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
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Bücher
Zeitschriften
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
MTZ-Fachkongress

Antriebe und Energiesysteme von morgen


Austausch von Automobil- und Energiewirtschaft

Am 14./15. Mai geht es in Chemnitz um die Mobilitätswende durch Elektro- und Wasserstofffahrzeuge.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:
Simulation and Segmentation Techniques for Crop Maturity Identification of Pineapple Fruit Kapitel lesen Erstes Kapitel lesen

2017 | OriginalPaper | Buchkapitel

A Hardware and Software Integration Approach for Development of a Non-invasive Condition Monitoring Systems for Motor-Coupled Gears Faults Diagnosis

verfasst von : Muhammad Irfan, Nordin Saad, Rosdiazli Ibrahim, Vijanth S. Asirvadam, Nursyarizal Mohd Nor, Abdullah Alwadie, Muhammad Aman Sheikh

Erschienen in: Modeling, Design and Simulation of Systems

Verlag: Springer Singapore

Einloggen

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

search-config
loading …

Abstract

A non-invasive condition monitoring system for diagnosis of faults is vital for induction motors to operate safely and reliably. The currently used invasive techniques need direct access to the motor to collect and analyze data. Furthermore, the sensors used in invasive techniques are relatively expensive. This paper presents the development of hardware and software integrations for non-invasive diagnostic system to monitor specifically motor-coupled gear defects. The proposed system employs instantaneous power analysis, a unique technique for diagnostic condition monitoring which allows real-time non-stop tracking as well as assesses the severity of the defects. This technique can be adopted for decision-making that is not only fast but reliable. The severity of different gear defects have been studied experimentally, and the results were analyzed. The effectiveness of the proposed method has been verified through experimentation from the actual hardware implementation through the system-design platform and development environment software tool, LabVIEW.

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 Aspen Plus® Simulation Studies of Steam Gasification in Fluidized Bed Reactor for Hydrogen Production Using Palm Kernel Shell
Nächstes Kapitel Application of Brushless Motor Speed Control System in Wave Power Generation Technology
Literatur
1.
Irfan, M., Saad, N., Ibrahim, R., Asirvadam, V.S.: A non invasive method for condition monitoring of induction motors operating under arbitrary loading conditions. Arab. J. Sci. Eng. 41(9), 3463–3471 (2016)CrossRef
2.
Irfan, M., Saad, N., Ibrahim, R., Asirvadam, V.S.: Condition monitoring of induction motors via instantaneous power analysis, J. Intell. Manuf. doi:10.​1007/​s10845-015-1048-2, February 2015
3.
Irfan, M., Saad, N., Ibrahim, R., Asirvadam, V.S.: An intelligent diagnostic condition monitoring system for ac motors via instantaneous power analysis. Int. Rev. Electr. Eng. 8(2), 664–672 (2013)
4.
Irfan, M., Saad, N., Ibrahim, R., Asirvadam, V.S., Hung, N.T., Magzoub, M.: Analysis of bearing surface roughness defects in induction motors. J. Fail. Anal. Prev. 15(5), 730–736 (2015)CrossRef
5.
Irfan, M., Saad, N., Ibrahim, R., Asirvadam, V.S.: An online condition monitoring system for induction motors via instantaneous power analysis. J. Mech. Sci. Technol. 29(4), 1483–1492 (2015)CrossRef
6.
Irfan, M., Saad, N., Ibrahim, R., Asirvadam, V.S.: An intelligent fault diagnosis of induction motors in an arbitrary noisy environment, J. Nondestr. Eval. 35(12) doi:10.​1007/​s10921-015-0327-3, March 2016
7.
Kia, S.H., Henao, H., Capolino, G.-A.: Development of a test bench dedicated to condition monitoring of wind turbines, IEEE-IECON, Dallas (TX, USA), 28 October–1 November 2014
8.
Dalpiaz, G., Rivola, A., Rubini, R.: Effectiveness and sensitivity of vibration processing techniques for local fault detection in gears. Mech. Syst. Signal Process. 14(3), 387–412 (2000)CrossRef
9.
Baydar, N., Ball, A.: Case study-detection of gear failures via vibration and acoustic signals using wavelet transform. Mech. Syst. Signal Process. 17, 787–804 (2003)CrossRef
10.
Loutas, T.H., Sotiriades, G., Kalaitzoglou, I., Kostopoulos, V.: Condition monitoring of a single-stage gearbox with artificially induced gear cracks utilizing on-line vibration and acoustic emission measurements. Appl. Acoust. 70, 1148–1159 (2009)CrossRef
11.
Mohanty, A.R., Kar, C.: Monitoring gear vibrations through motor current signature analysis and wavelet transform. Mech. Syst. Signal Process. 20(1), 158–187 (2006)CrossRef
12.
Feki, N., Clerc, G., Velex, P.: An integrated electro-mechanical model of motor-gear units - applications to tooth fault detection by electric measurements. Mech. Syst. Signal Process. 29, 377–390 (2012)CrossRef
13.
Strangas, E.G.: Response of electrical drives to gear and bearing faults - diagnosis under transient and steady state conditions. In: Proceedings of Workshop on Electrical Machines Design Control and Diagnosis (WEMDCD), invited paper, Paris (France), pp. 289–297, 11–12 March 2013
14.
Henao, H., Kia, S.H., Capolino, G.-A.: Torsional vibration assessment and gear fault diagnosis in railway traction system. IEEE Trans. Ind. Electron. 58(5), 1707–1717 (2011)CrossRef
15.
Bogiatzidis, I., Safacas, A., Mitronikas, E.: Detection of backlash phenomena appearing in a single cement kiln drive using the current and the electromagnetic torque signature. IEEE Trans. Ind. Electron. 60(8), 3441–3453 (2013)CrossRef
16.
Trajin, B., Regnier, J., Faucher, J.: Comparison between stator current and estimated mechanical speed for the detection of bearing wear in asynchronous drives. IEEE Trans. Ind. Electron. 56(11), 4700–4709 (2009)CrossRef
17.
Ibrahim, A., El-Badaoui, M., Guillet, F., Bonnardot, F.: A new bearing fault detection method in induction machines based on instantaneous power factor. IEEE Trans. Ind. Electron. 55(12), 4252–4259 (2008)CrossRef
18.
Blödt, M., Chabert, M., Regnier, J., Faucher, J.: Mechanical load fault detection in induction motors by stator current time-frequency analysis. IEEE Trans. Ind. Appl. 42(6), 1454–1463 (2006)CrossRef
19.
Mohanty, A.R., Kar, C.: Fault detection in a multistage gearbox by demodulation of motor current waveform. IEEE Trans. Ind. Electron. 53(4), 1285–1297 (2006)CrossRef
20.
Kar, C., Mohanty, A.R.: Vibration and current transient monitoring for gearbox fault detection using multiresolution Fourier transform. J. Sound Vib. 311(1/2), 109–132 (2008)CrossRef
21.
Kia, S.H., Henao, H., Capolino, G.-A.: Analytical and experimental study of gearbox mechanical effect on the induction machine stator current signature. IEEE Trans. Ind. Electron. 45(4), 1405–1415 (2009)
22.
Kia, S.H., Henao, H., Capolino, G.A.: Gear tooth surface damage fault detection using induction machine stator current space vector analysis. IEEE Trans. Ind. Electron. 62(3), 1866–2001 (2015)CrossRef
23.
Kia, S.H., Henao, H., Capolino, G.-A.: Torsional vibration effects on induction machine current and torque signatures in gearbox-based electromechanical system. IEEE Trans. Ind. Electron. 56(11), 4689–4699 (2009)CrossRef
24.
Feki, N., Clerc, G., Velex, P.: Gear and motor fault modeling and detection based on motor current analysis. Electric Power Syst. Res. 95, 28–37 (2013)CrossRef
25.
Daneshi-Far, Z., Henao, H., Capolino, G.-A.: Planetary gearbox effects on induction machine in wind turbine: modeling and analysis, In: Proceedings of International Conference on Electrical Machines (ICEM), Marseille (France), pp. 1790–1796, 2–5 September 2012
26.
Ottewill, J.R., Orkisz, M.: Condition monitoring of gearboxes using synchronously averaged electric motor signals. Mech. Syst. Signal Process. 38(2), 482–498 (2013)CrossRef
27.
Girsang, I.P., Dhupia, J.S., Muljadi, E., Singh, M., Pao, L.Y.: Gearbox and drive train models to study of dynamic effects of modern wind turbines. IEEE Trans. Ind. Appl. 50, 3777–3786 (2014)CrossRef
28.
Huh, K.-K., Lorenz, R.D., Nagel, N.J.: Gear fault diagnostics integrated in the motion servo drive for electromechanical actuators. IEEE Trans. Ind. Appl. 48(1), 142–150 (2012)CrossRef
29.
Bogiatzidis, I.X., Safacas, A.N., Mitronikas, E.D.: Detection of backlash phenomena appearing in a single cement kiln drive using the current and the electromagnetic torque signature. IEEE Trans. Ind. Electron. 60(8), 3441–3453 (2013)CrossRef
30.
Kia, S.H., Henao, H., Capolino, G.-A.: A real-time platform dedicated to on-line gear tooth surface damage fault detection in induction machines. In: International Conference on Electrical Machines (ICEM), Berlin, 2–5 September 2014
31.
Kia, S.H., Henao, H., Capolino, G.-A.: Gear tooth surface damage fault detection using induction machine stator current space vector analysis. IEEE Trans. Ind. Electron. 62(3), 1866–1878 (2015)CrossRef
32.
Fournier, E., et al.: Current-based detection of mechanical unbalance in an induction machine using spectral kurtosis with reference. IEEE Trans. Ind. Electron. 62(3), 1879–1887 (2015)CrossRef
33.
Irfan, M., Saad, N., Ibrahim, R., Asirvadam, V.S., Hung, N.T.: Analysis of bearing outer race defects in induction motor. In: The 5th IEEE International Conference on Intelligent and Systems (ICIAS), Kuala Lumpur, Malaysia, June 2014
34.
Irfan, M., Saad, N., Ibrahim, R., Asirvadam, V.S.:An intelligent diagnostic system for condition monitoring of ac motors. In: The 8th IEEE Conference on Industrial Electronics and Applications, Melbourne, Australia, June 2013
35.
Irfan, M., Saad, N., Ibrahim, R., Asirvadam, V.S., Hung, N.T.: A non-invasive fault diagnosis system for induction motors in noisy environment. In: IEEE International Conference on Power and Energy (PECon), Kuching, Malaysia, pp. 271–276, December 2014
36.
Irfan, M., Saad, N., Ibrahim, R., Asirvadam, V.S.: An approach to diagnose inner race surface roughness faults in bearings of induction motors. In: IEEE International Conference on Signal and Image Analysis (ICSIPA), Kuala Lumpur, Malaysia, October 2015
37.
38.
Irfan, M., Saad, N., Ibrahim, R., Asirvadam, V.S.: Development of an intelligent condition monitoring system for AC induction motors using PLC. In: 2013 IEEE Business Engineering and Industrial Applications Colloquium (BEIAC) (2013)
39.
Bishop, R.H.: Learning with LabVIEW 8, Pearson/Prentice Hall (2007)
Metadaten
Titel
A Hardware and Software Integration Approach for Development of a Non-invasive Condition Monitoring Systems for Motor-Coupled Gears Faults Diagnosis
verfasst von
Muhammad Irfan
Nordin Saad
Rosdiazli Ibrahim
Vijanth S. Asirvadam
Nursyarizal Mohd Nor
Abdullah Alwadie
Muhammad Aman Sheikh
Copyright-Jahr
2017
Verlag
Springer Singapore
Buch
Modeling, Design and Simulation of Systems

Print ISBN: 978-981-10-6462-3

Electronic ISBN: 978-981-10-6463-0

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-981-10-6463-0_55

Premium Partner

    Bildnachweise