Journals / SV / Vol.55, No.2

  • REVIEW

    Supervision of Milling Tool Inserts using Conventional and Artificial Intelligence Approach: A Review

    Nilesh Dhobale1, Sharad Mulik2, R. Jegadeeshwaran3,*, Abhishek Patange4
    Sound & Vibration, Vol.55, No.2, pp. 87-116, 2021, DOI:10.32604/sv.2021.014224
    Abstract Due to continuous cutting tool usage, tool supervision is essential for improving the metal cutting industry. In the metal removal process tool, supervision is carried out either by an operator or online tool supervision. Tool supervision helps to understand tool condition, dimensional accuracy, and surface superiority. For downtime in the metal cutting industry, the main reasons are tool breakage and excessive wear, so it is necessary to supervise tool which gives better tool life and enhance productivity. This paper presents different conventional and artificial intelligence techniques for tool supervision in the processing procedures that have been depicted in writing. More >

  • ARTICLE

    Improving the Morphological Parameters of Aluminum Foam for Maximum Sound Absorption Coefficient using Genetic Algorithm

    Mohammad Javad Jafari1, Mohsen Niknam Sharak2, Ali Khavanin3, Touraj Ebadzadeh4, Mahmood Fazlali5, Rohollah Fallah Madvari6,*
    Sound & Vibration, Vol.55, No.2, pp. 117-130, 2021, DOI:10.32604/sv.2021.09729
    Abstract Fabricating of metal foams with desired morphological parameters including pore size, porosity and pore opening is possible now using sintering technology. Thus, if it is possible to determine the morphology of metal foam to absorb sound at a given frequency, and then fabricate it through sintering, it is expected to have optimized metal foams for the best sound absorption. Theoretical sound absorption models such as Lu model describe the relationship between morphological parameters and the sound absorption coefficient. In this study, the Lu model was used to optimize the morphological parameters of Aluminum metal foam for the best sound absorption… More >

  • ARTICLE

    Experimental Modal Damping Identification of a Mechanical Structure Using Video Magnification Technique

    Jaafar Hallal1,*, Mahmoud Fakih2, Hala Damerji3, Mohammad Hammoud4,5, Mehdi Chouman4,5
    Sound & Vibration, Vol.55, No.2, pp. 131-140, 2021, DOI:10.32604/sv.2021.015293
    Abstract Vibration can be introduced in all mechanical fields in our life. Engineers try to avoid its negative effect leading in some cases to deformation in the machines. Many researches are dedicated to study the identification of damping especially in multi degree of freedom systems with particular attention to the source of energy dissipation. They focus on developing new tools or methods which may be used in real problems to obtain accurate results about the amount (or value) and the location of energy dissipation in the structure. The aim of this paper is to present an original procedure aims to experimentally… More >

  • ARTICLE

    Combined Signal Processing Based Techniques and Feed Forward Neural Networks for Pathological Voice Detection and Classification

    T. Jayasree1,*, S.Emerald Shia2
    Sound & Vibration, Vol.55, No.2, pp. 141-161, 2021, DOI:10.32604/sv.2021.011734
    Abstract This paper presents the pathological voice detection and classification techniques using signal processing based methodologies and Feed Forward Neural Networks (FFNN). The important pathological voices such as Autism Spectrum Disorder (ASD) and Down Syndrome (DS) are considered for analysis. These pathological voices are known to manifest in different ways in the speech of children and adults. Therefore, it is possible to discriminate ASD and DS children from normal ones using the acoustic features extracted from the speech of these subjects. The important attributes hidden in the pathological voices are extracted by applying different signal processing techniques. In this work, three… More >

  • ARTICLE

    Evaluation of Individual and Environmental Sound Pressure Level and Drawing Noise-Isosonic Maps using Surfer V.14 and Noise at Work V.5.0

    Sajad Zare1, Rasoul Hemmatjo2, Hossein ElahiShirvan3,*, Ashkan Jafari Malekabad3, Mansour Ziaei4, Farshad Nadri5
    Sound & Vibration, Vol.55, No.2, pp. 163-171, 2021, DOI:10.32604/sv.2021.09114
    Abstract Noise pollution is one of the common physical harmful factors in many work environments. The current study aimed to assess personal and environmental sound pressure level and project the sound-Isosonic map in one of the Razavi Khorasan Paste manufacture using Surfer V.14 and Noise at work V.5.0. This cross-sectional, descriptive study is analytical that was conducted in 2018 in the Paste factory that contains Canister, production and Brewing unit. Following ISO 9612:2009, Casella Cel-320 was used to measure personal sound pressure level, while CEL-450 sound level meter (manufactured by Casella-Cel, the UK) was employed to assess environmental sound pressure level.… More >

  • ARTICLE

    Ply-by-Ply Failure Analysis of Laminates Under Dynamic Loading

    Ravi Joshi*, P. Pal
    Sound & Vibration, Vol.55, No.2, pp. 173-190, 2021, DOI:10.32604/sv.2021.011387
    Abstract Ply-by-ply failure analysis of symmetric and anti-symmetric laminates under uniform sinusoidal transverse dynamic loading is performed for a specified duration. The study investigates the first ply failure load, followed by the detection of successive ply failures along with their failure modes using various failure theories. Some of the well-established failure theories, mostly used by the researchers, are considered for the failure prediction in laminates. The finite element computational model based on higher order shear deformation displacement field is used for the failure analysis and the complete methodology is computer coded using FORTRAN. The ply-discount stiffness reduction scheme is employed to… More >

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