4.5 Article

A data-driven adaptive fault diagnosis methodology for nuclear power systems based on NSGAII-CNN

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Nuclear Science & Technology

Advanced fault diagnosis method for nuclear power plant based on convolutional gated recurrent network and enhanced particle swarm optimization

Hang Wang et al.

Summary: A highly accurate and adaptable fault diagnosis technique based on CGRU and EPSO is proposed in this study. By stacking convolutional kernel and GRU, the model can extract local characteristics and learn time-series information, leading to enhanced intelligence and information level in NPP fault diagnosis.

ANNALS OF NUCLEAR ENERGY (2021)

Article Computer Science, Artificial Intelligence

A convolutional neural network model for abnormality diagnosis in a nuclear power plant

Gyumin Lee et al.

Summary: A convolutional neural network model is proposed for abnormality diagnosis in nuclear power plants, utilizing two-channel two-dimensional images to handle real-time data and system states dynamically. Experimental results show the model outperforms other classification models in terms of accuracy and reliability, indicating its potential for real-time diagnosis in actual NPP systems.

APPLIED SOFT COMPUTING (2021)

Article Automation & Control Systems

Multiscale Kernel Based Residual Convolutional Neural Network for Motor Fault Diagnosis Under Nonstationary Conditions

Ruonan Liu et al.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2020)

Article Nuclear Science & Technology

Framework and data management of digital design system for nuclear power

Shentu Jun et al.

ANNALS OF NUCLEAR ENERGY (2019)

Article Engineering, Multidisciplinary

Crack detection of plastic gears using a convolutional neural network pre-learned from images of meshing vibration data with transfer learning

B. H. Kien et al.

FORSCHUNG IM INGENIEURWESEN-ENGINEERING RESEARCH (2019)

Article Automation & Control Systems

Deep residual learning-based fault diagnosis method for rotating machinery

Wei Zhang et al.

ISA TRANSACTIONS (2019)

Article Nuclear Science & Technology

Knowledge base operator support system for nuclear power plant fault diagnosis

Abiodun Ayodeji et al.

PROGRESS IN NUCLEAR ENERGY (2018)

Article Chemistry, Multidisciplinary

End-To-End Convolutional Neural Network Model for Gear Fault Diagnosis Based on Sound Signals

Yong Yao et al.

APPLIED SCIENCES-BASEL (2018)

Article Mathematical & Computational Biology

Image Classification Using Biomimetic Pattern Recognition with Convolutional Neural Networks Features

Liangji Zhou et al.

COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE (2017)

Article Nuclear Science & Technology

Development strategy and conceptual design of China Lead-based Research Reactor

Yican Wu et al.

ANNALS OF NUCLEAR ENERGY (2016)

Article Energy & Fuels

CLEAR-S: an integrated non-nuclear test facility for China lead-based research reactor

Y. Wu

INTERNATIONAL JOURNAL OF ENERGY RESEARCH (2016)

Article Engineering, Mechanical

Clustering for unsupervised fault diagnosis in nuclear turbine shut-down transients

Piero Baraldi et al.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2015)

Article Nuclear Science & Technology

SEMISUPERVISED CLASSIFICATION FOR FAULT DIAGNOSIS IN NUCLEAR POWER PLANTS

Jianping Ma et al.

NUCLEAR ENGINEERING AND TECHNOLOGY (2015)

Article Nuclear Science & Technology

Improvement of fault diagnosis efficiency in nuclear power plants using hybrid intelligence approach

Yong-kuo Liu et al.

PROGRESS IN NUCLEAR ENERGY (2014)

Article Nuclear Science & Technology

Applications of fault detection and diagnosis methods in nuclear power plants: A review

Jianping Ma et al.

PROGRESS IN NUCLEAR ENERGY (2011)

Article Computer Science, Artificial Intelligence

A fast and elitist multiobjective genetic algorithm: NSGA-II

K Deb et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2002)