Prognostics and Health Management in Nuclear Power Plants: An Updated Method-Centric Review With Special Focus on Data-Driven Methods

Zhao, Xingang; Kim, Junyung; Warns, Kyle; Wang, Xinyan; Ramuhalli, Pradeep; Cetiner, Sacit; Kang, Hyun Gook; Golay, Michael

doi:10.3389/fenrg.2021.696785

Title: Prognostics and Health Management in Nuclear Power Plants: An Updated Method-Centric Review With Special Focus on Data-Driven Methods

Journal Article · Tue Jun 15 00:00:00 EDT 2021 · Frontiers in Energy Research

DOI:https://doi.org/10.3389/fenrg.2021.696785· OSTI ID:1807239

^[1]; Kim, Junyung ^[2]; Warns, Kyle ^[2]; Wang, Xinyan ^[3];

^[1];

^[1]; Kang, Hyun Gook ^[2]; Golay, Michael ^[3]

Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Nuclear Energy and Fuel Cycle Division
Rensselaer Polytechnic Inst., Troy, NY (United States). Dept. of Mechanical, Aerospace and Nuclear Engineering
Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States). Dept. of Nuclear Science and Engineering

In a carbon-constrained world, future uses of nuclear power technologies can contribute to climate change mitigation as the installed electricity generating capacity and range of applications could be much greater and more diverse than with the current plants. To preserve the nuclear industry competitiveness in the global energy market, prognostics and health management (PHM) of plant assets is expected to be important for supporting and sustaining improvements in the economics associated with operating nuclear power plants (NPPs) while maintaining their high availability. Of interest are long-term operation of the legacy fleet to 80 years through subsequent license renewals and economic operation of new builds of either light water reactors or advanced reactor designs. Recent advances in data-driven analysis methods—largely represented by those in artificial intelligence and machine learning—have enhanced applications ranging from robust anomaly detection to automated control and autonomous operation of complex systems. The NPP equipment PHM is one area where the application of these algorithmic advances can significantly improve the ability to perform asset management. This paper provides an updated method-centric review of the full PHM suite in NPPs focusing on data-driven methods and advances since the last major survey article was published in 2015. The main approaches and the state of practice are described, including those for the tasks of data acquisition, condition monitoring, diagnostics, prognostics, and planning and decision-making. Research advances in non-nuclear power applications are also included to assess findings that may be applicable to the nuclear industry, along with the opportunities and challenges when adapting these developments to NPPs. Finally, this paper identifies key research needs in regard to data availability and quality, verification and validation, and uncertainty quantification.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1807239

Journal Information:: Frontiers in Energy Research, Vol. 9; ISSN 2296-598X

Publisher:: Frontiers Research FoundationCopyright Statement

Country of Publication:: United States

Language:: English

References (199)

Fault detection and diagnosis for nonlinear systems: A new adaptive Gaussian mixture modeling approach Karami, Majid; Wang, Liping Energy and Buildings, Vol. 166 https://doi.org/10.1016/j.enbuild.2018.02.032	journal	May 2018
Multi-objective adjustment of remaining useful life predictions based on reinforcement learning Kozjek, Dominik; Malus, Andreja; Vrabič, Rok Procedia CIRP, Vol. 93 https://doi.org/10.1016/j.procir.2020.03.051	journal	January 2020
Innovative sensing technologies for nuclear instrumentation Calderoni, Pattrick; Hurley, David; Daw, Josh 2019 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) https://doi.org/10.1109/I2MTC.2019.8827129	conference	May 2019
A Review of Prognostics and Health Management Applications in Nuclear Power Plants Coble, Jamie; Ramuhalli, Pradeep; Bond, Leonard International Journal of Prognostics and Health Management, Vol. 6, Issue 3 https://doi.org/10.36001/ijphm.2015.v6i3.2271	journal	December 2015
Bidirectional handshaking LSTM for remaining useful life prediction Elsheikh, Ahmed; Yacout, Soumaya; Ouali, Mohamed-Salah Neurocomputing, Vol. 323 https://doi.org/10.1016/j.neucom.2018.09.076	journal	January 2019
Use of first order reversal curve measurements to understand Barkhausen noise emission in nuclear steel McCloy, J. S.; Ramuhalli, Pradeep; Henager, Jr., Charles REVIEW OF PROGRESS IN QUANTITATIVE NONDESTRUCTIVE EVALUATION: VOLUME 32, AIP Conference Proceedings https://doi.org/10.1063/1.4789247	conference	January 2013
Bayesian Networks in Fault Diagnosis Cai, Baoping; Huang, Lei; Xie, Min IEEE Transactions on Industrial Informatics, Vol. 13, Issue 5 https://doi.org/10.1109/TII.2017.2695583	journal	October 2017
A review of diagnostic and prognostic capabilities and best practices for manufacturing Vogl, Gregory W.; Weiss, Brian A.; Helu, Moneer Journal of Intelligent Manufacturing, Vol. 30, Issue 1 https://doi.org/10.1007/s10845-016-1228-8	journal	June 2016
Machine Health Monitoring Using Local Feature-Based Gated Recurrent Unit Networks Zhao, Rui; Wang, Dongzhe; Yan, Ruqiang IEEE Transactions on Industrial Electronics, Vol. 65, Issue 2 https://doi.org/10.1109/TIE.2017.2733438	journal	February 2018
Monitoring of pipelines in nuclear power plants by measuring laser-based mechanical impedance Lee, Hyeonseok; Sohn, Hoon; Yang, Suyoung Smart Materials and Structures, Vol. 23, Issue 6 https://doi.org/10.1088/0964-1726/23/6/065008	journal	April 2014
Online Fault Diagnosis for Industrial Processes With Bayesian Network-Based Probabilistic Ensemble Learning Strategy Yu, Wanke; Zhao, Chunhui IEEE Transactions on Automation Science and Engineering, Vol. 16, Issue 4 https://doi.org/10.1109/TASE.2019.2915286	journal	October 2019
An adaptive ARX model to estimate the RUL of aluminum plates based on its crack growth Barraza-Barraza, Diana; Tercero-Gómez, Víctor G.; Beruvides, Mario G. Mechanical Systems and Signal Processing, Vol. 82 https://doi.org/10.1016/j.ymssp.2016.05.041	journal	January 2017
Selecting features for nuclear transients classification by means of genetic algorithms Zio, E.; Baraldi, P.; Pedroni, N. IEEE Transactions on Nuclear Science, Vol. 53, Issue 3 https://doi.org/10.1109/TNS.2006.873868	journal	June 2006
Reconstruction-based contribution approaches for improved fault diagnosis using principal component analysis Mnassri, Baligh; El Adel, El Mostafa; Ouladsine, Mustapha Journal of Process Control, Vol. 33 https://doi.org/10.1016/j.jprocont.2015.06.004	journal	September 2015
Some Theorems on Quadratic Forms Applied in the Study of Analysis of Variance Problems, I. Effect of Inequality of Variance in the One-Way Classification Box, G. E. P. The Annals of Mathematical Statistics, Vol. 25, Issue 2 https://doi.org/10.1214/aoms/1177728786	journal	June 1954
Symptom-Based Conditional Failure Probability Estimation for Selected Structures, Systems, and Components Zhao, Xingang; Golay, Michael Massachusetts Institute of Technology https://doi.org/10.13140/RG.2.2.26898.58569	text	January 2020
Stochastic models for degradation-based reliability Kharoufeh, Jeffrey P.; Cox, Steven M. IIE Transactions, Vol. 37, Issue 6 https://doi.org/10.1080/07408170590929009	journal	June 2005
Development and assessment of a nearly autonomous management and control system for advanced reactors Lin, Linyu; Athe, Paridhi; Rouxelin, Pascal Annals of Nuclear Energy, Vol. 150 https://doi.org/10.1016/j.anucene.2020.107861	journal	January 2021
Semi-Markov models for degradation-based reliability Kharoufeh, Jeffrey P.; Solo, Christopher J.; Ulukus, M. Yasin IIE Transactions, Vol. 42, Issue 8 https://doi.org/10.1080/07408170903394371	journal	May 2010
A convolutional neural network model for abnormality diagnosis in a nuclear power plant Lee, Gyumin; Lee, Seung Jun; Lee, Changyong Applied Soft Computing, Vol. 99 https://doi.org/10.1016/j.asoc.2020.106874	journal	February 2021
A framework analyzing system status and human activities: Illustrated using 2011 Fukushima nuclear power plant accident scenarios Cai, Yinan; Golay, Michael W. Nuclear Engineering and Design, Vol. 373 https://doi.org/10.1016/j.nucengdes.2020.111025	journal	March 2021
Trends in the application of model-based fault detection and diagnosis of technical processes Isermann, R.; Ballé, P. Control Engineering Practice, Vol. 5, Issue 5 https://doi.org/10.1016/S0967-0661(97)00053-1	journal	May 1997
Output-Only Damage Detection of Shear Building Structures Using an Autoregressive Model-Enhanced Optimal Subpattern Assignment Metric Mei, Liu; Li, Huaguan; Zhou, Yunlai Sensors, Vol. 20, Issue 7 https://doi.org/10.3390/s20072050	journal	April 2020
Fault detection, identification and reconstruction of sensors in nuclear power plant with optimized PCA method Li, Wei; Peng, Minjun; Liu, Yongkuo Annals of Nuclear Energy, Vol. 113 https://doi.org/10.1016/j.anucene.2017.11.009	journal	March 2018
Irradiation Testing of Piezoelectric (Aluminum Nitride, Zinc Oxide, and Bismuth Titanate) and Magnetostrictive Sensors (Remendur and Galfenol) Reinhardt, B.; Daw, J.; Tittmann, B. R. IEEE Transactions on Nuclear Science, Vol. 65, Issue 1 https://doi.org/10.1109/TNS.2017.2775163	journal	January 2018
An improved Bayesian network method for fault diagnosis Wang, Yalin; Yang, Haibing; Yuan, Xiaofeng IFAC-PapersOnLine, Vol. 51, Issue 21 https://doi.org/10.1016/j.ifacol.2018.09.443	journal	January 2018
A New Fault Diagnosis and Prognosis Technology for High-Power Lithium-Ion Battery Wu, Chao; Zhu, Chunbo; Ge, Yunwang IEEE Transactions on Plasma Science, Vol. 45, Issue 7 https://doi.org/10.1109/TPS.2017.2706088	journal	July 2017
Optimization of a dynamic uncertain causality graph for fault diagnosis in nuclear power plant Zhao, Yue; Di Maio, Francesco; Zio, Enrico Nuclear Science and Techniques, Vol. 28, Issue 3 https://doi.org/10.1007/s41365-017-0184-0	journal	February 2017
Adaptive floating search methods in feature selection Somol, P.; Pudil, P.; Novovičová, J. Pattern Recognition Letters, Vol. 20, Issue 11-13 https://doi.org/10.1016/S0167-8655(99)00083-5	journal	November 1999
An Application of ASP in Nuclear Engineering: Explaining the Three Mile Island Nuclear Accident Scenario Hanna, Botros N.; Trieu, Ly Ly T.; Son, Tran C. Theory and Practice of Logic Programming, Vol. 20, Issue 6 https://doi.org/10.1017/S1471068420000241	journal	September 2020
Motor Health Monitoring at Standstill Through Impedance Analysis Shin, Sung Min; Choi, Bo H.; Kang, Hyun Gook IEEE Transactions on Industrial Electronics, Vol. 63, Issue 7 https://doi.org/10.1109/TIE.2016.2541089	journal	July 2016
Prognostic and health management for engineering systems: a review of the data‐driven approach and algorithms Sutharssan, Thamo; Stoyanov, Stoyan; Bailey, Chris The Journal of Engineering, Vol. 2015, Issue 7 https://doi.org/10.1049/joe.2014.0303	journal	July 2015
Dimension reduction of process dynamic trends using independent component analysis Li, R. F.; Wang, X. Z. Computers & Chemical Engineering, Vol. 26, Issue 3 https://doi.org/10.1016/S0098-1354(01)00773-6	journal	March 2002
Interval-valued fuzzy spiking neural P systems for fault diagnosis of power transmission networks Wang, Jun; Peng, Hong; Yu, Wenping Engineering Applications of Artificial Intelligence, Vol. 82 https://doi.org/10.1016/j.engappai.2019.03.014	journal	June 2019
Fault detection in the Tennessee Eastman benchmark process using dynamic principal components analysis based on decorrelated residuals (DPCA-DR) Rato, Tiago J.; Reis, Marco S. Chemometrics and Intelligent Laboratory Systems, Vol. 125 https://doi.org/10.1016/j.chemolab.2013.04.002	journal	June 2013
Fusing Competing Prediction Algorithms for Prognostics Goebel, K.; Eklund, N.; Bonanni, P. 2006 IEEE Aerospace Conference https://doi.org/10.1109/AERO.2006.1656116	conference	January 2006
Prognostic and diagnostic monitoring of complex systems for product lifecycle management: Challenges and opportunities Venkatasubramanian, Venkat Computers & Chemical Engineering, Vol. 29, Issue 6 https://doi.org/10.1016/j.compchemeng.2005.02.026	journal	May 2005
Hidden semi-Markov models Yu, Shun-Zheng Artificial Intelligence, Vol. 174, Issue 2 https://doi.org/10.1016/j.artint.2009.11.011	journal	February 2010
Simulation of magnetic hysteresis loops and magnetic Barkhausen noise of α-iron containing nonmagnetic particles Li, Yi; Xu, Ben; Hu, Shenyang AIP Advances, Vol. 5, Issue 7 https://doi.org/10.1063/1.4927548	journal	July 2015
Dynamic independent component analysis approach for fault detection and diagnosis Stefatos, George; Ben Hamza, A. Expert Systems with Applications, Vol. 37, Issue 12 https://doi.org/10.1016/j.eswa.2010.06.101	journal	December 2010
A Survey on Filter Techniques for Feature Selection in Gene Expression Microarray Analysis Lazar, C.; Taminau, J.; Meganck, S. IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol. 9, Issue 4 https://doi.org/10.1109/TCBB.2012.33	journal	July 2012
Novel fault diagnosis scheme utilizing deep learning networks Saeed, Hanan A.; Peng, Min-jun; Wang, Hang Progress in Nuclear Energy, Vol. 118 https://doi.org/10.1016/j.pnucene.2019.103066	journal	January 2020
Machinery Early Fault Detection Based on Dirichlet Process Mixture Model Ma, Bo; Zhao, Yi; Zhang, Ying IEEE Access, Vol. 7 https://doi.org/10.1109/ACCESS.2019.2927104	journal	January 2019
Support vector ensemble for incipient fault diagnosis in nuclear plant components Ayodeji, Abiodun; Liu, Yong-kuo Nuclear Engineering and Technology, Vol. 50, Issue 8 https://doi.org/10.1016/j.net.2018.07.013	journal	December 2018
Visual Vibrometry: Estimating Material Properties from Small Motions in Video Davis, Abe; Bouman, Katherine L.; Chen, Justin G. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 39, Issue 4 https://doi.org/10.1109/TPAMI.2016.2622271	journal	April 2017
Bearing Degradation Evaluation Using Recurrence Quantification Analysis and Kalman Filter Qian, Yuning; Yan, Ruqiang; Hu, Shijie IEEE Transactions on Instrumentation and Measurement, Vol. 63, Issue 11 https://doi.org/10.1109/TIM.2014.2313034	journal	November 2014
Multi-source information fusion based fault diagnosis of ground-source heat pump using Bayesian network Cai, Baoping; Liu, Yonghong; Fan, Qian Applied Energy, Vol. 114 https://doi.org/10.1016/j.apenergy.2013.09.043	journal	February 2014
Putting Together Wavelet-based Scaleograms and Convolutional Neural Networks for Anomaly Detection in Nuclear Reactors Tagaris, Thanos; Ioannou, George; Sdraka, Maria ICAAI 2019: 2019 The 3rd International Conference on Advances in Artificial Intelligence, Proceedings of the 2019 3rd International Conference on Advances in Artificial Intelligence https://doi.org/10.1145/3369114.3369121	conference	January 2020
Probabilistic decision-making under uncertainty for autonomous driving using continuous POMDPs Brechtel, Sebastian; Gindele, Tobias; Dillmann, Rudiger 2014 IEEE 17th International Conference on Intelligent Transportation Systems (ITSC), 17th International IEEE Conference on Intelligent Transportation Systems (ITSC) https://doi.org/10.1109/ITSC.2014.6957722	conference	October 2014
A hybrid fault diagnosis methodology with support vector machine and improved particle swarm optimization for nuclear power plants Wang, Hang; Peng, Min-jun; Wesley Hines, J. ISA Transactions, Vol. 95 https://doi.org/10.1016/j.isatra.2019.05.016	journal	December 2019
A Deep Learning Model for Predictive Maintenance in Cyber-Physical Production Systems Using LSTM Autoencoders Bampoula, Xanthi; Siaterlis, Georgios; Nikolakis, Nikolaos Sensors, Vol. 21, Issue 3 https://doi.org/10.3390/s21030972	journal	February 2021
Deep-learning-based alarm system for accident diagnosis and reactor state classification with probability value Kim, Taek Kyu; Park, Jae Kwan; Lee, Byeong Hee Annals of Nuclear Energy, Vol. 133 https://doi.org/10.1016/j.anucene.2019.07.022	journal	November 2019
Patterning piezoelectric thin film PVDF–TrFE based pressure sensor for catheter application Sharma, Tushar; Je, Sang-Soo; Gill, Brijesh Sensors and Actuators A: Physical, Vol. 177 https://doi.org/10.1016/j.sna.2011.08.019	journal	April 2012
Gated recurrent unit based recurrent neural network for remaining useful life prediction of nonlinear deterioration process Chen, Jinglong; Jing, Hongjie; Chang, Yuanhong Reliability Engineering & System Safety, Vol. 185 https://doi.org/10.1016/j.ress.2019.01.006	journal	May 2019
Data fusion and machine learning for industrial prognosis: Trends and perspectives towards Industry 4.0 Diez-Olivan, Alberto; Del Ser, Javier; Galar, Diego Information Fusion, Vol. 50 https://doi.org/10.1016/j.inffus.2018.10.005	journal	October 2019
A plant-wide industrial process control problem Downs, J. J.; Vogel, E. F. Computers & Chemical Engineering, Vol. 17, Issue 3 https://doi.org/10.1016/0098-1354(93)80018-I	journal	March 1993
Performing Feature Selection With Multilayer Perceptrons Romero, E.; Sopena, J. M. IEEE Transactions on Neural Networks, Vol. 19, Issue 3 https://doi.org/10.1109/TNN.2007.909535	journal	March 2008
Learning to Monitor Machine Health with Convolutional Bi-Directional LSTM Networks Zhao, Rui; Yan, Ruqiang; Wang, Jinjiang Sensors, Vol. 17, Issue 2 https://doi.org/10.3390/s17020273	journal	January 2017
A common cause failure model for components under age-related degradation Zhou, Taotao; Droguett, Enrique López; Modarres, Mohammad Reliability Engineering & System Safety, Vol. 195 https://doi.org/10.1016/j.ress.2019.106699	journal	March 2020
On the prediction of critical heat flux using a physics-informed machine learning-aided framework Zhao, Xingang; Shirvan, Koroush; Salko, Robert K. Applied Thermal Engineering, Vol. 164 https://doi.org/10.1016/j.applthermaleng.2019.114540	journal	January 2020
Uncertainty Management for Diagnostics and Prognostics of Batteries using Bayesian Techniques Saha, Bhaskar; Goebel, Kai 2008 IEEE Aerospace Conference https://doi.org/10.1109/AERO.2008.4526631	conference	March 2008
Loose parts detection method combining blind deconvolution with support vector machine Meng, Jianlin; Su, Youbiao; Xie, Shilin Annals of Nuclear Energy, Vol. 149 https://doi.org/10.1016/j.anucene.2020.107782	journal	December 2020
Semiparametric PCA and bayesian network based process fault diagnosis technique Wang, Yazhen; Liu, Yi; Khan, Faisal The Canadian Journal of Chemical Engineering, Vol. 95, Issue 9 https://doi.org/10.1002/cjce.22829	journal	April 2017
Investigating the performance of the supervised learning algorithms for estimating NPPs parameters in combination with the different feature selection techniques Moshkbar-Bakhshayesh, Khalil Annals of Nuclear Energy, Vol. 158 https://doi.org/10.1016/j.anucene.2021.108299	journal	August 2021
Research on intelligent fault diagnosis method for nuclear power plant based on correlation analysis and deep belief network Peng, Bin-Sen; Xia, Hong; Liu, Yong-Kuo Progress in Nuclear Energy, Vol. 108 https://doi.org/10.1016/j.pnucene.2018.06.003	journal	September 2018
An impedance-based diameter gauge for in-pile fuel deformation measurements Fleming, Austin; Al Rashdan, Ahmad; Jensen, Colby Instrumentation Science & Technology, Vol. 47, Issue 6 https://doi.org/10.1080/10739149.2019.1616207	journal	May 2019
Prognostics and Health Management for Maintenance Practitioners - Review, Implementation and Tools Evaluation Atamuradov, Vepa; Medjaher, Kamal; Dersin, Pierre International Journal of Prognostics and Health Management, Vol. 8, Issue 3 https://doi.org/10.36001/ijphm.2017.v8i3.2667	journal	December 2017
Knowledge base operator support system for nuclear power plant fault diagnosis Ayodeji, Abiodun; Liu, Yong-kuo; Xia, Hong Progress in Nuclear Energy, Vol. 105 https://doi.org/10.1016/j.pnucene.2017.12.013	journal	May 2018
Recent advances in sensor fault diagnosis: A review Li, Daoliang; Wang, Ying; Wang, Jinxing Sensors and Actuators A: Physical, Vol. 309 https://doi.org/10.1016/j.sna.2020.111990	journal	July 2020
Irradiation Campaign in the EOLE Critical Facility of Fiber Optic Bragg Gratings Dedicated to the Online Temperature Measurement in Zero Power Research Reactors Morana, Adriana; Mellier, Frederic; Cheymol, Guy IEEE Transactions on Nuclear Science, Vol. 63, Issue 6 https://doi.org/10.1109/TNS.2016.2618906	journal	December 2016
A novel wrapper method for feature selection and its applications Chen, Gang; Chen, Jin Neurocomputing, Vol. 159 https://doi.org/10.1016/j.neucom.2015.01.070	journal	July 2015
PWM-VSI Fault Diagnosis for a PMSM Drive Based on the Fuzzy Logic Approach Yan, Hao; Xu, Yongxiang; Cai, Feiyang IEEE Transactions on Power Electronics, Vol. 34, Issue 1 https://doi.org/10.1109/TPEL.2018.2814615	journal	January 2019
A Novel Dynamic-Weighted Probabilistic Support Vector Regression-Based Ensemble for Prognostics of Time Series Data Liu, Jie; Vitelli, Valeria; Zio, Enrico IEEE Transactions on Reliability, Vol. 64, Issue 4 https://doi.org/10.1109/TR.2015.2427156	journal	December 2015
Bayesian network approach to fault diagnosis of a hydroelectric generation system Xu, Beibei; Li, Huanhuan; Pang, Wentai Energy Science & Engineering, Vol. 7, Issue 5 https://doi.org/10.1002/ese3.383	journal	June 2019
Statistical fault detection using PCA-based GLR hypothesis testing Harrou, Fouzi; Nounou, Mohamed N.; Nounou, Hazem N. Journal of Loss Prevention in the Process Industries, Vol. 26, Issue 1 https://doi.org/10.1016/j.jlp.2012.10.003	journal	January 2013
A nonlinear quality-related fault detection approach based on modified kernel partial least squares Jiao, Jianfang; Zhao, Ning; Wang, Guang ISA Transactions, Vol. 66 https://doi.org/10.1016/j.isatra.2016.10.015	journal	January 2017
Identifying the most Informative Variables for Decision-Making Problems - a Survey of Recent Approaches and Accompanying Problems Pudil, Pavel; Somol, Petr Acta Oeconomica Pragensia, Vol. 16, Issue 4 https://doi.org/10.18267/j.aop.131	journal	August 2008
Kernel approaches for fault detection and classification in PARR-2 Jamil, F.; Abid, M.; Adil, M. Journal of Process Control, Vol. 64 https://doi.org/10.1016/j.jprocont.2018.01.003	journal	April 2018
False alarm reducing in PCA method for sensor fault detection in a nuclear power plant Li, Wei; Peng, Minjun; Wang, Qingzhong Annals of Nuclear Energy, Vol. 118 https://doi.org/10.1016/j.anucene.2018.04.012	journal	August 2018
A data-model-fusion prognostic framework for dynamic system state forecasting Liu, J.; Wang, W.; Ma, F. Engineering Applications of Artificial Intelligence, Vol. 25, Issue 4 https://doi.org/10.1016/j.engappai.2012.02.015	journal	June 2012
Uncertainty Quantification in Prognostic Health Management Systems Dewey, H. Heath; DeVries, Derek R.; Hyde, Scott R. 2019 IEEE Aerospace Conference https://doi.org/10.1109/AERO.2019.8741821	conference	March 2019
A New Hybrid Prognostic Methodology Eker, Omer F.; Camci, Fatih; Jennions, Ian K. International Journal of Prognostics and Health Management, Vol. 10, Issue 2 https://doi.org/10.36001/ijphm.2019.v10i2.2727	journal	June 2019
Benchmark for filter methods for feature selection in high-dimensional classification data Bommert, Andrea; Sun, Xudong; Bischl, Bernd Computational Statistics & Data Analysis, Vol. 143 https://doi.org/10.1016/j.csda.2019.106839	journal	March 2020
Sensing capabilities of piezoelectric wafer active sensors in extreme nuclear environment Faisal Haider, Mohammad; Lin, Bin; Yu, Lingyu SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, SPIE Proceedings https://doi.org/10.1117/12.2260162	conference	April 2017
Machinery health prognostics: A systematic review from data acquisition to RUL prediction Lei, Yaguo; Li, Naipeng; Guo, Liang Mechanical Systems and Signal Processing, Vol. 104 https://doi.org/10.1016/j.ymssp.2017.11.016	journal	May 2018
Prediction of the Mechanical Properties of P91 Steel by Means of Magneto-acoustic Emission and Acoustic Birefringence Makowska, Katarzyna; Piotrowski, Leszek; Kowalewski, Zbigniew Ludwik Journal of Nondestructive Evaluation, Vol. 36, Issue 2 https://doi.org/10.1007/s10921-017-0421-9	journal	May 2017
Particle swarm optimization Kennedy, J.; Eberhart, R. Proceedings of ICNN'95 - International Conference on Neural Networks https://doi.org/10.1109/ICNN.1995.488968	conference	January 1995
Fault Diagnosis of Nuclear Power Plant Based on Simplified Signed Directed Graph with Principal Component Analysis and Support Vector Machine Xin, Ma; Jiao, Wu; Da-zi, Li 2019 Chinese Automation Congress (CAC) https://doi.org/10.1109/CAC48633.2019.8997001	conference	November 2019
Fuzzy Logic Expert System for Incipient Fault Diagnosis of Power Transformers Husain, Zakir International Journal on Electrical Engineering and Informatics, Vol. 10, Issue 2 https://doi.org/10.15676/ijeei.2018.10.2.8	journal	June 2018
Data driven approach for fault detection and diagnosis of turbine in thermal power plant using Independent Component Analysis (ICA) Ajami, Ali; Daneshvar, Mahdi International Journal of Electrical Power & Energy Systems, Vol. 43, Issue 1 https://doi.org/10.1016/j.ijepes.2012.06.022	journal	December 2012
Feature Selection and Classification of Hyperspectral Images With Support Vector Machines Archibald, Rick; Fann, George IEEE Geoscience and Remote Sensing Letters, Vol. 4, Issue 4 https://doi.org/10.1109/LGRS.2007.905116	journal	October 2007
Visualization of back surface defects by piezoelectric film Komagome, Yuji; Matsumoto, Eiji International Journal of Applied Electromagnetics and Mechanics, Vol. 14, Issue 1-4 https://doi.org/10.3233/jae-2002-418	journal	December 2002
Toward identifying crack-length-related resonances in acoustic emission waveforms for structural health monitoring applications Bhuiyan, Md Yeasin; Bao, Jingjing; Poddar, Banibrata Structural Health Monitoring, Vol. 17, Issue 3 https://doi.org/10.1177/1475921717707356	journal	April 2017
Ensemble Learning-based Fault Detection in Nuclear Power Plant Screen Cleaners Deleplace, A.; Atamuradov, V.; Allali, A. IFAC-PapersOnLine, Vol. 53, Issue 2 https://doi.org/10.1016/j.ifacol.2020.12.2773	journal	January 2020
Fault detection with Conditional Gaussian Network Atoui, Mohamed Amine; Verron, Sylvain; Kobi, Abdessamad Engineering Applications of Artificial Intelligence, Vol. 45 https://doi.org/10.1016/j.engappai.2015.07.020	journal	October 2015
A review on the application of deep learning in system health management Khan, Samir; Yairi, Takehisa Mechanical Systems and Signal Processing, Vol. 107 https://doi.org/10.1016/j.ymssp.2017.11.024	journal	July 2018
Sensor fault detection, isolation and reconstruction in nuclear power plants Lin, Ting-Han; Wu, Shun-Chi Annals of Nuclear Energy, Vol. 126 https://doi.org/10.1016/j.anucene.2018.11.044	journal	April 2019
A fault diagnosis method based on signed directed graph and matrix for nuclear power plants Liu, Yong-Kuo; Wu, Guo-Hua; Xie, Chun-Li Nuclear Engineering and Design, Vol. 297 https://doi.org/10.1016/j.nucengdes.2015.11.016	journal	February 2016
The effects of the structure characteristics on Magnetic Barkhausen noise in commercial steels Deng, Yu; Li, Zhe; Chen, Juan Journal of Magnetism and Magnetic Materials, Vol. 451 https://doi.org/10.1016/j.jmmm.2017.11.041	journal	April 2018
A Critical Analysis of Crack Propagation Laws Paris, P.; Erdogan, F. Journal of Basic Engineering, Vol. 85, Issue 4 https://doi.org/10.1115/1.3656900	journal	December 1963
Development and Assessment of Physics-guided Machine Learning for Prognosis System Lin, L.; Dinh, N.; Gurgen, A. 2020 ANS Virtual Winter Meeting, Transactions of the American Nuclear Society - Volume 123 https://doi.org/10.13182/T123-33503	conference	January 2020
Robust on-line diagnosis tool for the early accident detection in nuclear power plants Tolo, Silvia; Tian, Xiange; Bausch, Nils Reliability Engineering & System Safety, Vol. 186 https://doi.org/10.1016/j.ress.2019.02.015	journal	June 2019
Self-driving cars: A survey Badue, Claudine; Guidolini, Rânik; Carneiro, Raphael Vivacqua Expert Systems with Applications, Vol. 165 https://doi.org/10.1016/j.eswa.2020.113816	journal	March 2021
A Deep Learning Method for Fault Detection of Autonomous Vehicles Ren, Jing; Ren, Rui; Green, Mark 2019 14th International Conference on Computer Science & Education (ICCSE) https://doi.org/10.1109/ICCSE.2019.8845483	conference	August 2019
Stochastic modelling and analysis of degradation for highly reliable products: Z.-S. YE AND M. XIE Ye, Zhi-Sheng; Xie, Min Applied Stochastic Models in Business and Industry, Vol. 31, Issue 1 https://doi.org/10.1002/asmb.2063	journal	October 2014
Remaining useful life prediction based on health index similarity Liu, Yingchao; Hu, Xiaofeng; Zhang, Wenjuan Reliability Engineering & System Safety, Vol. 185 https://doi.org/10.1016/j.ress.2019.02.002	journal	May 2019
A review of prognostics and health management of machine tools Baur, Marco; Albertelli, Paolo; Monno, Michele The International Journal of Advanced Manufacturing Technology, Vol. 107, Issue 5-6 https://doi.org/10.1007/s00170-020-05202-3	journal	March 2020
Utilizing uncertainty information in remaining useful life estimation via Bayesian neural networks and Hamiltonian Monte Carlo Benker, Maximilian; Furtner, Lukas; Semm, Thomas Journal of Manufacturing Systems https://doi.org/10.1016/j.jmsy.2020.11.005	journal	December 2020
On Applications of Spiking Neural P Systems Fan, Songhai; Paul, Prithwineel; Wu, Tianbao Applied Sciences, Vol. 10, Issue 20 https://doi.org/10.3390/app10207011	journal	October 2020
Physics-Informed Neural Networks for Missing Physics Estimation in Cumulative Damage Models: A Case Study in Corrosion Fatigue Dourado, Arinan; Viana, Felipe A. C. Journal of Computing and Information Science in Engineering, Vol. 20, Issue 6 https://doi.org/10.1115/1.4047173	journal	June 2020
Long short-term memory for machine remaining life prediction Zhang, Jianjing; Wang, Peng; Yan, Ruqiang Journal of Manufacturing Systems, Vol. 48 https://doi.org/10.1016/j.jmsy.2018.05.011	journal	July 2018
Metrics for Offline Evaluation of Prognostic Performance Saxena, Abhinav; Celaya, Jose; Saha, Bhaskar International Journal of Prognostics and Health Management, Vol. 1, Issue 1 https://doi.org/10.36001/ijphm.2010.v1i1.1336	journal	January 2010
An intelligent hybrid methodology of on-line system-level fault diagnosis for nuclear power plant Peng, Min-jun; Wang, Hang; Chen, Shan-shan Nuclear Engineering and Technology, Vol. 50, Issue 3 https://doi.org/10.1016/j.net.2017.11.014	journal	April 2018
Robot task plan representation by Petri nets: modelling, identification, analysis and execution Costelha, Hugo; Lima, Pedro Autonomous Robots, Vol. 33, Issue 4 https://doi.org/10.1007/s10514-012-9288-x	journal	March 2012
A cascade intelligent fault diagnostic technique for nuclear power plants Yong-kuo, Liu; Abiodun, Ayodeji; Zhi-bin, Wen Journal of Nuclear Science and Technology, Vol. 55, Issue 3 https://doi.org/10.1080/00223131.2017.1394228	journal	October 2017
Impact Monitoring for Aircraft Smart Composite Skins Based on a Lightweight Sensor Network and Characteristic Digital Sequences Qiu, Lei; Deng, Xiaolei; Yuan, Shenfang Sensors, Vol. 18, Issue 7 https://doi.org/10.3390/s18072218	journal	July 2018
Remaining useful life estimation of engineered systems using vanilla LSTM neural networks Wu, Yuting; Yuan, Mei; Dong, Shaopeng Neurocomputing, Vol. 275 https://doi.org/10.1016/j.neucom.2017.05.063	journal	January 2018
Damage Mechanics Approach for Bearing Lifetime Prognostics Qiu, Jing; Seth, Brij B.; Liang, Steven Y. Mechanical Systems and Signal Processing, Vol. 16, Issue 5 https://doi.org/10.1006/mssp.2002.1483	journal	September 2002
Quality-related fault detection approach based on dynamic kernel partial least squares Jia, Qilong; Zhang, Yingwei Chemical Engineering Research and Design, Vol. 106 https://doi.org/10.1016/j.cherd.2015.12.015	journal	February 2016
A review of feature selection techniques in bioinformatics Saeys, Y.; Inza, I.; Larranaga, P. Bioinformatics, Vol. 23, Issue 19 https://doi.org/10.1093/bioinformatics/btm344	journal	August 2007
Modernizing risk assessment: A systematic integration of PRA and PHM techniques Moradi, Ramin; Groth, Katrina M. Reliability Engineering & System Safety, Vol. 204 https://doi.org/10.1016/j.ress.2020.107194	journal	December 2020
A Belief Rule-Based Expert System for Fault Diagnosis of Marine Diesel Engines Xu, Xiaojian; Yan, Xinping; Sheng, Chenxing IEEE Transactions on Systems, Man, and Cybernetics: Systems https://doi.org/10.1109/TSMC.2017.2759026	journal	January 2017
Deep separable convolutional network for remaining useful life prediction of machinery Wang, Biao; Lei, Yaguo; Li, Naipeng Mechanical Systems and Signal Processing, Vol. 134 https://doi.org/10.1016/j.ymssp.2019.106330	journal	December 2019
Evaluation of Enhanced Risk Monitors for Use on Advanced Reactors Ramuhalli, Pradeep; Veeramany, Arun; Bonebrake, Christopher A. 2016 24th International Conference on Nuclear Engineering, Volume 4: Computational Fluid Dynamics (CFD) and Coupled Codes; Decontamination and Decommissioning, Radiation Protection, Shielding, and Waste Management; Workforce Development, Nuclear Education and Public Acceptance; Mitigation Strategies for Beyond Design Basis Events; Risk Management https://doi.org/10.1115/ICONE24-60040	conference	October 2016
Sensors incipient fault detection and isolation of nuclear power plant using extended Kalman filter and Kullback–Leibler divergence Gautam, Suryakant; Tamboli, Prakash K.; Roy, Kallol ISA Transactions, Vol. 92 https://doi.org/10.1016/j.isatra.2019.02.011	journal	September 2019
Deep learning for prognostics and health management: State of the art, challenges, and opportunities Rezaeianjouybari, Behnoush; Shang, Yi Measurement, Vol. 163 https://doi.org/10.1016/j.measurement.2020.107929	journal	October 2020
The 2 °C Global Temperature Target and the Evolution of the Long-Term Goal of Addressing Climate Change—From the United Nations Framework Convention on Climate Change to the Paris Agreement Gao, Yun; Gao, Xiang; Zhang, Xiaohua Engineering, Vol. 3, Issue 2 https://doi.org/10.1016/J.ENG.2017.01.022	journal	April 2017
A scalable fuzzy support vector machine for fault detection in transportation systems Liu, Jie; Zio, Enrico Expert Systems with Applications, Vol. 102 https://doi.org/10.1016/j.eswa.2018.02.017	journal	July 2018
An autonomous control framework for advanced reactors Wood, Richard T.; Upadhyaya, Belle R.; Floyd, Dan C. Nuclear Engineering and Technology, Vol. 49, Issue 5 https://doi.org/10.1016/j.net.2017.07.001	journal	August 2017
Improved Kalman Filtering-Based Information Fusion for Crack Monitoring Using Piezoelectric-Fiber Hybrid Sensor Network Wang, Yishou; He, Mengyue; Sun, Lei Frontiers in Materials, Vol. 7 https://doi.org/10.3389/fmats.2020.00300	journal	August 2020
Prognostics and life beyond 60 years for nuclear power plants Bond, Leonard J.; Ramuhalli, Pradeep; Tawfik, Magdy S. 2011 IEEE Conference on Prognostics and Health Management (PHM) https://doi.org/10.1109/ICPHM.2011.6024316	conference	June 2011
Rule - based Fault Diagnosis Expert System for Wind Turbine Deng, Xiao-Wen; Gao, Qing-Shui; Zhang, Chu ITM Web of Conferences, Vol. 11 https://doi.org/10.1051/itmconf/20171107005	journal	January 2017
On-line fault detection of a fuel rod temperature measurement sensor in a nuclear reactor core using ANNs Messai, A.; Mellit, A.; Abdellani, I. Progress in Nuclear Energy, Vol. 79 https://doi.org/10.1016/j.pnucene.2014.10.013	journal	March 2015
A survey on feature selection methods Chandrashekar, Girish; Sahin, Ferat Computers & Electrical Engineering, Vol. 40, Issue 1 https://doi.org/10.1016/j.compeleceng.2013.11.024	journal	January 2014
On-line monitoring applications in nuclear power plants Hashemian, H. M. Progress in Nuclear Energy, Vol. 53, Issue 2 https://doi.org/10.1016/j.pnucene.2010.08.003	journal	March 2011
Perspectives on process monitoring of industrial systems Severson, Kristen; Chaiwatanodom, Paphonwit; Braatz, Richard D. Annual Reviews in Control, Vol. 42 https://doi.org/10.1016/j.arcontrol.2016.09.001	journal	January 2016
A New Fuzzy Logic Classifier Based on Multiscale Permutation Entropy and Its Application in Bearing Fault Diagnosis Du, Wenhua; Guo, Xiaoming; Wang, Zhijian Entropy, Vol. 22, Issue 1 https://doi.org/10.3390/e22010027	journal	December 2019
Stanley: The robot that won the DARPA Grand Challenge Thrun, Sebastian; Montemerlo, Mike; Dahlkamp, Hendrik Journal of Field Robotics, Vol. 23, Issue 9 https://doi.org/10.1002/rob.20147	journal	January 2006
SVM-RFE With MRMR Filter for Gene Selection Mundra, P. A.; Rajapakse, J. C. IEEE Transactions on NanoBioscience, Vol. 9, Issue 1 https://doi.org/10.1109/TNB.2009.2035284	journal	March 2010
Remaining Useful Life Prediction using Deep Learning Approaches: A Review Wang, Youdao; Zhao, Yifan; Addepalli, Sri Procedia Manufacturing, Vol. 49 https://doi.org/10.1016/j.promfg.2020.06.015	journal	January 2020
Damage localization in metallic plate structures using edge-reflected lamb waves Ebrahimkhanlou, A.; Dubuc, B.; Salamone, S. Smart Materials and Structures, Vol. 25, Issue 8 https://doi.org/10.1088/0964-1726/25/8/085035	journal	July 2016
A radically data-driven method for fault detection and diagnosis in wind turbines Yu, D.; Chen, Z. M.; Xiahou, K. S. International Journal of Electrical Power & Energy Systems, Vol. 99 https://doi.org/10.1016/j.ijepes.2018.01.009	journal	July 2018
Estimation of Bearing Remaining Useful Life Based on Multiscale Convolutional Neural Network Zhu, Jun; Chen, Nan; Peng, Weiwen IEEE Transactions on Industrial Electronics, Vol. 66, Issue 4 https://doi.org/10.1109/TIE.2018.2844856	journal	April 2019
On the role of Prognostics and Health Management in advanced maintenance systems Guillén, A. J.; Crespo, A.; Macchi, M. Production Planning & Control, Vol. 27, Issue 12 https://doi.org/10.1080/09537287.2016.1171920	journal	April 2016
Multi-core cable fault diagnosis using cluster time-frequency domain reflectometry Lee, Chun-Kwon; Shin, Yong-June 2018 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) https://doi.org/10.1109/I2MTC.2018.8409561	conference	May 2018
On the Computational Power of Spiking Neural P Systems with Self-Organization Wang, Xun; Song, Tao; Gong, Faming Scientific Reports, Vol. 6, Issue 1 https://doi.org/10.1038/srep27624	journal	June 2016
Video Camera–Based Vibration Measurement for Civil Infrastructure Applications Chen, Justin G.; Davis, Abe; Wadhwa, Neal Journal of Infrastructure Systems, Vol. 23, Issue 3 https://doi.org/10.1061/(ASCE)IS.1943-555X.0000348	journal	September 2017
In situ Barely Visible Impact Damage detection and localization for composite structures using surface mounted and embedded PZT transducers: A comparative study Dziendzikowski, M.; Kurnyta, A.; Dragan, K. Mechanical Systems and Signal Processing, Vol. 78 https://doi.org/10.1016/j.ymssp.2015.09.021	journal	October 2016
Parallel PCA–KPCA for nonlinear process monitoring Jiang, Qingchao; Yan, Xuefeng Control Engineering Practice, Vol. 80 https://doi.org/10.1016/j.conengprac.2018.07.012	journal	November 2018
Comparison of Computational Prognostic Methods for Complex Systems Under Dynamic Regimes: A Review of Perspectives Bektas, Oguz; Marshall, Jane; Jones, Jeffrey A. Archives of Computational Methods in Engineering, Vol. 27, Issue 4 https://doi.org/10.1007/s11831-019-09339-7	journal	May 2019
Industry 4.0: Some Challenges and Opportunities for Reliability Engineering Farsi, Mohammad Ali; Zio, Enrico International Journal of Reliability, Risk and Safety: Theory and Application, Vol. 2, Issue 1 https://doi.org/10.30699/IJRRS.2.1.4	journal	December 2019
A nonlinear kernel Gaussian mixture model based inferential monitoring approach for fault detection and diagnosis of chemical processes Yu, Jie Chemical Engineering Science, Vol. 68, Issue 1 https://doi.org/10.1016/j.ces.2011.10.011	journal	January 2012
Prognostics, from the need to reality-from the fleet users and PHM system designer/developers perspectives Hess, A. 2002 IEEE Aerospace Conference, Proceedings, IEEE Aerospace Conference https://doi.org/10.1109/AERO.2002.1036118	conference	January 2002
Review of Hybrid Prognostics Approaches for Remaining Useful Life Prediction of Engineered Systems, and an Application to Battery Life Prediction Liao, Linxia; Kottig, Felix IEEE Transactions on Reliability, Vol. 63, Issue 1 https://doi.org/10.1109/TR.2014.2299152	journal	March 2014
Online Performance Assessment Method for a Model-Based Prognostic Approach Hu, Yang; Baraldi, Piero; Di Maio, Francesco IEEE Transactions on Reliability, Vol. 65, Issue 2 https://doi.org/10.1109/TR.2015.2500681	journal	June 2016
Gene Selection for Cancer Classification using Support Vector Machines Guyon, Isabelle; Weston, Jason; Barnhill, Stephen Machine Learning, Vol. 46, Issue 1/3, p. 389-422 https://doi.org/10.1023/A:1012487302797	journal	January 2002
Q-statistic and T2-statistic PCA-based measures for damage assessment in structures Mujica, Le; Rodellar, J.; Fernández, A. Structural Health Monitoring, Vol. 10, Issue 5 https://doi.org/10.1177/1475921710388972	journal	November 2010
SW-ELM: A summation wavelet extreme learning machine algorithm with a priori parameter initialization Javed, Kamran; Gouriveau, Rafael; Zerhouni, Noureddine Neurocomputing, Vol. 123 https://doi.org/10.1016/j.neucom.2013.07.021	journal	January 2014
A hybrid piezoelectric/fiber optic diagnostic system for structural health monitoring Qing, Xinlin; Kumar, Amrita; Zhang, Chang Smart Materials and Structures, Vol. 14, Issue 3 https://doi.org/10.1088/0964-1726/14/3/012	journal	May 2005
Embedded feature-selection support vector machine for driving pattern recognition Zhang, Xing; Wu, Guang; Dong, Zuomin Journal of the Franklin Institute, Vol. 352, Issue 2 https://doi.org/10.1016/j.jfranklin.2014.04.021	journal	February 2015
Self-maintenance and engineering immune systems: Towards smarter machines and manufacturing systems Lee, J.; Ghaffari, M.; Elmeligy, S. Annual Reviews in Control, Vol. 35, Issue 1 https://doi.org/10.1016/j.arcontrol.2011.03.007	journal	April 2011
Feature selection with neural networks Verikas, A.; Bacauskiene, M. Pattern Recognition Letters, Vol. 23, Issue 11 https://doi.org/10.1016/S0167-8655(02)00081-8	journal	September 2002
Acoustic source localization in an anisotropic plate without knowing its material properties – A new approach Park, Won Hyun; Packo, Pawel; Kundu, Tribikram Ultrasonics, Vol. 79 https://doi.org/10.1016/j.ultras.2017.02.021	journal	August 2017
Fault diagnosis in induction motor using fuzzy logic Shetgaonkar, Satej Santosh 2017 International Conference on Computing Methodologies and Communication (ICCMC) https://doi.org/10.1109/ICCMC.2017.8282693	conference	July 2017
Framework for fault diagnosis with multi-source sensor nodes in nuclear power plants based on a Bayesian network Wu, Guohua; Tong, Jiejuan; Zhang, Liguo Annals of Nuclear Energy, Vol. 122 https://doi.org/10.1016/j.anucene.2018.08.050	journal	December 2018
Rolling bearing health prognosis using a modified health index based hierarchical gated recurrent unit network Li, Xingqiu; Jiang, Hongkai; Xiong, Xiong Mechanism and Machine Theory, Vol. 133 https://doi.org/10.1016/j.mechmachtheory.2018.11.005	journal	March 2019
A survey of the state of condition-based maintenance (CBM) in the nuclear power industry Ayo-Imoru, R. M.; Cilliers, A. C. Annals of Nuclear Energy, Vol. 112 https://doi.org/10.1016/j.anucene.2017.10.010	journal	February 2018
Data-driven root cause diagnosis of faults in process industries Li, Gang; Qin, S. Joe; Yuan, Tao Chemometrics and Intelligent Laboratory Systems, Vol. 159 https://doi.org/10.1016/j.chemolab.2016.09.006	journal	December 2016
Review of Recent Research on Data-Based Process Monitoring Ge, Zhiqiang; Song, Zhihuan; Gao, Furong Industrial & Engineering Chemistry Research, Vol. 52, Issue 10 https://doi.org/10.1021/ie302069q	journal	February 2013
Debonding Detection in Hidden Frame Supported Glass Curtain Walls Using the Nonlinear Ultrasonic Modulation Method with Piezoceramic Transducers Hong, Xiaobin; Liu, Yuan; Liufu, Yonghong Sensors, Vol. 18, Issue 7 https://doi.org/10.3390/s18072094	journal	June 2018
Improved PCA method for sensor fault detection and isolation in a nuclear power plant Li, Wei; Peng, Minjun; Wang, Qingzhong Nuclear Engineering and Technology, Vol. 51, Issue 1 https://doi.org/10.1016/j.net.2018.08.020	journal	February 2019
Diagnosis of operational failures and on-demand failures in nuclear power plants: An approach based on dynamic Bayesian networks Zhao, Yunfei; Tong, Jiejuan; Zhang, Liguo Annals of Nuclear Energy, Vol. 138 https://doi.org/10.1016/j.anucene.2019.107181	journal	April 2020
Structural Health Monitoring with Piezoelectric Wafer Active Sensors for Space Applications Cuc, Adrian; Giurgiutiu, Victor; Joshi, Shiv AIAA Journal, Vol. 45, Issue 12 https://doi.org/10.2514/1.26141	journal	December 2007
Nuclear Power Plant Thermocouple Sensor Fault Detection and Classification using Deep Learning and Generalized Likelihood Ratio Test Mandal, Shyamapada; Santhi, B.; Sridhar, S. IEEE Transactions on Nuclear Science https://doi.org/10.1109/TNS.2017.2697919	journal	January 2017
An approach to multiple fault diagnosis using fuzzy logic Rodríguez Ramos, Adrián; Domínguez Acosta, Carlos; Rivera Torres, Pedro J. Journal of Intelligent Manufacturing, Vol. 30, Issue 1 https://doi.org/10.1007/s10845-016-1256-4	journal	August 2016
A Physics-informed Neural Network for Wind Turbine Main Bearing Fatigue Yucesan, Yigit A.; Viana, Felipe A. C. International Journal of Prognostics and Health Management, Vol. 11, Issue 1 https://doi.org/10.36001/ijphm.2020.v11i1.2594	journal	June 2023
Practical options for selecting data-driven or physics-based prognostics algorithms with reviews An, Dawn; Kim, Nam H.; Choi, Joo-Ho Reliability Engineering & System Safety, Vol. 133 https://doi.org/10.1016/j.ress.2014.09.014	journal	January 2015
A review on machinery diagnostics and prognostics implementing condition-based maintenance Jardine, Andrew K. S.; Lin, Daming; Banjevic, Dragan Mechanical Systems and Signal Processing, Vol. 20, Issue 7 https://doi.org/10.1016/j.ymssp.2005.09.012	journal	October 2006
Fault detection and diagnosis of large-scale HVAC systems in buildings using data-driven methods: A comprehensive review Mirnaghi, Maryam Sadat; Haghighat, Fariborz Energy and Buildings, Vol. 229 https://doi.org/10.1016/j.enbuild.2020.110492	journal	December 2020
Fault diagnostics of spur gear using decision tree and fuzzy classifier Krishnakumari, A.; Elayaperumal, A.; Saravanan, M. The International Journal of Advanced Manufacturing Technology, Vol. 89, Issue 9-12 https://doi.org/10.1007/s00170-016-9307-8	journal	August 2016
Study of fatigue crack initiation from flaws using fracture mechanics theory Forman, R. G. Engineering Fracture Mechanics, Vol. 4, Issue 2 https://doi.org/10.1016/0013-7944(72)90048-3	journal	June 1972
A dual-LSTM framework combining change point detection and remaining useful life prediction Shi, Zunya; Chehade, Abdallah Reliability Engineering & System Safety, Vol. 205 https://doi.org/10.1016/j.ress.2020.107257	journal	January 2021
A General Methodology for Uncertainty Quantification in Engineering Analyses Using a Credible Probability Box Ewing, Mark E.; Liechty, Brian C.; Black, David L. Journal of Verification, Validation and Uncertainty Quantification, Vol. 3, Issue 2 https://doi.org/10.1115/1.4041490	journal	June 2018
Neural network of Gaussian radial basis functions applied to the problem of identification of nuclear accidents in a PWR nuclear power plant Gomes, Carla Regina; Canedo Medeiros, Jose Antonio Carlos Annals of Nuclear Energy, Vol. 77 https://doi.org/10.1016/j.anucene.2014.10.001	journal	March 2015
Towards bearing health prognosis using generative adversarial networks: Modeling bearing degradation Khan, Sheraz Ali; Prosvirin, Alexander E.; Kim, Jong-Myon 2018 International Conference on Advancements in Computational Sciences (ICACS) https://doi.org/10.1109/ICACS.2018.8333495	conference	February 2018
Wrappers for feature subset selection Kohavi, Ron; John, George H. Artificial Intelligence, Vol. 97, Issue 1-2 https://doi.org/10.1016/S0004-3702(97)00043-X	journal	December 1997
Optimal Fault Classification Using Fisher Discriminant Analysis in the Parity Space for Applications to NPPs Cho, Sungwhan; Jiang, Jin IEEE Transactions on Nuclear Science, Vol. 65, Issue 3 https://doi.org/10.1109/TNS.2018.2803658	journal	March 2018
Support vector machine with parameter optimization by a novel hybrid method and its application to fault diagnosis Zhang, Xiaoyuan; Qiu, Daoyin; Chen, Fuan Neurocomputing, Vol. 149 https://doi.org/10.1016/j.neucom.2014.08.010	journal	February 2015
Remaining useful life estimation – A review on the statistical data driven approaches Si, Xiao-Sheng; Wang, Wenbin; Hu, Chang-Hua European Journal of Operational Research, Vol. 213, Issue 1 https://doi.org/10.1016/j.ejor.2010.11.018	journal	August 2011
A multi-stage hybrid fault diagnosis approach for operating conditions of nuclear power plant Wang, Zhichao; Xia, Hong; Peng, Binsen Annals of Nuclear Energy, Vol. 153 https://doi.org/10.1016/j.anucene.2020.108015	journal	April 2021
Bearing faults diagnosis using fuzzy expert system relying on an Improved Range Overlaps and Similarity method Berredjem, Toufik; Benidir, Mohamed Expert Systems with Applications, Vol. 108 https://doi.org/10.1016/j.eswa.2018.04.025	journal	October 2018
Real-Time Impact Visualization Inspection of Aerospace Composite Structures with Distributed Sensors Si, Liang; Baier, Horst Sensors, Vol. 15, Issue 7 https://doi.org/10.3390/s150716536	journal	July 2015
A new fault detection method for non-Gaussian process based on robust independent component analysis Cai, Lianfang; Tian, Xuemin Process Safety and Environmental Protection, Vol. 92, Issue 6 https://doi.org/10.1016/j.psep.2013.11.003	journal	November 2014
A novel concept and assessment method for trustworthiness of prognostics Sun, Bo; Jiang, Xiaopeng; Ye, Tianyuan Advances in Mechanical Engineering, Vol. 8, Issue 3 https://doi.org/10.1177/1687814016638807	journal	March 2016
Statistics versus machine learning Bzdok, Danilo; Altman, Naomi; Krzywinski, Martin Nature Methods, Vol. 15, Issue 4 https://doi.org/10.1038/nmeth.4642	journal	April 2018
Analysis of a complex of statistical variables into principal components. Hotelling, H. Journal of Educational Psychology, Vol. 24, Issue 6 https://doi.org/10.1037/h0071325	journal	January 1933
Fault diagnosis of Pakistan Research Reactor-2 with data-driven techniques Jamil, Farhan; Abid, Muhammad; Haq, Inamul Annals of Nuclear Energy, Vol. 90 https://doi.org/10.1016/j.anucene.2015.12.023	journal	April 2016
Explicit results for wear processes in a Markovian environment Kharoufeh, Jeffrey P. Operations Research Letters, Vol. 31, Issue 3 https://doi.org/10.1016/S0167-6377(02)00229-8	journal	May 2003
ANN Based Sensor and Actuator Fault Detection in Nuclear Reactors Banerjee, Shohan; Deng, Jiamei; Gorse, Chris 2020 8th International Conference on Control, Mechatronics and Automation (ICCMA) https://doi.org/10.1109/ICCMA51325.2020.9301579	conference	November 2020

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