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RISS 인기검색어
- 검색키워드
- 저자 : Qianzhi Pang (검색결과 3 건)
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Hua Huang,Wenhu Xue,Qianzhi Pang 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.7
Compound fault characteristics in single-channel vibration signals of rolling bearings are difficult to separate. On the basis of improved harmonic wavelet packet decomposition and fast independent component analysis (FICA), this study proposes a new method to address this problem. First, a series of mutually independent frequency bands are obtained after harmonic wavelet packet decomposition of the initial vibration signal to satisfy the requirement that the number of observed signals must be larger than the number of source signals in the FICA algorithm. Second, the optimal frequency bands are selected based on the maximum kurtosis index and used as the input matrix of the FICA algorithm to separate the compound fault characteristics further. Lastly, accurate separation and extraction of the compound fault characteristics of the rolling bearings are realized. Results show that the proposed method can effectively separate the compound fault characteristics in the single-channel vibration signals of the bearings.
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Analysis and prediction of wind turbine bolts based on GPR method
Hua Huang,Yonghe Wang,Qianzhi Pang 대한기계학회 2023 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.37 No.3
With the variance of preload and vibration in working conditions, wind turbine bolt loosening is difficult to predict accurately. To address the problem, wind turbine bolts are employed as the study object, and the loosening mechanism of bolts as well as the prediction of preload variation are investigated by means of finite element analysis. The result shows that, under the action of transverse vibration load, the magnitude of vibration load is the main factor affecting the loosening, and the larger the load magnitude, the more likely the loosening occurs. Besides, a bolt loosening prediction model based on Gaussian process regression is developed to obtain confidence intervals for the variation of the preload in a probabilistic sense. This study provides a theoretical basis for solving the problem of bolt loosening and preload relaxation in wind power under vibration conditions, and improves the safety and reliability of wind turbine operation.
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Hua Huang,Huiyang Huang,Runlan Guo,Qianzhi Pang 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.11
The self-healing of resin mineral composites by adding microcapsules has been widely used. However, it is difficult to determine the proportion of microcapsule to obtain the optimal self-healing performance because of the contradictory characteristics between the selfhealing efficiency and elastic modulus of composites. To address this problem, this study proposes a novel method to optimize the proportion of microcapsule under the constraints of engineering design requirements. The results show that (1) the damage evolution of self-healing resin mineral composites with microcapsule can be divided into four processes: damage accumulation, bond interface crack appearing, matrix crack appearing and fracture surface formation. (2) The position of aggregate has little effect on the mechanical properties of the overall composites structure, but it plays a decisive role in the distribution and size of cracks. (3) The relationship between the self-healing efficiency and the proportion of microcapsule is a nonlinear positive correlation, but the elastic modulus is a nonlinear negative correlation with the proportion of microcapsule. (4) The optimization results show that the optimal microcapsule proportion of a resin mineral composite machine tool is 1.68 %; at this time the mechanical properties of the material are reduced by 2.9 % and the self-healing efficiency is 25.38 %. The results provide a reference for the damage performance research and engineering design of microcapsule self-healing composites.
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