Measurement Technique for Quantifying Structure Borne and Air Borne Noise Levels in Utility Vehicle 2014-01-0003
Accurate quantification of structure borne noise is a challenging task for NVH engineers. The structural excitation sources of vibration and noise such as powertrain and suspension are connected to the passenger compartment by means of elastomer mounts and spring elements. The indirect force estimation methods such as complex dynamic stiffness method and matrix inversion method are being used to overcome the limitations of direct measurement. In many practical applications, the data pertaining to load dependent dynamic stiffness of the connections especially related to mounts is not available throughout the frequency range of interest which limits the application of complex dynamic stiffness method. The matrix inversion method mainly suffers from the drawback that it needs operational data not contaminated by the effect of other forces which are not considered for calculation. In this paper, a new method is proposed in which the structure borne noise associated with powertrain is quantified easily and reliably. The powertrain is disconnected at its mounting locations from the vehicle without changing its position and orientation. The test is conducted in idling, stationary run up and 2nd gear run up conditions on plain road surface. The difference in the noise levels of tests conducted with and without mounts is the structure borne contribution from the powertrain. The technique is also helped in reducing the time taken for matrix inversion method without the need for complete removal of source. The new method also helps in finding the dynamic stiffness of the powertrain mounts over the wide frequency band of interest.
Citation: Rao, M., Frank, J., and Raghavendran, P., "Measurement Technique for Quantifying Structure Borne and Air Borne Noise Levels in Utility Vehicle," SAE Technical Paper 2014-01-0003, 2014, https://doi.org/10.4271/2014-01-0003. Download Citation
Author(s):
Manchi Venkateswara Rao, Jos Frank, Prasath Raghavendran