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      저자 : Qianwen Xia (검색결과 2 건)
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        Friction-induced vibration of marine propeller shaft based on the LuGre friction model

        Qianwen Huang,Jing Xia,Huaiguang Liu 대한기계학회 2023 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.37 No.8

        The friction-induced vibration with stick-slip behavior is caused by the contact of the shaft-bearing system. A LuGre friction model is thus applied in the investigation of frictioninduced vibration of the marine propeller shaft. The model parameters contain Coulomb friction, stiction force, Stribeck velocity and viscous coefficient are obtained through fitting curves of friction with experimental data in published papers. The dynamical response of a marine propulsion system is measured with an experiment and calculated with the Stribeck model to verify the adaptation of the LuGre friction model in the friction-induced vibration. To capture the nature of the LuGre friction model, the velocity-dependent function, friction coefficient, pre-sliding displacement, hysteresis, break-away force and dynamical response are numerically calculated. The impact factors include relative velocity, tangential force, and rotational speed are discussed with specific comparison. Therefore a suitable model focusing on the friction-induced vibration is proposed for the marine propeller shaft.

      • KCI등재

        Quantitative Detection of Corroded Reinforced Concrete of Different Sizes Based on SMFL

        Mao Yang,Jianting Zhou,Qingyuan Zhao,Qianwen Xia,Hong Zhang,Lifeng Wang 대한토목학회 2022 KSCE JOURNAL OF CIVIL ENGINEERING Vol.26 No.1

        In order to solve the problem of quantitative detection of corroded reinforced concrete of different sizes, the quantitative detection experiment based on spontaneous magnetic flux leakage (SMFL) was carried out in batches. Electrochemical corrosion of 27 reinforced concrete specimens was carried out, and the SMFL signals of reinforcement were obtained by magnetic detection equipment. Four-dimensional magnetic indicators M1-M4 that can characterize the corrosion degree of the specimens were defined. The influence of different sizes on the magnetic indicators were analyzed. It is concluded that the thicknesses of the concrete covers affect the magnetic indicators by affecting the lift-off heights z. The influence of diameter of the rebars on the quantitative detection can be eliminated by describing the corrosion degree with the average cross-section loss rate α. The influence of length of the rebars on quantitative detection is not clear yet. Finally, Support Vector Machine (SVM) was introduced to establish a classification model of corrosion classes and magnetic indicators. Using the model to predict the corrosion classes of the specimens can achieve a high classification accuracy. The research provides a new method for the quantitative detection of steel corrosion.

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