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“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.

The analysis of the periodic components in noise and vibration signals measured on rotating equipment, like car power trains, must more and more be done under rapid changes of an axle, or reference RPM. Normal tracking filters (analog, or digital implementations) have limited resolution in such situations; wavelet methods, even when applied after resampling the data to be proportional to an axle RPM, must compromise between time and frequency resolution. The authors propose the application of nonstationary Kalman filters for the tracking of periodic components in such noise and vibration signals. These filters are designed to track accurately signals with a known structure among noise and signal components of different, ‘unknown’, structure.

This paper presents a model updating method based on experimental receptances. The presented method minimises the so called ‘indirect receptance difference’. First, the reduced analytical dynamic stiffness matrix is expressed as an approximate, linearised function of the updating parameters. In a numerically stable, iterative procedure, this reduced analytical dynamic stiffness matrix is changed in such a way that the analytical receptances match the experimental receptances at the updating frequencies. The updating frequencies are a set of selected frequency points in the frequency range of interest. Some considerations about an optimal selection of the updating frequencies are given. Finally, a mixed static-dynamic reduction scheme is discussed. Dynamic reduction of the analytical dynamic stiffness matrix at each updating frequency is physically exact, but it involves a great computational effort.

Kalman filters have been employed very successfully in control and guidance systems since the sixties, with particular application to avionics and navigation. These filters can track accurately signals of known structure among noise and other signal components with different structure. This paper investigates the application of nonstationary Kalman filters to track harmonic components. This approach enables the analysis of harmonic components in signals even when the rate of change of frequency, or slew rate, is high. A Kalman filter formulation to track harmonic components in data records sampled with constant frequency is first reviewed. Particular attention is paid to the characteristics of the filters in terms of filter resolution and harmonic separation, as well as ability to handle higher slew rates. The applicability of the method is demonstrated for analyzing driveline harshness problem.