참고문헌 (36)

1. Electr. Power Energy Syst. Ajami 43 728 2012 10.1016/j.ijepes.2012.06.022 Data driven approach for fault detection and diagnosis of turbine in thermal power plant using Independent Component Analysis (ICA) 

   상세보기

2. Automatica Alcala 45 1593 2009 10.1016/j.automatica.2009.02.027 Reconstruction-based contribution for process monitoring 

   상세보기

3. Ann. Nucl. Energy Baraldi 37 778 2010 10.1016/j.anucene.2010.03.002 An ensemble approach to sensor fault detection and signal reconstruction for nuclear system control 

   상세보기

4. Chen 2013 Research on data preprocess method for thermal parameters 

5. Comput. Indus. Chen 62 42 2011 10.1016/j.compind.2010.05.013 Using SVM based method for equipment fault detection in a thermal power plant 

   상세보기

6. Electr. Power Energy Syst. Chen 71 274 2015 10.1016/j.ijepes.2015.03.012 A hybrid data-driven modeling method on sensor condition monitoring and fault diagnosis for power plants 

   상세보기

7. Comput. Stat. Data Anal. Chen 53 3706 2009 10.1016/j.csda.2009.03.014 Robust probabilistic PCA with missing data and contribution analysis for outlier detection 

   상세보기

8. Int. Rev. Automatic Control Daneshvar 3 2 198 2010 Data driven approach for fault detection and diagnosis of boiler system in coal fired power plant using principal component analysis 

9. 10.1109/NUICONE.2012.6493290 Deshpande, P., Warke, N., Khandare, P., Deshpande, V., 2012 December. Thermal power plant analysis using artificial neural network. In: Engineering (NUiCONE). 

   

10. Fu 2007 Structure optimized PCA and its application 

11. Control Eng. Practice Gang Li 18 1211 2010 10.1016/j.conengprac.2010.05.012 Reconstruction based fault prognosis for continuous processes 

    상세보기

12. Guidance on Cross Calibration of Protection System Resistance Temperature Detectors. United States Nuclear Regulatory Commission, Washington DC., NUREG-08001997. 

13. He 2010 Research of principal component analysis and its application in data reconstruction of fault sensor 

14. Hines 2006 Technical Review of On-line Monitoring Techniques for Performance Assessment: State-of-the-Art 

15. Hu 2013 Study on the PCA-Based Sensor Fault Detection Efficiency of the Water-Cooled Chiller 

16. Ann. Nucl. Energy Jamil 90 433 2016 10.1016/j.anucene.2015.12.023 Fault diagnosis of Pakistan Research Reactor-2 with data-driven techniques 

    상세보기

17. Li 2007 Research on statistical process monitoring based on PCA 

18. Li 2011 Sensor fault detection and isolation using system dynamic identification techniques 

19. Li 2011 Dynamic Modeling, Sensor Placement Design, and Fault Diagnosis of Nuclear Desalination Systems 

20. Ann. Nucl. Energy Li 109 92 2017 10.1016/j.anucene.2017.05.024 Design of comprehensive diagnosis system in nuclear power plant 

    상세보기

21. Energy Build. Li 68 63 2014 10.1016/j.enbuild.2013.08.044 A model-based fault detection and diagnostic methodology based on PCA method and wavelet transform 

    상세보기

22. Comput. Speech Lang. Lu 24 632 2010 10.1016/j.csl.2009.09.001 A gain factor adapted by masking property and SNR variation for speech enhancement in colored noise corruptions 

    상세보기

23. Prog. Nucl. Energy. Ma 53 255 2011 10.1016/j.pnucene.2010.12.001 Applications of fault detection and diagnosis methods in nuclear power plants: a review 

    상세보기

24. Prog. Nucl. Energy Messai 79 8 2015 10.1016/j.pnucene.2014.10.013 On-line fault detection of a fuel rod temperature measurement sensor in a nuclear reactor core using ANNs 

    상세보기

25. On-line Testing of Calibration of Process Instrumentation Channels in Nuclear Power Plants. US Nuclear Regulatory Commission, NUREG/CR-6343, 1995. 

26. Penha 2017 Using principal component analysis modeling to monitor temperature sensors in a nuclear research reactor 

27. Energy Salahshoor 35 5472 2010 10.1016/j.energy.2010.06.001 Fault detection and diagnosis of an industrial steam turbine using fusion of SVM (support vector machine) and ANFIS (adaptive neuro-fuzzy inference system) classifiers 

    상세보기

28. Chemometr. Intell. Lab. Syst. Tao 128 49 2013 10.1016/j.chemolab.2013.07.012 Fault diagnosis based on PCA for sensors of laboratorial wastewater treatment process 

    상세보기

29. Signal Process. Tomassi 106 73 2015 10.1016/j.sigpro.2014.07.001 Wavelet shrinkage using adaptive structured sparsity constraints 

    상세보기

30. Chemometr. Intell. Lab. Syst. Tong 161 34 2017 10.1016/j.chemolab.2016.11.015 Fault detection and diagnosis of dynamic processes using weighted dynamic decentralized PCA approach 

    상세보기

31. Signal Process. ur Rehman 131 220 2017 10.1016/j.sigpro.2016.08.019 Translation invariant multi-scale signal denoising based on goodness-of-fit tests 

    상세보기

32. Ann. Nucl. Energy Uren 87 739 2016 10.1016/j.anucene.2015.06.013 An integrated approach to sensor FDI and signal reconstruction in HTGRs - Part II: case studies 

    상세보기

33. Ann. Nucl. Energy Uren 87 750 2016 10.1016/j.anucene.2015.06.010 An integrated approach to sensor FDI and signal reconstruction in HTGRs - Part I: theoretical framework 

    상세보기

34. Indus. Eng. Chem. Res. Valle 38 4389 1999 10.1021/ie990110i Selection of the number of principal components: the variance of the reconstruction error criterion with a comparison to other methods 

    상세보기

35. Walpole 2012 Probability and Statistics for Engineers and Scientists 

36. Wang 2014 The Research on the Sensor Fault Detection and Diagnosis of the Central Air-Conditioning Water System based on PCA