Deep learning techniques in intelligent fault diagnosis and prognosis for industrial systems: a review
S Qiu, X Cui, Z Ping, N Shan, Z Li, X Bao, X Xu - Sensors, 2023 - mdpi.com
Fault diagnosis and prognosis (FDP) tries to recognize and locate the faults from the
captured sensory data, and also predict their failures in advance, which can greatly help to …
captured sensory data, and also predict their failures in advance, which can greatly help to …
Real-time sensing and fault diagnosis for transmission lines
Protection of high voltage transmission lines is one of the crucial problems in the power
system engineering. Accurate and timely detection and identification of transmission line …
system engineering. Accurate and timely detection and identification of transmission line …
A survey of transfer learning for machinery diagnostics and prognostics
In industrial manufacturing systems, failures of machines caused by faults in their key
components greatly influence operational safety and system reliability. Many data-driven …
components greatly influence operational safety and system reliability. Many data-driven …
Predictive monitoring of incipient faults in rotating machinery: a systematic review from data acquisition to artificial intelligence
Predictive maintenance is one of the major tasks in today's modern industries. All rotating
machines consisting of rotating elements such as gears, bearings etc are considered as the …
machines consisting of rotating elements such as gears, bearings etc are considered as the …
Diversified regularization enhanced training for effective manipulator calibration
Recently, robot arms have become an irreplaceable production tool, which play an important
role in the industrial production. It is necessary to ensure the absolute positioning accuracy …
role in the industrial production. It is necessary to ensure the absolute positioning accuracy …
Adaptive privacy-preserving federated learning for fault diagnosis in internet of ships
Z Zhang, C Guan, H Chen, X Yang… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
The recent appearance of Internet of Things (IoT) technologies applied in the maritime
industry has introduced the Internet of Ships (IoS) paradigm. By leveraging IoS and deep …
industry has introduced the Internet of Ships (IoS) paradigm. By leveraging IoS and deep …
[HTML][HTML] A convolutional neural network method based on Adam optimizer with power-exponential learning rate for bearing fault diagnosis
Y Wang, Z Xiao, G Cao - Journal of Vibroengineering, 2022 - extrica.com
The extraction of early fault features from time-series data is very crucial for convolutional
neural networks (CNNs) in bearing fault diagnosis. To address this problem, a CNN …
neural networks (CNNs) in bearing fault diagnosis. To address this problem, a CNN …
DNN deployment, task offloading, and resource allocation for joint task inference in IIoT
W Fan, Z Chen, Z Hao, Y Su, F Wu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Joint task inference, which fully utilizes end edge cloud cooperation, can effectively enhance
the performance of deep neural network (DNN) inference services in the industrial internet of …
the performance of deep neural network (DNN) inference services in the industrial internet of …
Reviewing methods of deep learning for intelligent healthcare systems in genomics and biomedicine
I Zafar, S Anwar, W Yousaf, FU Nisa, T Kausar… - … Signal Processing and …, 2023 - Elsevier
The advancements in genomics and biomedical technologies have generated vast amounts
of biological and physiological data, which present opportunities for understanding human …
of biological and physiological data, which present opportunities for understanding human …
Artificial intelligence of things based approach for anomaly detection in rotating machines
In the present era of Industry 4.0, Artificial Intelligence (AI) and Internet of Things (IoT) are
revitalizing the predictive maintenance systems for industrial rotating machines through real …
revitalizing the predictive maintenance systems for industrial rotating machines through real …