Identification of unbalance in a rotor system using a joint input-state estimation technique

A technique for estimation of unbalance parameters of rotor-bearing systems has been presented and verified by numerical simulations and experimental measurements. The method uses system model and response measurements for unbalance identification. A rigid rotor model is considered in the present wo...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Journal of sound and vibration Ročník 442; s. 414 - 427
Hlavní autoři: Shrivastava, Akash, Mohanty, Amiya R.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Amsterdam Elsevier Ltd 03.03.2019
Elsevier Science Ltd
Témata:
ISSN:0022-460X, 1095-8568
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:A technique for estimation of unbalance parameters of rotor-bearing systems has been presented and verified by numerical simulations and experimental measurements. The method uses system model and response measurements for unbalance identification. A rigid rotor model is considered in the present work. Unbalance force estimation using a joint-input state estimation technique is followed by unbalance parameter identification using least-squares fitting. Results are presented for different shaft speeds and measurement noise levels. Unbalance parameters are identified accurately with noisy measurements, which verifies the robustness of the proposed technique. The proposed technique is verified on a rotor-bearing test rig for different unbalance configurations. Sensitivity analysis is also performed by varying the values of system parameters. •A model-based approach for unbalance parameter estimation is proposed.•Unbalance force is estimated using a joint-input state estimation technique.•Numerical and experimental results are presented for the verification.•Effect of measurement noise is shown.•Sensitivity analysis is performed by varying system parameters.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0022-460X
1095-8568
DOI:10.1016/j.jsv.2018.11.019