Journals / SV / Vol.53, No.5


    Experimental and Numerical Study of the Key Non-Dimensional Geometrical Parameters on the Noise Level of Dry-Type Cast Resin Transformers

    Mahdi Soltanmohammadi1, Vahid Monfared2,*
    Sound & Vibration, Vol.53, No.5, pp. 177-198, 2019, DOI:10.32604/sv.2019.05811
    Abstract Dry-Type Cast Resin Distribution Transformers (CRT) is the secondgeneration of air-cooled distribution transformers where oil is replaced by resin for electrical insulation. CRT transformers may installed indoor adjacent to or near residential areas since they are clean and safe comparing to the conventional transformers. But, as it is obvious, noise discrepancy is intrinsically accompanied with all types of transformers and is inevitable for CRT transformers too. Minimization of noise level caused by such these transformers has biological and ergonomic importance. As it is known the core of transformers is the main source of the noise generation. In this paper, experimental… More >


    A Novel Method for Vibration Mitigation of Complex Mechanical Systems

    Cheng Hu*
    Sound & Vibration, Vol.53, No.5, pp. 199-206, 2019, DOI:10.32604/sv.2019.07712
    Abstract Taking the complex mechanical systems as the research project, a theoretical multi-degree-of-freedom (MDOF) model was established. Based on the vibration characteristics analysis of this system, a novel method of vibration mitigation was proposed, which can be applied to most of the complex mechanical systems. Through this method, limited grounding stiffness was made use of and added to certain degree of freedom (DOF) discretely. Thus, the root-meansquare (RMS) of the systems amplitude can be reduced to ideal level. The MATLAB code based on this method was attached, which was tested on the theoretical model. Consider that complex mechanical systems are nonlinear… More >


    Improving the Sound Absorption Properties of Flexible Polyurethane (PU) Foam using Nanofibers and Nanoparticles

    Roohalah Hajizadeh1, Ali Khavanin2,*, Mohammad Barmar3, Ahmad Jonidi Jafari4, Somayeh Farhang Dehghan5
    Sound & Vibration, Vol.53, No.5, pp. 207-222, 2019, DOI:10.32604/sv.2019.06523
    Abstract Polyurethane foam as the most well-known absorbent materials has a suitable absorption coefficient only within a limited frequency range. The aim of this study was to improve the sound absorption coefficient of flexible polyurethane (PU) foam within the range of various frequencies using clay nanoparticles, polyacrylonitrile nanofibers, and polyvinylidene fluoride nanofibers. The response surface method was used to determine the effect of addition of nanofi- bers of PAN and PVDF, addition of clay nanoparticles, absorbent thickness, and air gap on the sound absorption coefficient of flexible polyurethane foam (PU) across different frequency ranges. The absorption coefficient of the samples was… More >


    Integrated Condition Monitoring of Large Captive Power Plants and Aluminum Smelters

    J.K. Mohanty1, A. Adarsh2, P.R. Dash1, K. Parida1, P.K. Pradhan1,*
    Sound & Vibration, Vol.53, No.5, pp. 223-235, 2019, DOI:10.32604/sv.2019.07737
    Abstract Condition monitoring is implementation of the advanced diagnostic techniques to reduce downtime and to increase the efficiency and reliability. The research is for determining the usage of advanced techniques like Vibration analysis, Oil analysis and Thermography to diagnose ensuing problems of the Plant and Machinery at an early stage and plan to take corrective and preventive actions to eliminate the forthcoming breakdown and enhancing the reliability of the system. Nowadays, the most of the industries have adopted the condition monitoring techniques as a part of support system to the basic maintenance strategies. Major condition monitoring technique they follow is Vibration… More >


    Extrapolation for Aeroengine Gas Path Faults with SVM Bases on Genetic Algorithm

    Yixiong Yu*
    Sound & Vibration, Vol.53, No.5, pp. 237-243, 2019, DOI:10.32604/sv.2019.07887
    Abstract Mining aeroengine operational data and developing fault diagnosis models for aeroengines are to avoid running aeroengines under undesired conditions. Because of the complexity of working environment and faults of aeroengines, it is unavoidable that the monitored parameters vary widely and possess larger noise levels. This paper reports the extrapolation of a diagnosis model for 20 gas path faults of a double-spool turbofan civil aeroengine. By applying support vector machine (SVM) algorithm together with genetic algorithm (GA), the fault diagnosis model is obtained from the training set that was based on the deviations of the monitored parameters superimposed with the noise… More >

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