Autor: Tomczyk, Mariusz - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Application of wavelet – neural method to detect backlash zone in electromechanical systems generating noises
Autorzy:: Tomczyk, Marcin
Plichta, Anna
Mikulski, Mariusz
Powiązania:: https://bibliotekanauki.pl/articles/117667.pdf
Data publikacji:: 2019
Wydawca:: Polskie Towarzystwo Promocji Wiedzy
Tematy:: induction motor
wavelet transformation
backlash zone
neural networks
silnik indukcyjny
transformacja falkowa
strefa luzu
sieci neuronowe
Opis:: 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.
Źródło:: Applied Computer Science; 2019, 15, 4; 93-108
1895-3735
Pojawia się w:: Applied Computer Science
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: Identification of a Backlash Zone in an Electromechanical System Containing Changes of a Mass Inertia Moment Based on a Wavelet–Neural Method
Autorzy:: Tomczyk, Marcin
Borowik, Barbara
Mikulski, Mariusz
Powiązania:: https://bibliotekanauki.pl/articles/118045.pdf
Data publikacji:: 2018
Wydawca:: Polskie Towarzystwo Promocji Wiedzy
Tematy:: inertia moment
induction motor
wavelet transformation
backlash zone
neural network weights
moment bezwładności
silnik indukcyjny
transformacja falkowa
strefa luzu
sieci neuronowe
Opis:: 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.
Źródło:: Applied Computer Science; 2018, 14, 4; 54-69
1895-3735
Pojawia się w:: Applied Computer Science
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 3.

Tytuł:: Application of image analysis to the identification of mass inertia momentum in electromechanical system with changeable backlash zone
Autorzy:: Tomczyk, Marcin
Plichta, Anna
Mikulski, Mariusz
Powiązania:: https://bibliotekanauki.pl/articles/118237.pdf
Data publikacji:: 2019
Wydawca:: Polskie Towarzystwo Promocji Wiedzy
Tematy:: inertia moment
induction motor
wavelet transformation
backlash zone
membership function
moment bezwładności
silnik indukcyjny
transformacja falkowa
strefa luzu
funkcja przynależności
Opis:: 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.
Źródło:: Applied Computer Science; 2019, 15, 3; 87-102
1895-3735
Pojawia się w:: Applied Computer Science
Dostawca treści:: Biblioteka Nauki

Artykuł

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