ISSN 2353-6977 (Online)
This paper presents a method of identifying the width of backlash zone in an electromechanical system generating noises. The system load is a series of rectangular pulses of constant amplitude, generated at equal intervals. The need for identification of the backlash zone is associated with a gradual increase of its width during the drive operation. The study uses wavelet analysis of signals and analysis of neural network weights obtained from the processing without supervised learning. The time-frequency signal representations of accelerations of the mechanical load components were investigated.
- APA 6th style
Tomczyk, M., Plichta, A., & Mariusz, M. (2019). Application of wavelet –neural method to detect backlash zone in electromechanical systems generating noises. Applied Computer Science, 15(4), 93-108. doi:10.23743/acs-2019-32
- Chicago style
Tomczyk, Marcin, Anna Plichta, and Mikulski Mariusz. "Application of Wavelet –Neural Method to Detect Backlash Zone in Electromechanical Systems Generating Noises." Applied Computer Science 15, no. 4 (2019): 93-108.
- IEEE style
M. Tomczyk, A. Plichta, and M. Mariusz, "Application of wavelet –neural method to detect backlash zone in electromechanical systems generating noises," Applied Computer Science, vol. 15, no. 4, pp. 93-108, 2019, doi: 10.23743/acs-2019-32.
- Vancouver style
Tomczyk M, Plichta A, Mariusz M. Application of wavelet –neural method to detect backlash zone in electromechanical systems generating noises. Applied Computer Science. 2019;15(4):93-108.
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