Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Extraction of Weak Bearing Fault Signatures from Non-stationary Signals Using Parallel Wavelet Denoising Read chapter Read first chapter

2019 | OriginalPaper | Chapter

Model-Based State Estimation for the Diagnosis of Multiple Faults in Non-linear Electro-Mechanical Systems

Authors : Mikel Gonzalez, Oscar Salgado, Jan Croes, Bert Pluymers, Wim Desmet

Published in: Advances in Condition Monitoring of Machinery in Non-Stationary Operations

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

This paper presents a framework for the condition monitoring of large non-linear electro-mechanical systems. Faults are assessed in different subsystems by means of joint state-parameter estimations. The different estimations are interconnected by a Digital Twin of the system, which provides background information for the physics neglected in the estimation models. In addition, the Digital Twin provides a benchmark for the estimations, which allows identifying the location and extend of faults. As application case, the condition of the guiding system and the electric machine of a vertical transportation system are evaluated. For this purpose, a scaled test bench of the vertical transportation system is used, showing the potential of this approach in the condition monitoring of complex industrial systems.

Dont have a licence yet? Then find out more about our products and how to get one now:

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!

inform now

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!

inform now

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!

inform now
previous chapter Convolutional Neural Networks for Fault Diagnosis Using Rotating Speed Normalized Vibration
next chapter Estimating the Rotational Synchronous Component from Instantaneous Angular Speed Signals in Variable Speed Conditions
Literature
1.
Farrar C, Worden K (2012) Structural Health Monitoring: A Machine Learning Perspective. Wiley, ChichesterCrossRef
2.
Venkatasubramanian V, Rengaswamy R, Yin K, Kavuri SN (2003) A review of process fault detection and diagnosis: part i: quantitative model-based methods. Comput Chem Eng 27(3):293–311CrossRef
3.
Isermann R (2005) Model-based fault-detection and diagnosis-status and applications. Annu Rev Control 29(1):71–85CrossRef
4.
Del Pizzo A, Spina I, Schäfer U, Beti LT (2011) A parameter estimation method for on-line failure detection in permanent magnet AC-brushless motors having current-dependent parameters. In: SDEMPED 2011 - 8th IEEE Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives, pp 258–264 (2011)
5.
Jha MS, Dauphin-Tanguy G, Ould-Bouamama B (2016) Particle filter based hybrid prognostics for health monitoring of uncertain systems in bond graph framework. Mech Syst Signal Process 75:301–329CrossRef
6.
Bonvini M, Sohn MD, Granderson J, Wetter M, Piette MA (2014) Robust on-line fault detection diagnosis for hvac components based on nonlinear state estimation techniques. Appl Energy 124:156–166CrossRef
7.
Arriola D, Thielecke F (2017) Model-based design and experimental verification of a monitoring concept for an active-active electromechanical aileron actuation system. Mech Syst Signal Process 94:322–345CrossRef
8.
Cauffriez L, Grondel S, Loslever P, Aubrun C (2016) Bond graph modeling for fault detection and isolation of a train door mechatronic system. Control Eng Pract 49:212–224CrossRef
9.
Frank PM, Ding X (1997) Survey of robust residual generation and evaluation methods in observer-based fault detection systems. J Process Control 7(6):403–424CrossRef
10.
Isermann R (200) Integration of fault detection and diagnosis methods. In: Issues of Fault Diagnosis for Dynamic Systems, pp 15–49. Springer, LondonCrossRef
11.
Hanlon PD, Maybeck PS (2000) Multiple-model adaptive estimation using a residual correlation Kalman filter bank. IEEE Trans Aerosp Electron Syst 36(2):393–406CrossRef
12.
Simon D (2006) Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches. Wiley, HobokenCrossRef
13.
Isermann R, Munchhof M (2011) Identification of Dynamic Systems: An Introduction with Applications. Springer, HeidelbergCrossRef
14.
Naets F, Croes J, Desmet W (2014) An online coupled state/input/parameter estimation approach for structural dynamics 283:1167–1188
15.
Hermann R, Krener A (1977) Nonlinear controllability and observability. IEEE Trans Autom Control 22(5):728–740 (Cited By 956)MathSciNetCrossRef
16.
Ghosh B, Rosenthal J (1995) A generalized popov-belevitch-hautus test of observability. IEEE Trans Autom Control 40(1):176–180 (Cited By 14)MathSciNetCrossRef
17.
Croes J (2017) Virtual sensing in mechatronic systems State estimation using system level models. PhD thesis
18.
Nakhaeinejad M, Bryant MD (2011). Observability analysis for model-based fault detection and sensor selection in induction motors. Meas Sci Technol 22(7)CrossRef
19.
20.
Chartered Institution of Building Services Engineers, CIBSE (2005) Transportation Systems in Buildings
21.
Kukhnin A, Li T, Yates M, Tokarenko A, Bell A (2016) Global Elevators and Escalators Industry Primer
22.
Andrew J, Kaczmarczyk S (2011) Systems Engineering of Elevators. Elevator World
23.
Ruoho S, Kolehmainen J, Ikäheimo J, Arkkio A (2010) Interdependence of demagnetization, loading, and temperature rise in a permanent-magnet synchronous motor. IEEE Trans Magn 46(3 PART 2):949–953CrossRef
24.
González M, Esteban E, Salgado O, Urchegui MA, Croes J, Pluymers B, Desmet W (2016) Model-based virtual sensing approaches for the estimation of forces in guiding systems. In: ISMA International Conference on Noise and Vibration Engineering, Leuven
25.
Gonzalez M, Salgado O, Croes J, Pluymers B, Desmet W (2017) Condition monitoring of guiding systems by means of model-based virtual sensors, pp 1–8
26.
Krause P, Wasynczuk O, Sudhoff S, Pekarek S (2013) Analysis of Electric Machinery and Drive Systems, vol 75. Wiley, HobokenCrossRef
27.
Esteban E, Salgado O, Iturrospe A, Isasa I (2016) Model-based approach for elevator performance estimation. Mech Syst Signal Process 68–69:125–137CrossRef
28.
Esteban E, Salgado O, Iturrospe A, Isasa I (2017) Design methodology of a reduced-scale test bench for fault detection and diagnosis. Mechatronics 47:14–23CrossRef
Metadata
Title
Model-Based State Estimation for the Diagnosis of Multiple Faults in Non-linear Electro-Mechanical Systems
Authors
Mikel Gonzalez
Oscar Salgado
Jan Croes
Bert Pluymers
Wim Desmet
Copyright Year
2019
Book
Advances in Condition Monitoring of Machinery in Non-Stationary Operations

Print ISBN: 978-3-030-11219-6

Electronic ISBN: 978-3-030-11220-2

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-11220-2_9

Premium Partners

    Image Credits