In any off-highway machinery throughout the product development cycle, noise is
considered an important characteristic. This characteristic drives the product
quality, safety, and productivity and meets the homologation requirements.
Identifying the critical noise source and finding out the true root cause of the
noise source is a very critical element in improving the design to reduce the
noise levels. A systematic approach is needed to understand the behavior of the
system, which can be achieved through collaborative efforts among the analysis,
design, and testing teams.
This paper describes how virtual analysis helps to determine the main source of
noise radiation in the audible frequency range of the human ear. The sound
pressure level (SPL) in the test data at the end unit drive of an agriculture
machine showed high peaks at a few frequencies in the critical frequency range.
The spectral content remains the same regardless of the backshaft speed. The
noise goes away when the tensioner sprocket center nut is loosened. In the
initial stage, the accuracy of the end unit drive finite element (FE) model is
ensured by comparing the virtual driving point impedances with test data for
both loose and tight nut conditions. In the later stage, the acoustic finite
element method adaptive order (FEM AO) model is developed [1] and correlated with test data of SPLs. In the final
stage, panel contribution analysis is carried out to determine the critical
noise-radiating component. This validated model will be confidently used to
improve the design further.