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One of the key elements in efforts to minimize the noise emmissionis of engines and other machinery is the knowledge of the main noise radiating surfaces and the relation between measurable surface vibration and the sound pressure. Under the name of Airborne Source Quantification (ASQ), various techniques have been developed to discretize and quantify the source strength, and noise contributions, of vibrating surface patches of machinery or vehicle components. The noise contributions of patches to the sound pressure at specific locations in the sound field or to the total radiated sound power are identified. The source strength of equivalent point sources, the acoustic transfer from the source surface to critical sound field locations and finally the sound pressure contributions of the individual patches are quantified. These techniques are not unique to engine application, but very relevant for engine development. An example is shown for an engine under artificial excitation.

The vibration-generating mechanisms inside an engine are highly non-linear (combustion, valve operation, hydraulic bearing behavior, etc.). However, the engine structure, under the influence of these vibration-generating mechanisms, responds in a highly linear way. For the development and optimization of the engine structure for noise and vibration it is beneficial to use fast and ‘simple’ linear models, like linear FE-models, measured modal models or measured FRF-models. All these models allow a qualitative assessment of variants without excitation information. But, for true optimization, internal excitation spectra are needed in order to avoid that effort is spent to optimize non-critical system properties. Unfortunately, these internal excitation spectra are difficult to measure. Direct measurement of combustion pressure is still feasible, but crank-bearing forces, piston guidance forces etc. can only be identified indirectly.