Feature extraction under bounded noise background and its application in low speed bearing fault diagnosis
Artykuł w czasopiśmie
MNiSW
70
Lista 2021
| Status: | |
| Autorzy: | Zhang Jin, Yang Jianhua, Litak Grzegorz, Hu Eryi |
| Dyscypliny: | |
| Aby zobaczyć szczegóły należy się zalogować. | |
| Rok wydania: | 2019 |
| Wersja dokumentu: | Drukowana | Elektroniczna |
| Język: | angielski |
| Numer czasopisma: | 7 |
| Wolumen/Tom: | 33 |
| Strony: | 3193 - 3204 |
| Web of Science® Times Cited: | 9 |
| Scopus® Cytowania: | 11 |
| Bazy: | Web of Science | Scopus |
| Efekt badań statutowych | NIE |
| Materiał konferencyjny: | NIE |
| Publikacja OA: | NIE |
| Abstrakty: | angielski |
| We investigated the low speed bearing fault diagnosis under bounded noise background in three typical conditions. These situations included when the frequency of bounded noise was much larger, a little larger, and a little smaller than the driving frequency. Through the investigation of a harmonic signal in these three situations, we found the effect of stochastic resonance method was the best in the first situation, while it was invalid in the third situation. For the third situation, we introduced the vibrational resonance method by adding an auxiliary signal to extract the character frequency successfully. Then we also studied the low speed experimental bearing fault signal under bounded noise background, and it showed the same results as those of the simulation harmonic signal case. The methods and resultsof this paper might be useful in practical engineering, especially in extracting the weak character signal in the bounded noise background. |
