crucial to ensure reliable network performance. As mobile networks grow more complex …
crucial to ensure reliable network performance. As mobile networks grow more complex …