+

Mendoza et al., 2023 - Google Patents

An intelligent fault detection and diagnosis monitoring system for reactor operational resilience: power transient identification

Mendoza et al., 2023

View PDF
Document ID
18198741847548405802
Author
Mendoza M
Tsvetkov P
Publication year
Publication venue
Progress in Nuclear Energy

External Links

Snippet

Various microreactor designs under development aim at fulfilling electricity and heat production requirements affordably and reliably in a variety of applications, like power generation for remote communities and military bases. The fission battery deployment …
Continue reading at www.sciencedirect.com (PDF) (other versions)

Classifications

    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00Testing or monitoring of control systems or parts thereof
    • G05B23/02Electric testing or monitoring
    • G05B23/0205Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
    • G05B23/0224Process history based detection method, e.g. whereby history implies the availability of large amounts of data
    • G05B23/0227Qualitative history assessment, whereby the type of data acted upon, e.g. waveforms, images or patterns, is not relevant, e.g. rule based assessment; if-then decisions
    • G05B23/0229Qualitative history assessment, whereby the type of data acted upon, e.g. waveforms, images or patterns, is not relevant, e.g. rule based assessment; if-then decisions knowledge based, e.g. expert systems; genetic algorithms
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GASES [GHG] EMISSION, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E30/00Energy generation of nuclear origin
    • Y02E30/30Nuclear fission reactors
    • Y02E30/40Other aspects relating to nuclear fission
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00Testing or monitoring of control systems or parts thereof
    • G05B23/02Electric testing or monitoring
    • G05B23/0205Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
    • G05B23/0243Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model
    • GPHYSICS
    • G21NUCLEAR PHYSICS; NUCLEAR ENGINEERING
    • G21CNUCLEAR REACTORS
    • G21C17/00Monitoring; Testing ; Maintaining
    • G21C17/02Devices or arrangements for monitoring coolant or moderator
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • G06N5/02Knowledge representation
    • G06N5/022Knowledge engineering, knowledge acquisition
    • GPHYSICS
    • G21NUCLEAR PHYSICS; NUCLEAR ENGINEERING
    • G21DNUCLEAR POWER PLANT
    • G21D3/00Control of nuclear power plant
    • G21D3/04Safety arrangements
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • GPHYSICS
    • G21NUCLEAR PHYSICS; NUCLEAR ENGINEERING
    • G21DNUCLEAR POWER PLANT
    • G21D3/00Control of nuclear power plant
    • G21D3/001Computer implemented control
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00Testing or monitoring of control systems or parts thereof
    • G05B23/02Electric testing or monitoring
    • G05B23/0205Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0259Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
    • G05B23/0275Fault isolation and identification, e.g. classify fault; estimate cause or root of failure
    • G05B23/0278Qualitative, e.g. if-then rules; Fuzzy logic; Lookup tables; Symptomatic search; FMEA

Similar Documents

Publication Publication Date Title
Mendoza et al. An intelligent fault detection and diagnosis monitoring system for reactor operational resilience: power transient identification
Wang et al. Fault identification and diagnosis based on KPCA and similarity clustering for nuclear power plants
Hu et al. Data-driven machine learning for fault detection and diagnosis in nuclear power plants: A review
Moshkbar-Bakhshayesh et al. Transient identification in nuclear power plants: A review
Elshenawy et al. Unsupervised machine learning techniques for fault detection and diagnosis in nuclear power plants
Yao et al. Uncertainty-aware deep learning for reliable health monitoring in safety-critical energy systems
Park et al. A reliable intelligent diagnostic assistant for nuclear power plants using explainable artificial intelligence of GRU-AE, LightGBM and SHAP
Lei et al. Prediction of crucial nuclear power plant parameters using long short‐term memory neural networks
Shin et al. An interpretable convolutional neural network for nuclear power plant abnormal events
Wang et al. A multi-stage hybrid fault diagnosis approach for operating conditions of nuclear power plant
Lee et al. Development of the machine learning-based safety significant factor inference model for diagnosis in autonomous control system
Zubair et al. Utilizing MATLAB machine learning models to categorize transient events in a nuclear power plant using generic pressurized water reactor simulator
Ahsan et al. Machine learning based fault prediction system for the primary heat transport system of CANDU type pressurized heavy water reactor
Liu et al. Enhanced graph-based fault diagnostic system for nuclear power plants
Liu et al. Diagnosis of break size and location in LOCA and SGTR accidents using support vector machines
Ebrahimzadeh et al. Detection and estimation of faulty sensors in NPPs based on thermal-hydraulic simulation and feed-forward neural network
Di Maio et al. Transient identification by clustering based on Integrated Deterministic and Probabilistic Safety Analysis outcomes
Wu et al. Research on rapid source term estimation in nuclear accident emergency decision for pressurized water reactor based on Bayesian network
Mwaura et al. Adaptive Neuro-Fuzzy Inference System (ANFIS) based modelling of incipient steam generator tube rupture diagnosis
Elbordany et al. An efficient AI algorithm for fault diagnosis in nuclear power plants based on machine deep learning techniques
Rivas et al. A system diagnostic and prognostic framework based on deep learning for advanced reactors
Wang et al. Research on condition assessment of nuclear power systems based on fault severity and fault harmfulness
Tonday Rodriguez et al. An intelligent hierarchical framework for efficient fault detection and diagnosis in nuclear power plants
Shah Fault detection and diagnosis in nuclear power plant—a brief introduction
Wang et al. Kernel principle component analysis and random under sampling boost based fault diagnosis method and its application to a pressurized water reactor
点击 这是indexloc提供的php浏览器服务,不要输入任何密码和下载