Vibroacoustic Optimisation of Tractor Cabin and Correlation with Experimental Data

2017-01-1847

06/05/2017

Features
Event
Noise and Vibration Conference and Exhibition
Authors Abstract
Content
Tractor operators prefer to drive more comfortable tractors in the recent years. The high noise and vibration levels, to which drivers of agricultural tractor are often exposed for long periods of time, have a significant part in the driver’s fatigue and may lead to substantial hearing impairment and health problems. Therefore, it is essential for an optimal cabin design to have time and cost effective analysis tools for the assessment of the noise and vibration characteristics of various design alternatives at both the early design stages and the prototype testing phase. Airborne excitation and Structure Borne excitation are two types of dynamic cabin excitations mainly cause the interior noise in a driver’s cabin. Structure-borne excitation is studied in this paper and it consists of dynamic forces, which are directly transmitted to the cabin through the cabin suspension. These transmitted forces introduce cabin vibrations, which in turn generate interior noise. This study comprises the correlation and verification of low frequency acoustic performance of a tractor cabin and development for interior noise. In order to correlate the model, finite element analysis and tests were performed simultaneously in order to update the model. Then, results from analysis were compared against the subjective comments and objective levels. With the help of this work, a methodology for correlating complex models with local information was developed. In order to illustrate the efficiency and reliability of the various vibro-acoustic analysis procedures, all experimental and numerical procedures have been applied and evaluated for the tractor cabin model.
Meta TagsDetails
DOI
https://doi.org/10.4271/2017-01-1847
Pages
8
Citation
Shaik Mohammad, A., Vijayakumar, R., and rao.P, N., "Vibroacoustic Optimisation of Tractor Cabin and Correlation with Experimental Data," SAE Technical Paper 2017-01-1847, 2017, https://doi.org/10.4271/2017-01-1847.
Additional Details
Publisher
Published
Jun 5, 2017
Product Code
2017-01-1847
Content Type
Technical Paper
Language
English