Czasopismo | PRZEGLĄD ELEKTROTECHNICZNY | Rocznik 2019 - zeszyt 10

Application of PCA for early leak detection in a pipeline system of a steam boiler

Zastosowanie metody PCA do wczesnego wykrywania wycieków w rurociągach kotła parowego

10.15199/48.2019.10.43

nr katalogowy: 122746
10.15199/48.2019.10.43

Streszczenie

The application of the Principal Component Analysis (PCA) method for early detection of leakages in the pipeline system of a steam boiler in a thermal-electrical power plant is presented and discussed. The PCA model built from historical measurements of 12 selected process variables, mapped to the reduced space of three Principal Components (PC) of the highest magnitude, was used to establish the confidence ellipsoid, i.e. the feasible region in the PC coordinates, occupied by the values of process variables related to the "healthy" system. Changes of the current location of the process operating point in the PC space created the ‘fault trajectory' and were the basis for making a decision of leakage detection.

Abstract

W artykule przedstawiono zastosowanie metody składowych głównych (PCA) do wczesnego wykrywania wycieków z rurociągów kotła parowego pracującego w elektrociepłowni miejskiej. Model PCA, zbudowany na podstawie pomiarów 12 wybranych zmiennych procesowych, przedstawiony w przestrzeni trzech składowych głównych (PC) o największych modułach, został wykorzystany do określenia tzw. elipsoidy ufności, tj. obszaru w przestrzeni PC, w którym mieszczą się wartości zmiennych odpowiadające poprawnemu działaniu systemu. Zmiany aktualnego punktu pracy kotła tworzyły tzw. trajektorię uszkodzenia w przestrzeni PC i były podstawą do podejmowania decyzji na temat ew. wycieku z rurociągów.

Słowa kluczowe

Keywords

Bibliografia

[1] Zhang H., Xu L., Diagnostic System for Current-Carrying Fault: Modeling, Precaution, and Prediction, IEEE Trans. Power Delivery, 29 (2014), No. 3, 1318-1325, doi: 10.1109/TPWRD.2013.2295005
[2] Sun X., Chen T., Marquez H.J., Efficient model-based leak detection in boiler steam-water systems, Computers and Chemical Engineering, 26 (2002), No. 11, 1643-1647
[3] Sun X., Chen T., Marquez H.J., Boiler Leak Detection Using a System Identification Technique, Industrial & Engineering Chemistry Research, 41 (2002), No. 22, 5447-5454
[4] Jankowska A., Approach to Early Boiler Tube Leak Detection with Artificial Neural Networks. In: Jablonski R., Turkowski M., Szewczyk R. (eds.), Recent Advances in Mechatronics, Springer-Verlag, Berlin Heidelberg, 2007, 57-61
[5] Sato R., Yasukouchi K., Yamamoto T., Device for early detection of rupture of the pressure part of a boiler, United States Patent 3831561, August 27, 1974
[6] Jung G.J., Cho Y.S., Kim Y.C., Baek S.H., Sung J.H., Frequency Shifting Signal Detection and Analysis of Boiler Tube Leaks, 18th International Conference on Composite Materials, 21-26 August 2011, ICC Jeju, Korea
[7] Studdard B., Arrington P., Rechner M., Operating Experience Using Acoustic Leak Detection at Gaston Station, Technical Paper BR-1492, Babcock & Wilcox, a McDermott company, presented to: Power-Gen '92, 17-19 November 1992, Orlando, USA
[8] Jiang G., Wang L., Tian J., and Pan J., Research on acoustic source positioning method for boilers tube leakage, Proceedings of 20th International Congress on Acoustics, ICA 2010, 23-27 August 2010, Sydney, Australia, PACS: 43.20.-f, 1-6
[9] An L., Wang P., Sarti A., Antonacci F., Shi J., Hyperbolic boiler tube leak location based on quaternary acoustic array, Applied Thermal Engineering, vol. 31 (2011), No. 16, 3428- 3436
[10] Kim D.-H., Yang B.-S., Lee S.-B., 3D boiler tube leak detection technique using acoustic emission signals for power plant structure health monitoring, Prognostics and System Health Management Conference (PHM-Shenzhen), 24-25 May 2011, 1-7
[11] Jones C.S., Koch D.B., Morris K.W., Classical and parametric spectral analysis instrument using a visual programming language, 9th IEEE Instrumentation and Measurement Technology Conference, IMTC '92, 12-14 May 1992, 533-538
[12] Jiang G., Wang L., Research on the Detection and Location of Sound Emission Caused by Tube Leakage in Boilers, 2012 Asia-Pacific Power and Energy Engineering Conference (APPEEC), 27-29 March 2012, Shanghai, 1-4, doi: 10.1109/APPEEC.2012.6307413
[13] Burgmayer P.R., Durham V.E., Effective Recovery Boiler Leak Detection with Mass Balance Methods, Proceedings of TAPPI Engineering Conference, Atlanta (USA), 17-21 September 2000, 1011-1025
[14] Pertew A.M., Sun X., Kent Gooden R., Marquez H.J., A new blowdown compensation scheme for boiler leak detection, 2008 American Control Conference, Seattle, USA, 11-13 June 2008, 4309-4311
[15] Lang F.D., Rodgers D.A.T., Mayer L.E., Detection of Tube Leaks and Their Location Using Input/Loss Methods, Proceedings of the 2004 International Joint Power Generation Conference (combined Electric Power 2004 Conference), IJPGC2004, Baltimore, USA, 30 March - 1 April 2004
[16] de Mello F.P., Boiler models for system dynamic performance studies, IEEE Trans. Power Systems, 6 (1991), No. 1, 66-74
[17] Colonna P., van Putten H., Dynamic modeling of steam power cycles. Part I - Modeling paradigm and validation, Applied Thermal Engineering, 27 (2007), No. 2-3, 467-480
[18] Liu C., Liu J., Niu Y., Jin X., Nonlinear modeling and simulation for large scale coal-fired power unit, 30th Annual Conference of the IEEE Industrial Society 2004, 2-6 November 2004, Busan, Korea, vol. 3, 1983-1986
[19] van Putten H., Colonna P., Dynamic modeling of steam power cycles. Part II - Simulation of a small simple Rankine cycle system, Applied Thermal Engineering, 27 (2007), No. 14-15, 2566-2582 PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 95 NR 10/2019 203
[20] Sun X., Chen T., Marquez H.J., Detecting leaks and sensor biases by recursive identification with forgetting factors, Proceedings of the 40th IEEE Conference on Decision and Control 2001, Orlando, USA, December 2001, vol. 4, 3716- 3721
[21] Castillo I., Edgar T.F. and Fernández B.R., Robust modelbased fault detection and isolation for nonlinear processes using sliding modes, International Journal of Robust and Nonlinear Control, 22 (2012), No. 1, 89-104
[22] Marquez H.J., Riaz M., Robust state observer design with application to an industrial boiler system, Control Engineering Practice, 13 (2005), No. 6, 713-728
[23] Lo K.L., Rathamarit Y., State estimation of a boiler using the unscented Kalman filter, IET Generation, Transmission & Distribution, 2 (2008), No. 6, 917-931
[24] Nazaruddin Y.Y., Nur Aziz A., Sudibjo W., Improving the Performance of Industrial Boiler Using Artificial Neural Network Modeling and Advanced Combustion Control, International Conference on Control, Automation and Systems, ICCAS 2008, 14-17 October 2008, Seoul, Korea, 1921-1926
[25] Yu D.L., Chang T.K., Yu D.W., Adaptive neural model-based fault tolerant control for multi-variable processes, Engineering Applications of Artificial Intelligence, 18 (2005), No. 4, 393- 411
[26] Rostek K., Morytko L., Jankowska A., Early detection and prediction of leaks in fluidized-bed boilers using artificial neural networks, Energy, 89 (2015), September 2015, 914- 923, doi: 10.1016/j.energy.2015.06.042
[27] Dong X.-C., Wang H.-B., Zhao X.-X., Model Reference Neural Network Control for Boiler Combustion System, Proceedings of the Fourth International Conference on Machine Learning and Cybernetics, Guangzhou, China, 18- 21 August 2005, vol. 8, 4694-4698
[28] Ghaffari A., Moosavian S.A.A., and Chaibakhsh A., Experimental Fuzzy Modeling and Control of a Once-through Boiler, Proceedings of the IEEE international Conference on Mechatronic & Automation, Niagara Falls, Canada, July 2005, vol. 3, 1340-1345
[29] Alouani A.T., Chang S.-Y.P., Artificial Neural Network and Fuzzy Logic Based Boiler Tube Leak Detection Systems, USA Patent No: 6,192,352 B1, Feb 20, 2001.
[30] Ghaffari A., Chaibakhsh A., Lucas C., Soft computing approach for modeling power plant with a once-through boiler, Engineering Applications of Artificial Intelligence, 20 (2007), No. 6, 809-819
[31] Arroyo-Figueroa G., Sucar L.E., Vilaavicencio A., Probabilistic temporal reasoning and its application to fossil power plant operation, Expert Systems with Applications, 15 (1998), No. 3-4, 317-324
[32] Ge Z., Song Z., Gao F., Review of Recent Research on Data- Based Process Monitoring, Industrial & Engineering Chemistry Research, 52 (2013), No. 10, 3543-3562
[33] Jolliffe I.T., Principal Component Analysis, Second Edition, Springer series in statistics, Springer, New York Berlin Heidelberg, 2002
[34] Ge Z., Song Z., Multivariate Statistical Process Control: Process Monitoring Methods and Applications, Advances in Industrial Control, Springer, 2013th Edition, London, 2013
[35] Deng P.C., Gui W.H., Xie, Y.F., Latent space transformation based on principal component analysis for adaptive fault detection, IET Control Theory & Applications, 4 (2010), No. 11, 2527-2538
[36] Ma Y.-G., Zhang J., Fault Diagnosis based on PCA and D-S Evidence Theory, Asia-Pacific Power and Energy Engineering Conference, APPEEC 2009, 28-31 March 2009, Wuhan, China, 1-5
[37] Lau C.K., Ghosh K., Hussain M.A., Che Hassan C.R., Fault diagnosis of Tennessee Eastman process with multi-scale PCA and ANFIS, Chemometrics and Intelligent Laboratory Systems, 120 (2013), 1-14
[38] Ghamari A., Khaloozadeh H., Ashraf-Modarres A., Ghamari H., Application of Quantitative Data-Based Fault Detection Methods on a Drum-Type Boiler, Proceedings of the 3rd Conference on Thermal Power Plants (CTPP), 2011, 1-6
[39] Jaffel I., Taouali O., Elaissi I., Messaoud H., Comparative study of PCA approaches for fault detection: Application to a chemical reactor, IEEE - 2013 International Conference on Control, Decision and Information Technologies CoDIT'13, 6- 8 May 2013, Hammamet, Tunisia, 57-62
[40] Ding S., Zhang P., Ding E., Yin S., Naik A., Deng P., Gui W., On the Application of PCA Technique to Fault Diagnosis, Tsinghua Science and Technology, 15 (2010), No. 2, 138- 144
[41] Tamura M., Tsujita S., A study on the number of principal components and sensitivity of fault detection using PCA, Computers and Chemical Engineering, 31 (2007), No. 9, 1035-1046
[42] Huang Y., Gertler J., McAvoy T.J., Sensor and actuator fault isolation by structured partial PCA with nonlinear extensions, Journal of Process Control, 10 (2000), No. 5, 459-469
[43] Yoo C.K., Lee J.-M., Vanrolleghem P.A., Lee I.-B., On-line monitoring of batch processes using multiway independent component analysis, Chemometrics and Intelligent Laboratory Systems, 71 (2004), No. 2, 151-163
[44] Cheng H., Nikus M., Jämsä-Jounela S.-L., Evaluation of PCA methods with improved fault isolation capabilities on a paper machine simulator, Chemometrics and Intelligent Laboratory Systems, 92 (2008), No. 2, 186-199
[45] Yu J., Yoo J., Jang J., Park J.H., Kim S., A novel plugged tube detection and identification approach for final super heater in thermal power plant using principal component analysis. Energy, vol. 26 (2017), 1 May 2017, 404-418
[46] Niu Z., Liu J.-Z., Niu Y.-G., Pan Y.-S, A Reformative PCAbased Fault Detection Method Suitable for Power Plant Process, Proceedings of the Fourth International Conference on Machine Learning and Cybernetics, Guangzhou, China, 18-21 August 2005, 2133-2138
[47] Tong P., An L.-S., Zhang J., Liu Y.-T., Research on Fault Diagnosis Method of Principal Components Analysis and D-S Evidence Theory, Chinese Control and Decision Conference, CCDC '09, 2009, 1601-1605
[48] Sun X., Marquez H.J., Chen T., Riaz M., An improved PCA method with application to boiler leak detection, ISA Transactions, 44 (2005), 379-397
[49] Pawlik M., Strzelczyk F., Elektrownie (Power plants) - in Polish, WNT, Warszawa, Poland, 2009

Jeśli masz wykupiony/przyznany dostęp - zaloguj się. Skorzystaj z naszych propozycji zakupu!

Publikacja


e-Publikacja (format pdf) - nr 122746 "Application of PCA for ea..." licencja: Osobista Produkt cyfrowy	10.00 zł

Zeszyt


PRZEGLĄD ELEKTROTECHNICZNY - e-zeszyt (pdf) 2019-10 licencja: Osobista Produkt cyfrowy	55.00 zł

Prenumerata

PRZEGLĄD ELEKTROTECHNICZNY - prenumerata cyfrowa
licencja: Osobista

Produkt cyfrowy
Nowość

762.00 zł

PRZEGLĄD ELEKTROTECHNICZNY - PAKIET prenumerata PLUS
licencja: Osobista

Szczegóły pakietu

Nazwa
PRZEGLĄD ELEKTROTECHNICZNY - PAKIET prenumerata PLUS (Prenumerata papierowa + dostęp do portalu sigma-not.pl + e-prenumerata)	1002.00 zł brutto 927.78 zł netto 74.22 zł VAT (stawka VAT 8%)

1002.00 zł

PRZEGLĄD ELEKTROTECHNICZNY - papierowa prenumerata roczna + wysyłka
licencja: Osobista

Szczegóły pakietu

Nazwa
PRZEGLĄD ELEKTROTECHNICZNY - papierowa prenumerata roczna	960.00 zł brutto 888.89 zł netto 71.11 zł VAT (stawka VAT 8%)
PRZEGLĄD ELEKTROTECHNICZNY - pakowanie i wysyłka	42.00 zł brutto 34.15 zł netto 7.85 zł VAT (stawka VAT 23%)

1002.00 zł

Zeszyt

2019-10

Twój Koszyk

Publikacja

Zeszyt

Prenumerata

Zeszyt

Czasopisma