Archives of Acoustics 

About: Archives of Acoustics is an academic journal published by De Gruyter. The journal publishes majorly in the area(s): Noise & Acoustic wave. It has an ISSN identifier of 0137-5075. Over the lifetime, 1609 publications have been published receiving 8052 citations.

Improving Sound Absorption Property of Polyurethane Foams by Adding Tea-Leaf Fibers

Abstract: The sound absorption property of polyurethane (PU) foams loaded with natural tea-leaf fibers and luffa cylindrica (LC) has been studied. The results show a significant improvement in the sound absorption property parallel to an increase in the amount of tea-leaf fibers (TLF). Using luffa-cylindrica as a filler material improves sound absorption properties of soft foam at all frequency ranges. Moreover, an increase in the thickness of the sample resulted in an improvement of the sound absorption property. It is pleasing to see that adding tea-leaf fibers and luffa-cylindrica to the polyurethane foam demonstrate a significant contribution to sound absorption properties of the material and it encourages using environmental friendly products as sound absorption material in further studies.

Synthetic Transmit Aperture in Ultrasound Imaging

Abstract: The paper describes the use of synthetic transmit aperture (STA) imaging in medical ultrasound. The synthetic aperture (SA) imaging is a novel approach to today's commercial systems. In these systems the image is acquired sequentially one image line at a time that puts a strict limit on the frame rate and the possibility of acquiring a sufficient amount of data for high image quality. This limitation can be lifted by employing SA imaging where the data are acquired simultaneously from all directions over a number of emissions, and the full image can be reconstructed from those data. Due to the complete data set, it is possible to have full transmitting and receiving focusing at the entire image region to improve the contrast dynamic and spatial resolution. The paper describes the STA imaging with a single element transmitting and all elements receiving apertures. In experiments, 32-element linear transducer array with 0.48 mm inter-element spacing and a burst pulse of 100ns duration were used. The single element transmission aperture was used to generate a spherical wave covering the full image region. The 2D ultrasound images of wire phantom are presented to demonstrate the benefits of SA imaging.

Fault Detection Enhancement in Rolling Element Bearings Using the Minimum Entropy Deconvolution

Abstract: Minimum Entropy Deconvolution (MED) has been recently introduced to the machine condition mon- itoring field to enhance fault detection in rolling element bearings and gears. MED proved to be an excellent aid to the extraction of these impulses and diagnosing their origin, i.e. the defective component of the bearing. In this paper, MED is revisited and re-introduced with further insights into its application to fault detection and diagnosis in rolling element bearings. The MED parameter selection as well as its combination with pre-whitening is discussed. Two main cases are presented to illustrate the benefits of the MED technique. The first one was taken from a fan bladed test rig. The second case was taken from a wind turbine with an inner race fault. The usage of the MED technique has shown a strong enhancement for both fault detection and diagnosis. The paper contributes to the knowledge of fault detection of rolling element bearings through providing an insight into the usage of MED in rolling element bearings diag- nostic. This provides a guide for the user to select optimum parameters for the MED filter and illustrates these on new interesting cases both from a lab environment and an actual case.

n-gram-based approach to composer recognition

Abstract: This paper describes how tools provided by Natural Language Processing and Information Retrieval can be applied to music. A method of converting complex musical structure to features (n-grams) corresponding with words of text was introduced. Mutual correspondence between both representations was shown by demonstrating certain important regularities known from text processing, which may also be found in music. The problem of automatic composer attribution to which statistical analysis of n-gram profiles known from statistical NLP was applied served as a case study. A MIDI files corpus of piano pieces was chosen as the source of data.

Diagnostics of Synchronous Motor Based on Analysis of Acoustic Signals with the use of Line Spectral Frequencies and K-nearest Neighbor Classifier

Abstract: In industrial processes electrical motors are serviced after a specific number of hours, even if there is a need for service. This led to the development of early fault diagnostic methods. Paper presents early fault diagnostic method of synchronous motor. This method uses acoustic signals generated by synchronous motor. Plan of study of acoustic signal of synchronous motor was proposed. Two conditions of synchronous motor were analyzed. Studies were carried out for methods of data processing: Line Spectral Frequencies and K-Nearest Neighbor classifier with Minkowski distance. Condition monitoring is useful to protect electric motors and mining equipment. In the future, these studies can be used in other electrical devices.