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Source identification applied to a truck engine and using inverse numerical acoustics is presented. The approach is based on acoustic transfer vectors (ATV) and truncated singular value decomposition (SVD). Acoustic transfer vectors are arrays of transfer functions between surface normal velocity and acoustic pressure at response points. They can be computed using boundary element methods (indirect, direct or multi-domain direct formulations) or finite element methods (in physical or modal coordinates). Regularization techniques such as the so-called L-curve approach are used to identify the optimum SVD truncation. To increase the reliability of the source identification, the approach can use velocity measurements on the boundary surface as well as the standard nearfield pressure measurements. It also allows for linear or spline interpolation of the acoustic transfer vectors in the frequency domain, to increase computational speed.

“Noise and vibration are not invented here!”. Undesirable structural dynamic behaviour is normally experienced on final assemblies, by which time the underlying cause of the problem is difficult to solve intuitively. Solving the problems classically involves the partial breakdown of assemblies and the application of various structural dynamics testing and analysis procedures. Preferably, noise and vibration problems should be avoided by designing the product right the first time, by the use of various integrated analysis and testing disciplines, from the component level to the final assembly. Such an approach is referred to, in a broader sense, by trendy themes as concurrent engineering, forward engineering, simultaneous engineering.... This paper analyzes trends in analytical and experimental structural dynamics toward better integration of the various discipline oriented techniques that are currently used.