Predictive maintenance architecture development for nuclear infrastructure using machine learning
Nuclear infrastructure systems play an important role in national security. The functions and
missions of nuclear infrastructure systems are vital to government, businesses, society and …
missions of nuclear infrastructure systems are vital to government, businesses, society and …
Graph convolutional network-based method for fault diagnosis using a hybrid of measurement and prior knowledge
Deep-neural network-based fault diagnosis methods have been widely used according to
the state of the art. However, a few of them consider the prior knowledge of the system of …
the state of the art. However, a few of them consider the prior knowledge of the system of …
Unsupervised machine learning techniques for fault detection and diagnosis in nuclear power plants
Nuclear power plants have proved their importance in the energy sector by generating clean
and uninterrupted energy over decades. Moreover, nuclear power plants (NPPs) are large …
and uninterrupted energy over decades. Moreover, nuclear power plants (NPPs) are large …
A data-driven adaptive fault diagnosis methodology for nuclear power systems based on NSGAII-CNN
C He, D Ge, M Yang, N Yong, J Wang, J Yu - Annals of Nuclear Energy, 2021 - Elsevier
With the development of digital information technology, nuclear energy systems are
develo** in the direction of intelligence and unmanned, which requires a higher demand …
develo** in the direction of intelligence and unmanned, which requires a higher demand …
Framework for fault diagnosis with multi-source sensor nodes in nuclear power plants based on a Bayesian network
Fault detection and diagnosis (FDD) provides safety alarms and diagnostic functions for a
nuclear power plant (NPP), which comprises large and complex systems. Here, a technical …
nuclear power plant (NPP), which comprises large and complex systems. Here, a technical …
[HTML][HTML] Power plant induced-draft fan fault prediction using machine learning stacking ensemble
The improvement of fault prediction and diagnosis in industrial systems is crucial to minimize
unscheduled shutdowns. However, the predictive performance of current models for thermal …
unscheduled shutdowns. However, the predictive performance of current models for thermal …
Data‐driven fault diagnosis approaches for industrial equipment: A review
Undetected and unpredicted faults in heavy industrial machines/equipment can lead to
unwanted failures. Therefore, prediction of faults puts paramount importance on maintaining …
unwanted failures. Therefore, prediction of faults puts paramount importance on maintaining …
[HTML][HTML] Application of monitoring, diagnosis, and prognosis in thermal performance analysis for nuclear power plants
As condition-based maintenance (CBM) has risen as a new trend, there has been an active
movement to apply information technology for effective implementation of CBM in power …
movement to apply information technology for effective implementation of CBM in power …
A framework for monitoring and fault diagnosis in nuclear power plants based on signed directed graph methods
W Guohua, Y Di**, Y Jiyao, X Yiqing… - Frontiers in Energy …, 2021 - frontiersin.org
When nuclear power plants (NPPs) are in a state of failure, they may release radioactive
material into the environment. The safety of NPPs must thus be maintained at a high …
material into the environment. The safety of NPPs must thus be maintained at a high …
Expert knowledge modelling software design based on Signed Directed Graph with the application for PWR fault diagnosis
Z Ma, S Deng, Z Zhou, X Ai, J Zhang, Y Liu… - Annals of Nuclear …, 2024 - Elsevier
Abstract Online monitoring and Fault Diagnosis and Detection (FDD) can help the operator
to enhance the situation awareness. The Signed Directed Graph (SDG) has the significant …
to enhance the situation awareness. The Signed Directed Graph (SDG) has the significant …