Unsupervised anomaly detection for Nuclear Power Plants based on Denoising Diffusion Probabilistic Models

Shiqiao Liu; Zhenyu Zhu; Xinwen Zhao; Yangguang Wang; Sun Xiang; Lei Yu

doi:10.1016/j.pnucene.2024.105521

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Unsupervised anomaly detection for Nuclear Power Plants based on Denoising Diffusion Probabilistic Models

Shiqiao Liu Zhenyu Zhu Xinwen Zhao Yangguang Wang Sun Xiang Lei Yu

Year: 2024 Journal: Progress in Nuclear Energy Vol: 178 Pages: 105521-105521 Publisher: Elsevier BV

DOI: 10.1016/j.pnucene.2024.105521

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Keywords:

Probabilistic logic Diffusion Computer science Anomaly detection Anomaly (physics) Noise reduction Pattern recognition (psychology) Artificial intelligence Physics Thermodynamics

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Topics

Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Nuclear Engineering Thermal-Hydraulics

Physical Sciences → Engineering → Aerospace Engineering

Risk and Safety Analysis

Social Sciences → Decision Sciences → Statistics, Probability and Uncertainty

Unsupervised anomaly detection for Nuclear Power Plants based on Denoising Diffusion Probabilistic Models

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Citation History

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