ACS Applied Computer Science

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APPLICATION OF IMAGE ANALYSIS TO THE IDENTIFICATION OF MASS INERTIA MOMENTUM IN ELECTROMECHANICAL SYSTEM WITH CHANGEABLE BACKLASH ZONE

This paper presents a new method of identification of inertia moment of reduced masses on a shaft of an induction motor drive being a part of an electromechanical system. The study shows the results of simulations performed on the tested model of a complex electromechanical system during some changes of a backlash zone width. An analysis of wavelet scalograms of the examined signals carried out using a clustering technique was applied in the diagnostic algorithm. The correctness of the earliest fault detection has been verified during monitoring and identification of mass inertia moment for state variables describing physical quantities of a tested complex of the electromechanical system.
  • APA 6th style
Tomczyk, M., Plichta, A., & Mikulski, M. (2019). Application of image analysis to the identification of mass inertia momentum in electromechanical system with changeable backlash zone. Applied Computer Science, 15(3), 87-102. 
  • Chicago style
Tomczyk, Marcin, Anna Plichta, and Mariusz Mikulski. "Application of Image Analysis to the Identification of Mass Inertia Momentum in Electromechanical System with Changeable Backlash Zone." Applied Computer Science 15, no. 3 (2019): 87-102.
  • IEEE style
M. Tomczyk, A. Plichta, and M. Mikulski, "Application of image analysis to the identification of mass inertia momentum in electromechanical system with changeable backlash zone," Applied Computer Science, vol. 15, no. 3, pp. 87-102, 2019, doi: 10.23743/acs-2019-24.
  • Vancouver style
Tomczyk M, Plichta A, Mikulski M. Application of image analysis to the identification of mass inertia momentum in electromechanical system with changeable backlash zone. Applied Computer Science. 2019;15(3):87-102.