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This paper describes new method for selecting optimal field points in Inverse-Numerical Acoustic analysis (INA), and its application to construction of a sound source model for diesel engines. INA identifies the surface vibration of a sound source by using acoustic transfer functions and actual sound pressures measured at field points located near the sound source. When measuring sound pressures with INA, it is necessary to determine the field point arrangement. Increased field points leads to longer test and analysis time. Therefore, guidelines for selecting the field point arrangement are needed to conduct INA efficiently. The authors focused on the standard deviations of distance between sound source elements and field points and proposed a new guideline for optimal field point selection in our past study. In that study, we verified the effectiveness of this guideline using a simple plate model.

This paper describes the identification of a sound source model for diesel engines installed on agricultural machines by using Inverse-Numerical Acoustic (INA) analysis, and noise predictions using the sound source model identified by INA. INA is a method of identifying surface vibrations from surrounding sound pressures. This method can be applied to sound sources with complicated shapes like those in engines. Although many studies on INA have been conducted, these past studies have focused on improvements to the identified accuracy and prediction of noise in free sound field or hemi-free sound field. The authors accurately predicted the sound pressure levels of engine enclosures using a sound source model identified by INA and a boundary element method (BEM). However, we had not yet verified the effectiveness of this sound source model against enclosures that had sound absorbing materials and openings.