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How to decrease noise and vibration exposure has been of interest for many years. Empirical data have indicated that too high dose values can create multiple problems to a human body - often severe. Some years back, the European Machinery Directive has increased the responsibility for manufacturers and employers to make sure limits are complying with legislation. Classical technology often consists of passive solutions aiming at trying to cut back on noise and vibration levels. For low frequency, these methods are often lacking the needed performance especially if weight should be considered at the same time. A smart combination of passive and active techniques can make a real difference. Today, with possibilities for low cost and embedded electronics and the rapid development of new actuators, a vast range of applications are possible for this combined combat approach, with a financial advantage as well.

Chatter vibrations are causing large monetary losses daily in industry. New materials have increased the challenges with harmful vibration levels. Since the vibrations, when observed as a final result, are chaotic and the vibration process nonlinear, it is a challenging task to deal with it. It is also a common “understanding” in the cutting industry that chatter is RPM (the rotational speed) dependent, since the behavior changes with RPM. Many attempts have been done over many years to mitigate and understand the vibrations. In our vast research on these topics, we have found that it is rewarding to classify the vibrations into categories, enabling a better understanding of its underlying physics and “source of vibrations,” and thus also the formulation of a possible remedy. An analysis approach has been developed where vibrations are analyzed and categorized and a GO/NOGO indicator is telling if the machine has the “right type of vibrations.”

In aerospace applications it is often vital to understand what is happening when analyzing sound and vibration data and what total accuracy one receives. The tradition has been to spend money on yearly calibration of sensors and part of the measurement equipment, but not on the software used for analysis of the data collected by these sensors. While the sensors might be accurate to a percentage level, erroneous analysis procedures can give arbitrarily high errors! Usually, there is no “calibration option” or “benchmark” for sound and vibration analysis software. This paper will present some common pitfalls and what can happen if the user is not aware how the software is handling the data, or even worse, the code was not correctly implemented in the first place. Some real life examples of the latter and suggested solutions to avoid such harmful situations will be presented.

In workshops where metal cutting is performed, the machining processes frequently introduces productivity degrading vibration problems and annoying sound, sometimes almost at unbearable levels. Besides producing disturbing noise, the vibrations affect the surface finish of the workpiece and the tool life. Two different approaches based on feedback control are investigated, both applied for the control of an active boring bar. The first approach is based on a digital adaptive feedback controller; the feedback filtered-X LMS algorithm. The second approach is based on an analog controller; a feedback controller with gain and phase orthogonally adjustable, thus flexible for the control of systems with different dynamic properties. Based on open loop frequency response function estimates, robustness and stability of both the digital and the analog feedback control system are discussed.

Commercial tools for measurement and analysis of noise and vibration signals have traditionally been very expensive. In the last decade, however, multi-channel measurement systems have become relatively inexpensive. The analysis functionality in most inexpensive instruments is limited. Therefore, many companies are using alternatives for post processing of measurement results. Matlab is a platform that is popular for this purpose and which offers many advantages over dedicated, menu driven systems. The open functions in Matlab assure flexibility and the possibility to modify functions for specific needs. In addition, a command based programming environment provides for traceability and quality assurance, including qualification of used algorithms, important aspects particularly in the aerospace industry. In the past, basic functions for signal analysis and vibration analysis have had to be developed before taking full advantage of the Matlab platform.

In applications for acoustic profiling, an analysis of current versus depth is key. By analyzing the Doppler frequency variation in the backscattering signal, it is possible to calculate the mean current versus depth. However, due to turbulence in the water creating simultaneous currents and layers, the current direction could change rapidly, making the data non-stationary and difficult to analyze. The transmitted pulse is very short, and the volume where the current should be estimated is typically small. Also, the water volume can contain multiple Doppler responses due to turbulence and other phenomenon. W hen using this innovative non-linear filtering method, Multiple Peak Count Analysis, these effects can become visible, and the method shows superior performance as compared to classical methods. Classical 3-dimensional spectral plots of the data, does not use a-priori information.

In applications for acoustic profiling, an analysis of current versus depth is key. By analyzing the Doppler frequency variation in the backscattering signal, it is possible to calculate the mean current versus depth. However, due to turbulence in the water creating simultaneous currents and layers, the current direction could change rapidly, making the data non-stationary and difficult to analyze. The transmitted pulse is very short, and the volume where the current should be estimated is typically small. Also, the water volume can contain multiple Doppler responses due to turbulence and other phenomenon. When using this innovative non-linear filtering method, Multiple Peak Count Analysis, these effects can become visible, and the method shows superior performance as compared to classical methods. Classical 3-dimensional spectral plots of the data, does not use a-priori information.