ACS Applied Computer Science

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IDENTIFICATION OF A BACKLASH ZONE IN AN ELECTROMECHANICAL SYSTEM CONTAINING CHANGES OF A MASS INERTIA MOMENT BASED ON A WAVELET–NEURAL METHOD

In this article a new method of identification of a backlash zone width in a structure of an electromechanical system has been presented. The results of many simulations in a tested model of a complex electromechanical system have been taken while changing a value of a reduced masses inertia moment on a shaft of an induction motor drive. A wavelet analysis of tested signals and analysis of weights that have been obtained during a neural network supervised learning - have been applied in a diagnostic algorithm. The proposed algorithm of detection of backlash zone width, represents effective diagnostic method of a system at changing dynamic conditions, occurring also as a result of mass inertia moment changes.
  • APA 6th style
Tomczyk, M., Borowik, B., & Mikulski, M. (2018). Identification of a backlash zone in an electromechanical system containing changes of a mass inertia moment based on a wavelet–neural method. Applied Computer Science, 14(4), 54-69. doi:10.23743/acs-2018-29
  • Chicago style
Tomczyk, Marcin, Barbara Borowik, and Mariusz Mikulski. "Identification of a Backlash Zone in an Electromechanical System Containing Changes of a Mass Inertia Moment Based on a Wavelet–Neural Method." Applied Computer Science 14, no. 4 (2018): 54-69.
  • IEEE style
M. Tomczyk, B. Borowik, and M. Mikulski, "Identification of a backlash zone in an electromechanical system containing changes of a mass inertia moment based on a wavelet–neural method," Applied Computer Science, vol. 14, no. 4, pp. 54-69, 2018.
  • Vancouver style
Tomczyk M, Borowik B, Mikulski M. Identification of a backlash zone in an electromechanical system containing changes of a mass inertia moment based on a wavelet–neural method. Applied Computer Science. 2018;14(4):54-69.