Home / Journals / SV / Vol.54, No.4, 2020
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  • Open AccessOpen Access

    ARTICLE

    An Exact Solution for Acoustic Simulation Based Transmission Loss Optimization of Double-Chamber Silencer

    Wael A. Altabey1,2,*
    Sound & Vibration, Vol.54, No.4, pp. 215-224, 2020, DOI:10.32604/sv.2020.011516 - 25 November 2020
    Abstract The optimization of the acoustic silencer volume is very important to develop it and to get high-performance, the importance of the silencer was appeared in industrial field to eliminate the noise of the duct by efficient and economical method. The main goal of this research is to optimize the transmission loss (TL) by analytical method of the Double-Chamber Silencer (DCS), the TL has been selected as the main parameter in silencer because it does not based on the source or the termination impedances. First we calculated the power transmission coefficient (PTC) and the TL of More >

  • Open AccessOpen Access

    ARTICLE

    Cost Optimized Non-Contacting Experimental Modal Analysis Using a Smartphone

    Jaafar Hallal1,2,3,*, Mohammad Hammoud2,3, Mahmoud Fakih2,3,4, Ali Hallal2,3
    Sound & Vibration, Vol.54, No.4, pp. 225-236, 2020, DOI:10.32604/sv.2020.011513 - 25 November 2020
    Abstract The vibrations behavior analysis is an essential step in the mechanical design process. Several methods such as analytical modelling, numerical analysis and experimental measurements can be used for this purpose. However, the numerical or analytical models should be validated through experimental measurements, usually expensive. This paper introduces an inexpensive smartphone as an accurate, non-intrusive vibrations’ behavior measurement device. An experimental measurement procedure based on the video processing method is presented. This procedure allows the measurement of the natural frequencies and the mode shapes of a vibrating structure, simply by using a smartphone built-in camera. The… More >

  • Open AccessOpen Access

    ARTICLE

    Frequencies Rotation at High Sound Pressure Levels Toward Low Frequencies

    Hadi Negahdari1, Sirus Javadpour2,*, Faramarz Moattar3
    Sound & Vibration, Vol.54, No.4, pp. 237-246, 2020, DOI:10.32604/sv.2020.011086 - 25 November 2020
    Abstract Today, analyzing of sound pressure level and frequency is considered as an important index in human society. Sound experts believe that analyzing of these parameters can help us to better understanding of work environments. Sound measurements and frequency analysis did to fix the harmful frequency in all sections in Shiraz gas power plant with sound analyzer model BSWA 308. The sound pressure levels (LP) and the one and one-third octave band were continuously measured in A and C weighting networks and slow mode for time response. Excel 2013 and Minitab 18.1 software used for statistical calculations.… More >

  • Open AccessOpen Access

    ARTICLE

    Noise Control of a Domestic Refrigerator Using a Natural Material Based Composite

    A. R. Mohanty1,*, S. Fatima2
    Sound & Vibration, Vol.54, No.4, pp. 247-256, 2020, DOI:10.32604/sv.2020.011011 - 25 November 2020
    Abstract This paper studies the acoustics of a frost free three door domestic refrigerator. Then, as a case study, the radiated noise reduction in the refrigerator using a natural material base composite is presented. Composites manufactured out of Jute, which is a plant fiber abundantly and cheaply available in India and Bangladesh are used in the noise reduction in the refrigerator. Mostly in this work, composites made out of felts of jute were used as barriers for noise control of the refrigerator. Measured acoustical, thermal and physical properties of various jute composites are reported. Noise sources More >

  • Open AccessOpen Access

    ARTICLE

    Condition Monitoring of an Industrial Oil Pump Using a Learning Based Technique

    Amin Ranjbar1, Amir Abolzafl Suratgar1,*, Saeed Shiry Ghidary2, Jafar Milimonfared3
    Sound & Vibration, Vol.54, No.4, pp. 257-267, 2020, DOI:10.32604/sv.2020.05055 - 25 November 2020
    Abstract This paper proposes an efficient learning based approach to detect the faults of an industrial oil pump. The proposed method uses the wavelet transform and genetic algorithm (GA) ensemble for an optimal feature extraction procedure. Optimal features, which are dominated through this method, can remarkably represent the mechanical faults in the damaged machine. For the aim of condition monitoring, we considered five common types of malfunctions such as casing distortion, cavitation, looseness, misalignment, and unbalanced mass that occur during the machine operation. The proposed technique can determine optimal wavelet parameters and suitable statistical functions to More >

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