Towards efficient and interpretative rolling bearing fault diagnosis via quadratic neural network with BI-LSTM
Y Keshun, W Puzhou, G Yingkui - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
With the widespread application of deep learning in Internet of Things (IoT), remarkable
achievements have been made especially in rolling bearing fault diagnosis in rotating …
achievements have been made especially in rolling bearing fault diagnosis in rotating …
Localization of Coordinated Cyber-Physical Attacks in Power Grids Using Moving Target Defense and Machine Learning
J Yu, Q Li, L Li - Electronics, 2024 - mdpi.com
Coordinated cyber-physical atacks (CCPAs) are dangerously stealthy and have
considerable destructive effects against power grids. The problem of stealthy CCPA …
considerable destructive effects against power grids. The problem of stealthy CCPA …
Extremely Rare Anomaly Detection Pipeline in Semiconductor Bonding Process with Digital Twin-driven Data Augmentation Method
M Jeon, IH Choi, SW Seo… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
With advancements in precise semiconductor manufacturing processes, a new category of
anomalies has increasingly emerged. However, due to the probability of an abnormal …
anomalies has increasingly emerged. However, due to the probability of an abnormal …
Robot Mechanical Fault Diagnosis Method Based on Deep Learning
H Fang, Y Wu, X Ling - 2023 IEEE 16th International …, 2023 - ieeexplore.ieee.org
An image input ResNet-based (IIRB) method for wheeled robot mechanical fault diagnosis
(MFD) is proposed. Firstly, the time series signal (TSS) of the vibration sensor is normalized …
(MFD) is proposed. Firstly, the time series signal (TSS) of the vibration sensor is normalized …