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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.

This paper describes an identification of a sound source model for a diesel engine installed on an agricultural machine by Inverse-Numerical Acoustic analysis (INA), and the applicability of the identified sound source model. INA is a method to identify surface vibrations from surrounding sound pressures. This method is applicable for a complicated-shaped sound source like an engine. In order to confirm the accuracy of the identified sound source model, the surface vibrations of the engine are compared with the measured results. Moreover, in the condition of the simulated engine room, the surrounding sound pressure levels of the engine are predicted using the sound source model and the boundary element method (BEM). For the verification of the prediction accuracy, the surrounding sound pressures of the engine are measured using the testing device which simulated actual engine room, namely an enclosure.

This paper describes a prediction of vibration and the transfer path analysis (TPA) using an engine multi body dynamics (MBD) model and measured frequency response functions (FRFs). TPA is used in order to analyze each contribution of vibration transfer paths. In the TPA, input forces from vibration source to passive part should be identified accurately. In the traditional TPA, an identification of input forces is done using only experimental results. Therefore, a parametric study to an improvement of a structure or an isolation system is impossible. In this study, the MBD model of engine is constructed, and input forces from engine to mainframe of agriculture machine are predicted. The accuracy of prediction is confirmed, compared with the results from the traditional TPA method. The contribution of each transfer path is analyzed, and the vibration levels of operator position are predicted using the measured FRFs and the simulated input forces.

This paper describes how we predict the stress of engine components resulting from vibration of engine, using MBD (Multi Body Dynamics) and FEA (Finite Element Analysis). In a development of industrial engine, many engine models which are installed on various machines are developed. Depending on operating condition of machine, many kinds of components are designed. Therefore, in order to shorten a development period, it is important to predict accurately stress of components and evaluate its durability in the design phase. In this study, for exhaust silencer, the stress of engine components which are caused from of engine vibration is calculated by FEA and MBD and the accuracy of prediction is confirmed as compared with the experiment result. In addition, the stress of oil suction pipe is predicted. As vibrational characteristic of oil suction pipe is influenced by lube oil, virtual mass method is used in order to take into consideration the influence of fluid which is surrounding it.

This paper describes how we design engine mount layout, in order to isolate a machine from engine vibration. Natural frequency of vibration isolation system is calculated by Finite Element Method. We focus on the exciting force direction and mode vectors calculated by FEM, and optimize engine mount layout. In the optimization process, we use Modal Assurance Criterion (MAC) to track mode shape which is corresponded with exciting force, and create the maps of MAC value and natural frequency against design parameters. Proper engine mount layout is searched within our design parameters. Finally, multi body dynamics model of engine is constructed and the effect of mount layout which is optimized is confirmed. As a result, the transfer force is reduced 75 % against original design at maximum point.