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Vibration Modeling and Modification of Cutting Platform in a Harvest Combine by Means of Operational Modal Analysis (OMA)

Reza Ebrahimi, Mohsen Esfahanian, Saeed Ziaei-Rad

Measurement, Volume 46, Issue 10, December 2013, Pages 3959–3967

 

ABSTRACT

Vibration in combine cutting platform causes increase in grain loss, reduction of vehicle lifetime and driver’s comfort, and also affects the machine working precision. In order to determine vibration behavior of a mechanical structure, the model which relates acting forces on the structure with the resulting responses of it plays a significant role. For a great deal of mechanical structures, only response data are measurable while the actual loading conditions are unknown. Therefore, the system identification process will need to build on the output-only data. The use of such processes allows the identification of modal models of structures which are excited by unknown ambient vibration. In this contribution, controlled vibration experiments were conducted on cutting platform of a combine in order to recognize and reduce its vibration problem. A finite element model is constructed representing the vibration behavior of the cutting platform. Also, the frequency domain decomposition (FDD) technique is used to estimate the modal parameters of vibrating structures in operational conditions. Then, the finite element model is successfully updated by comparing the estimated results of the operational modal analysis. It is found that there is a resonance condition around 50 Hz. Then, the mass change strategy is used to estimate the scaling-factor and frequency response function (FRF) matrix. Finally, the resonance condition and subsequently vibration of cutting platform is reduced by the structural modification technique. As a result of this modification, natural frequency of fifth mode shape (50 Hz) of the combine cutting platform is shifted to 48 Hz.

 

Keywords:

Cutting platform; FDD technique; Operational modal analysis; Mass modification

 

Link to Journal Webpage

 

Journal Papers
Month/Season: 
December
Year: 
2013

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