Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:
Introduction to Condition Monitoring in Mechanical and Electrical Systems Kapitel lesen Erstes Kapitel lesen

2012 | OriginalPaper | Buchkapitel

7. Fuzzy Systems for Condition Monitoring

verfasst von : Tshilidzi Marwala

Erschienen in: Condition Monitoring Using Computational Intelligence Methods

Verlag: Springer London

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

The chapter presents the application of Fuzzy Set Theory (FST) and fuzzy ARTMAP (Adaptive Resonance Theory Mapping) to diagnose the condition of high voltage bushings. The diagnosis uses Dissolved Gas Analysis (DGA) data from bushings based on IEC60599, IEEE C57-104, and California State University Sacramento (CSUS) criteria for Oil Impregnated Paper (OIP) bushings. FST and fuzzy ARTMAP are compared in terms of accuracy. Both FST and fuzzy ARTMAP could diagnose the bushings condition with accuracy of 98% and 97.5% respectively.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Vorheriges Kapitel Gaussian Mixture Models and Hidden Markov Models for Condition Monitoring
Nächstes Kapitel Rough Sets for Condition Monitoring
Literatur
Aliustaoglu C, Metin Ertunc H, Ocak H (2009) Tool wear condition monitoring using a sensor fusion model based on fuzzy inference system. Mech Syst Signal Process 23(2):539–546CrossRef
Ammar S, Wright R (2000) Applying fuzzy-set theory to performance evaluation. Socioecon Plann Sci 34:285–302CrossRef
Araujo E (2008) Improved Takagi-Sugeno fuzzy approach. In: Proceedings of the IEEE international conference on fuzzy systems, pp 1154–1158
Babuska R (1991) Fuzzy modeling and identification. PhD thesis, Technical University of Delft
Bandemer H, Gottwald S (1995) Fuzzy sets, fuzzy logic, fuzzy methods with applications. Wiley, New YorkMATH
Barszcz T, Bielecka M, Bielecki A, Wójcik M (2011) Wind turbines states classification by a fuzzy-ART neural network with a stereographic projection as a signal normalization. Lect Notes Comput Sci (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6594 LNCS (PART 2):225–234
Bih J (2006) Paradigm shift – an introduction to fuzzy logic. IEEE Potentials 25:6–21CrossRef
Boesack CD, Marwala T, Nelwamondo FV (2010) Application of GA-fuzzy controller design to automatic generation control. In: 2010 Third international workshop on advanced computational intelligence (IWACI), pp 227–232
Bojadziev G, Bojadziev M (1995) Fuzzy sets, fuzzy logic, applications. World Scientific Publishing Co. Pte. Ltd, Singapore/River EdgeMATHCrossRef
Cabalar AF, Cevik A, Gokceoglu C, Baykal G (2010) Neuro-fuzzy based constitutive modeling of undrained response of Leighton Buzzard sand mixtures. Expert Syst Appl 37:842–851CrossRef
Cantor G (1874) Über eine Eigenschaft des Inbegriffes aller reellen algebraischen Zahlen. Crelles J Math 77:258–262CrossRef
Carpenter GA, Grossberg S, Markuzon N, Reynolds JH, Rosen DB (1992) Fuzzy ARTMAP: a neural network architecture for incremental supervised learning of analog multidimensional maps. IEEE Trans Neural Netw 3:698–713CrossRef
Catelani M, Fort A, Alippi C (2002) A fuzzy approach for soft fault detection in analog circuits. Measurement 32(1):73–83CrossRef
Chang CY, Wang HJ, Jian RH (2010a) Semantic image retrieval with Fuzzy-ART. In: 2010 International conference on system science and engineering, ICSSE 2010, art.# 5551705, pp 69–74
Chang CY, Wang HJ, Jian RH (2010b) Color-based semantic image retrieval with fuzzy-ART. In: Proceedings of 2010 6th international conference on intelligent information hiding and multimedia signal processing, IIHMSP 2010, art. #5635903, pp 426–429
Chen B, Wang W, Qin Q (2010) Infrared target detection based on fuzzy ART neural network. In: 2010 2nd international conference on computational intelligence and natural computing, CINC 2010, 2, art. no. 5643745, pp 240–243
Chen J, Roberts C, Weston P (2008) Fault detection and diagnosis for railway track circuits using neuro-fuzzy systems. Control Eng Pract 16(5):585–596CrossRef
Cox E (1994) The fuzzy systems handbook: a practitioner’s guide to building, using, maintaining fuzzy systems. AP Professional, Boston
D’Angelo MFSV, Palhares RM, Takahashi RHC, Loschi RH, Baccarini LMR, Caminhas WM (2011) Incipient fault detection in induction machine stator-winding using a fuzzy-Bayesian change point detection approach. Appl Software Comput 11(1):179–192CrossRef
Demirli K, Khoshnejad M (2009) Autonomous parallel parking of a car-like mobile robot by a neuro-fuzzy sensor-based controller. Fuzzy Sets Syst 160:2876–2891MathSciNetCrossRef
Dhlamini SM (2007) Bushing diagnosis using artificial intelligence and dissolved gas analysis. University of the Witwatersrand PhD thesis
Dhlamini SM, Marwala T (2005) Modeling inaccuracies from simulators for HV polymer Bushing. In: Proceedings of international symposium on high voltage, Beijing, Paper A18
Dhlamini SM, Marwala T, Majozi T (2006) Fuzzy and multilayer perceptron for evaluation of HV bushings. In: Proceedings of the IEEE international conference on systems, man and cybernetics, Taiwan, pp 1331–1336
El-Sebakhy EA (2010) Flow regimes identification and liquid-holdup prediction in horizontal multiphase flow based on neuro-fuzzy inference systems. Math Comput Simul 80:1854–1866MathSciNetMATHCrossRef
Evsukoff A, Gentil S (2005) Recurrent neuro-fuzzy system for fault detection and isolation in nuclear reactors. Adv Eng Inform 19(1):55–66CrossRef
Ferreirós J (1999) Labyrinth of thought: a history of set theory and its role in modern mathematics. Birkhäuser, BaselMATH
Flaig A, Barner KE, Arce GR (2000) Fuzzy ranking: theory and applications. Signal Process 80:1017–1036MATHCrossRef
Hájek P (1995) Fuzzy logic and arithmetical hierarchy. Fuzzy Sets Syst 3:359–363CrossRef
Halpern JY (2003) Reasoning about uncertainty. MIT Press, CambridgeMATH
Hsu Y-C, Lin S-F (2009) Reinforcement group cooperation-based symbiotic evolution for recurrent wavelet-based neuro-fuzzy systems. J Neurocomput 72:2418–2432CrossRef
Huang TM, Kecman V (2005) Gene extraction for cancer diagnosis by support vector
Hwang JIG, Liu CE, Sokoll L, Adam BL (2010) Applying fuzzy ART in medical diagnosis of cancers. In: 2010 international conference on machine learning and cybernetics, ICMLC 2010, Qingdao, 3, art. no. 5580939, pp 1084–1089
Iplikci S (2010) Support vector machines based neuro-fuzzy control of nonlinear systems. J Neurocomput 73:2097–2107CrossRef
Javadpour R, Knapp GM (2003a) A fuzzy neural network approach to condition monitoring. Comput Ind Eng 45:323–330CrossRef
Javadpour R, Knapp GM (2003b) A fuzzy neural network approach to machine condition monitoring. Comput Ind Eng 45(2):323–330, 25th international conference on computers and industrial engineering, August 2003
Jeffries M, Lai E, Plantenberg DH, Hull JB (2001) A fuzzy approach to the condition monitoring of a packaging plant. J Mater Process Technol 109(1–2):83–89CrossRef
Jiang M, Lin S (2010) A study of personal credit scoring models based on fuzzy ART. J Comput Info Syst 6(9):2805–2811MathSciNet
Johnson P (1972) A history of set theory. Prindle, Weber & Schmidt, BostonMATH
Klir GJ, Folger TA (1988) Fuzzy sets, uncertainty, and information. Prentice Hall, Englewood CliffsMATH
Klir GJ, Yuan B (1995) Fuzzy sets and fuzzy logic: theory and applications. Prentice Hall, Upper Saddle RiverMATH
Klir GJ, St Clair UH, Yuan B (1997) Fuzzy set theory: foundations and applications. Prentice Hall, Upper Saddle RiverMATH
Korbicz J, Kowal M (2007) Neuro-fuzzy networks and their application to fault detection of dynamical systems. Eng Appl Artif Intell 20(5):609–617, Soft Computing Applications, August 2007
Kosko B (1993) Fuzzy thinking: the new science of fuzzy logic. Hyperion, New York
Kubica EG, Wang D, Winter AD (1995) Modelling balance and posture control mechanisms of the upper body using conventional and fuzzy techniques. Gait Posture 3(2):111CrossRef
Lau HCW, Dwight RA (2011) A fuzzy-based decision support model for engineering asset condition monitoring – a case study of examination of water pipelines. Expert Syst Appl 38(10):13342–13350CrossRef
Lopes MLM, Minussi CR, Lotufo ADP (2005) Electric load forecasting using a fuzzy ART&ARTMAP neural network. Appl Software Comput 5(2):235–244CrossRef
Majozi T, Zhu XX (2005) A combined fuzzy set theory and MILP approach in integration of planning and scheduling of batch plants – personnel evaluation and allocation. Comput Chem Eng 29:2029–2047, Elsevier Science, July 2005CrossRef
Mamdani EH (1974) Application of fuzzy algorithms for the control of a dynamic plant. Proc IEE 121:1585–1588
Mamdani EH, Assilian S (1975) An experiment in linguistic synthesis with a fuzzy logic controller. Int J Man–Mach Stud 7(1):1–13MATHCrossRef
Marwala T (2009) Computational intelligence for missing data imputation, estimation and management: knowledge optimization techniques. IGI Global Publications, Information Science Reference Imprint, New York
Marwala T, Lagazio M (2011) Militarized conflict modeling using computational intelligence techniques. Springer, LondonCrossRef
Mendonca LF, Sousa JMC, Sá da Costa JMG (2009) An architecture for fault detection and isolation based on fuzzy methods. Expert Syst Appl 36(2, Part 1):1092–1104CrossRef
Msiza IS, Szewczyk M, Halinka A, Pretorius J-HC, Sowa P, Marwala T (2011) Neural networks on transformer fault detection: evaluating the relevance of the input space parameters. In: 2011 IEEE/PES Power Systems Conference and Exposition, PSCE 2011, Phoenix, art. no. 5772567
Nelwamondo FV, Marwala T (2007) Fuzzy artmap and neural network approach to online processing of inputs with missing values. Trans S Afr Inst Electrical Eng 98(2):45–51
Novák V (1989) Fuzzy sets and their applications. Adam Hilger, BristolMATH
Novák V, Perfilieva I, Močkoř J (1999) Mathematical principles of fuzzy logic. Kluwer, DordrechtMATHCrossRef
Razavi-Far R, Davilu H, Palade V, Lucas C (2009) Model-based fault detection and isolation of a steam generator using neuro-fuzzy networks. Neurocomputing 72(13–15):2939–2951, Hybrid Learning Machines (HAIS 2007)/Recent Developments in Natural Computation (ICNC 2007), August 2009
Sainz Palmero GI, Juez Santamaria J, Moya de la Torre EJ, Peran Gonzalez JR (2005) Fault detection and fuzzy rule extraction in AC motors by a neuro-fuzzy ART-based system. Eng Appl Artif Intell 18(7):867–874CrossRef
Sugeno M (1985) Industrial applications of fuzzy control. Elsevier, Amsterdam
Takagi T, Sugeno M (1985) Fuzzy identification of systems and its applications to modeling and control. IEEE Trans Syst Man Cybern 15:116–132MATH
Tan SC, Rao MVC, Lim Fuzzy CP (2008) ARTMAP dynamic decay adjustment: an improved fuzzy ARTMAP model with a conflict resolving facility. Appl Software Comput 8(1):543–554CrossRef
Tettey T, Marwala T (2006) Neuro-fuzzy modeling and fuzzy rule extraction applied to conflict management. Lect Notes Comput Sci 4234:1087–1094CrossRef
Vilakazi CB (2007) Machine condition monitoring using artificial intelligence: the incremental learning and multi-agent system approach, University of the Witwatersrand Masters dissertation
Vilakazi CB, Marwala T (2006) Application of feature selection and fuzzy ARTMAP to intrusion detection. In: IEEE international conference on systems, man and cybernetics, pp 4880–4885
Vilakazi CB, Marwala T (2007a) Incremental learning and its application to bushing condition monitoring. Lect Notes Comput Sci (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 4491 LNCS (PART 1):1237–1246
Vilakazi CB, Marwala T (2007b) Online incremental learning for high voltage bushing condition monitoring. In: IEEE international conference on neural networks – conference proceedings, art. no. 4371355, pp 2521–2526
Von Altrock C (1995) Fuzzy logic and neurofuzzy applications explained. Prentice Hall, Englewood Cliffs
Wang M, Zan T (2010) Adaptively pattern recognition in statistical process control using fuzzy ART neural network. In: Proceedings – 2010 international conference on digital manufacturing and automation, ICDMA 2010, 1, art. no. 5701122, pp 160–163
Wang Z (2000) Artificial intelligence applications in the diagnosis of power transformer incipient faults, PhD thesis, Virginia Polytechnic Institute and State University
Wright S, Marwala T (2006) Artificial intelligence techniques for steam generator modelling. arXiv:0811.1711
Zadeh LA (1973) Outline of a new approach to the analysis of complex systems and decision processes. IEEE Trans Syst Man Cybern 3(1):28–44MathSciNetMATHCrossRef
Zemankova-Leech M (1983) Fuzzy relational data bases. PhD dissertation, Florida State University
Zimmermann H (2001) Fuzzy set theory and its applications. Kluwer, BostonCrossRef
Metadaten
Titel
Fuzzy Systems for Condition Monitoring
verfasst von
Tshilidzi Marwala
Copyright-Jahr
2012
Verlag
Springer London
Buch
Condition Monitoring Using Computational Intelligence Methods

Print ISBN: 978-1-4471-2379-8

Electronic ISBN: 978-1-4471-2380-4

Copyright-Jahr: 2012

DOI
https://doi.org/10.1007/978-1-4471-2380-4_7

Premium Partner

    Marktübersichten

    Die im Laufe eines Jahres in der „adhäsion“ veröffentlichten Marktübersichten helfen Anwendern verschiedenster Branchen, sich einen gezielten Überblick über Lieferantenangebote zu verschaffen. 

    Zur Marktübersicht
    Bildnachweise