Zaznavanje napak na elektromotorjih s pomočjo psihoakustičnih cenilk zvoka

magistrsko delo magistrskega študijskega programa II. stopnje Strojništvo

Erik Rutar (Author), Jurij Prezelj (Mentor)

Abstract

Zaradi močne konkurence na trgu je kontrola hrupa elektromotorjev vedno bolj prisotna in vedno bolj stroga, zato podjetje teži k nenehnemu znižanju hrupa elektromotorjev. Prav tako je z ustrezno obdelavo zvoka, lahko le-ta močan indikator napak na elektromotorjih. Podjetje že izvaja različne kontrolne meritve, ki določajo ustreznost motorja, a se pri montaži pojavijo napake, ki jih je težko zaznati preko merjenja teh fizikalnih veličin. Z obstoječimi kontrolnimi napravami za hrup, pa se opazuje le absolutne vrednosti hrupa in vibracij (klasičen pristop), kateri se večkrat izkaže za neučinkovitega. V delu je predstavljen povzetek raziskave, ki je bila opravljena na 20-ih vzorcih elektromotorjev. Cilj naloge pa je preveriti ali lahko s pomočjo računanja psiho-akustičnih cenilk ločimo ustrezne vzorce od neustreznih.

Keywords

magistrske naloge;elektromotorji;hrup;vibracije;psiho-akustika;cenilke;klasifikacija;

Data

Language:	Slovenian
Year of publishing:	2018
Typology:	2.09 - Master's Thesis
Organization:	UL FS - Faculty of Mechanical Engineering
Publisher:	[E. Rutar]
UDC:	621.313.13:534(043.2)
COBISS:	16426779
Views:	960
Downloads:	196
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	English
Secondary title:	Detecting errors on electric motors using psychoacoustic sound features
Secondary abstract:	Because of the strong competition in electric motors manufacturing, manufacturers put more and more effort in noise control. Besides, noise might be a very strong indicator of possible motor errors, if observed properly. Company is already measuring many properties of electric motor although during the mounting process of electric motors, many mistakes can be done and some of them can not be detected with those measurements. Existing control devices are based on absolute values of noise and vibration (classic approach), which in many cases, doesn't seem to be effective, so use of a psycho-acoustic approach in failure detection, might be worth trying. In this work, the research was done using 20 sample electric motors. The goal of the research was to determine, whether we can distinguish between good and bad samples, by extracting and evaluating sound features.
Secondary keywords:	electric motors;noise;vibration;psycho-acoustics;features;classification;
Type (COBISS):	Master's thesis/paper
Study programme:	0
Embargo end date (OpenAIRE):	1970-01-01
Thesis comment:	Univ. Ljubljana, Fak. za strojništvo
Pages:	XXIV, 66 str.
ID:	10958900