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Noise problems are often system issues rather than component issues. Component manufacturers have been putting continued efforts into constantly improving the quality of their products. There are numerous tests and standards to assess the vibro-acoustic performance of individual components. But once all components are put together, the system response might be entirely different from those of individual components. Typical system level testing has primarily been used to identify bad assembled products from good ones. These tests are usually done as part of a quality control process and slow down production. Such tests usually provide little information about the root causes of noise and vibration problems and no insight into improving engineering designs for noise abatement. This paper presents a new way of conducting system level noise diagnoses by using the Helmholtz Equation Least Squares (HELS) based Nearfield Acoustical Holography (NAH) technology [1].

This paper presents an experimental study on using the Helmholtz equation least squares (HELS) based nearfield acoustic holography (NAH) method for reconstructing the vibro-acoustic responses on the surfaces of arbitrarily-shaped structures. Specifically, we demonstrate the capability of HELS to reconstruct normal surface velocity (NSV) and perform panel contribution analysis. The test object is a hexagonal-shaped structure made of eight panels and frames that mimic a scaled automotive passenger compartment. The test was conducted inside a fully anechoic chamber with the structure excited by a point force using random input signals. The radiated acoustic pressures were measured via a linear array of microphones at a very close distance to the structural surfaces, and taken as the input to the HELS codes to reconstruct NSV and surface acoustic pressures (SAP).

A model based approach is developed to track and trace multiple incoherent sound sources in 3D space in real time. This technology is capable of handling continuous, random, transient, impulsive, narrowband and broadband sounds over a wide frequency range (20 to 20,000 Hz). The premise of this technology is that the sound field is generated by point sources located in a free field. To locate these sound sources, iterative triangulations are used based on the signals measured by a microphone array. These signals are preprocessed through de-noising techniques to enhance signal to noise ratios (SNR). Unlike the conventional beamforming, the present technology enables one to pinpoint the exact locations of multiple incoherent sound sources simultaneously by using the Cartesian coordinates, including sources behind measurement microphones. In other words, the microphone array need not face a test object, which is required in the beamforming.

A semi-empirical formula [1] for predicting noise spectra of an engine cooling fan assembly is developed. In deriving this formulation it is assumed that sound radiation from an axial flow fan is primarily due to fluctuating forces exerted on the fan blade surface. These fluctuating forces are correlated to the total lift force exerted on the fan blade, and is approximated by pressure pulses that decay both in space and time. The radiated acoustic pressure is then expressed in terms of superposition of contributions from these pressure pulses, and the corresponding line spectrum is obtained by taking a Fourier series expansion. To simulate the broad band sounds, a normal distribution-like shape function is designed which divides the frequency into consecutive bands centered at the blade passage frequency and its harmonics. The amplitude of this shape function at the center frequency is unity but decays exponentially. The decay rate decreases with an increase in the number of bands.

This paper presents a computer model for simulating dynamic responses inside an injector of an automotive fuel rail system. The injector contains a filter at the top, a coil spring in the middle, and a needle and orifices at the bottom. The equations of motion for unsteady one-dimensional flow are derived for the fluid flowing through the injector. The needle motion is described by a second order ordinary differential equation. The forces exerted on the needle include the magnetic force that controls the opening and closing of the injector and the coil spring force. To account for the loss of kinetic energy, we define two loss factors Ka and Kb. The former describes the loss of kinetic energy as fluid enters the injector through the filter at the top, and the latter depicts that as fluid is ejected into a large chamber through the passage between the needle and the needle seat and across four orifices at the bottom of the injector.

An extensive experimental study of noise generating mechanisms of two production models of automotive alternators is presented. It was established that aerodynamic noise (generated by cooling fans) is dominating at high speeds (above 3,000 rpm), while electromagnetic noise is the most intensive at low rpm. Two directions of noise reduction are proposed and validated: reduction of noise levels generated by alternators to be achieved by using axial flow fans for cooling instead of presently used bladed discs, and radical reduction of operating speed of alternators by using variable transmission ratio accessory drives.

A computer model is developed for predicting pressure fluctuations inside an automotive electronic fuel rail system, which consists of six injectors connected in series through pipelines and a pressure regulator. The pressure fluctuations are mainly caused by opening and closing of injectors fired in a particular order. The needles that control the opening and closing of the injectors are modeled by mass- spring-dashpot systems, whose equations of motion are governed by a second order ordinary differential equations. A similar second order ordinary differential equation is used to describe the motion of the membrane with nonlinear stiffness inside the pressure regulator. The responses of injectors and pressure regulator are coupled by unsteady one-dimensional flow through the pipelines. The pressure fluctuations are also required to satisfy a one-dimensional damped wave equation. To validate this computer model, pressure fluctuations inside injectors and pipelines are calculated.