Time-Frequency Analysis of Accelerometery Data for Detection and Identification of Faults on a Pneumatic Production Machine
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F22%3APU147630" target="_blank" >RIV/00216305:26210/22:PU147630 - isvavai.cz</a>
Výsledek na webu
<a href="https://ieeexplore-ieee-org.ezproxy.lib.vutbr.cz/stamp/stamp.jsp?tp=&arnumber=9983139" target="_blank" >https://ieeexplore-ieee-org.ezproxy.lib.vutbr.cz/stamp/stamp.jsp?tp=&arnumber=9983139</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ME54704.2022.9983139" target="_blank" >10.1109/ME54704.2022.9983139</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Time-Frequency Analysis of Accelerometery Data for Detection and Identification of Faults on a Pneumatic Production Machine
Popis výsledku v původním jazyce
As pneumatic cylinders are nowadays an integral part of manufacturing machines in a variety of industries, there is a growing demand for development of cost-effective and reliable techniques for detection and identification of faults on these machines. In this paper, we propose a novel algorithm for condition indicator extraction from the time-frequency domain. The algorithm uses signal-based condition indicators extracted from a frequency spectrum obtained by a modified version of the Short-Time Fourier Transform (STFT). The aim of this article is to demonstrate that the processing of readings from an accelerometer by the proposed method provides higher accuracy in detecting and identifying faults. We achieve all this by processing only a fraction of the measured signal. As result of that, the computational requirements are decreasing, leading to lower hardware cost which is advantageous as the proposed method is developed for industrial deployment.
Název v anglickém jazyce
Time-Frequency Analysis of Accelerometery Data for Detection and Identification of Faults on a Pneumatic Production Machine
Popis výsledku anglicky
As pneumatic cylinders are nowadays an integral part of manufacturing machines in a variety of industries, there is a growing demand for development of cost-effective and reliable techniques for detection and identification of faults on these machines. In this paper, we propose a novel algorithm for condition indicator extraction from the time-frequency domain. The algorithm uses signal-based condition indicators extracted from a frequency spectrum obtained by a modified version of the Short-Time Fourier Transform (STFT). The aim of this article is to demonstrate that the processing of readings from an accelerometer by the proposed method provides higher accuracy in detecting and identifying faults. We achieve all this by processing only a fraction of the measured signal. As result of that, the computational requirements are decreasing, leading to lower hardware cost which is advantageous as the proposed method is developed for industrial deployment.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
—
OECD FORD obor
20204 - Robotics and automatic control
Návaznosti výsledku
Projekt
—
Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2022
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
Proceedings of the 2022 20th International Conference on Mechatronics - Mechatronika (ME)
ISBN
978-1-6654-1040-3
ISSN
—
e-ISSN
—
Počet stran výsledku
6
Strana od-do
„“-„“
Název nakladatele
Institute of Electrical and Electronics Engineers
Místo vydání
Plzeň
Místo konání akce
Pilsen
Datum konání akce
7. 12. 2022
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
000947331700032