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RISS 인기검색어
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- 저자 : Qibin Wang (검색결과 5 건)
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Effects of different coupling models of a helical gear system on vibration characteristics
Qibin Wang,Zhanwei Li,Hui Ma,Bang-chun Wen 대한기계학회 2017 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.31 No.5
Time-varying mesh stiffness (TVMS) and the dynamic coupling between the helical gears have a great influence on the vibration characteristics of a helical gear rotor system. Considering the effects of TVMS and adopting two coupling models (lateral-torsional coupling model and lateral-torsional-axial-swing coupling model), the dynamic behavior of a helical gear system was studied. First, an analytical model was used to analyze TVMS of a helical gear pair where the helical tooth is simulated by many spur tooth slices along the direction of the tooth width and the mesh stiffness of each slice is calculated using the energy method. Then, considering the effects of the TVMS excitation, the finite element model of a helical gear rotor system was established. Gear mesh was simulated by the above-mentioned two coupling models to investigate the effects of coupling forms on the system vibration characteristics. The strain energy was used to distinguish the dominant mode and dominant shaft of a gear system in natural characteristics analysis. The results show that the full coupling model can analyze accurately the vibration characteristics of the system and the axial and swing motions cannot be ignored in vibration analysis. Finally, the effects of helix angle on TVMS and vibration responses of a helical gear system were also studied.
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Qibin Wang,Bo Zhao,Hongbo Ma,Jiantao Chang,Gang Mao 대한기계학회 2019 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.33 No.6
Real-time monitoring and rapid evaluation of bearing operating conditions, especially for the reliability evaluation and remaining useful life (RUL) prediction, are major challenges in the rotating machinery field. A two-dimensional (2-D) deep convolution neural network (CNN) is proposed for rapidly evaluating reliability and predicting RUL, in which a signal conversion method is proposed for converting the one-dimensional signal into the 2-D image to satisfy the input requirements of the 2-D CNN. Different activation functions are employed to implement the conversion of the input data to the output data for each layer of the network, and dropout is only adopted in the hidden layer to change the network structure to prevent overfitting. The maximum correlation entropy with regular terms is employed as the loss function of the model to obtain better training performance compared with the mean square error (MSE). Then, the rolling bearing degradation vibration data is applied to the proposed model to verify the accuracy and rapidity. The results show that the proposed method has good accuracy and fast calculation ability in bearing reliability evaluation and RUL prediction, especially, its time consumption is shorter than that by other deep learning networks.
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Dynamic analysis of three-dimensional helical geared rotor system with geometric eccentricity
Yimin Zhang,Qibin Wang,Hui Ma,Jing Huang,Chunyu Zhao 대한기계학회 2013 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.27 No.11
A dynamic model of a multi-shaft helical geared rotor system is presented. Rotating shafts of the system are modeled as Timoshenko beams. A general three-dimensional dynamic model of helical gear pairs with geometric eccentricity is developed for the gear mesh and bearing flexibility is included in the model as well. The transmission error and gear geometric eccentricity are simulated as excitations. Eigenvalue solution and the modal summation technique are used to predict the natural frequencies and forced responses of the system. Then two geared rotor system models are presented for validation of the gear dynamic model. It is demonstrated that the gear mesh model is effective for general geared rotor systems, spur and helical gears, one-stage and multi-stage systems. Finally, forced responses of an example system are analyzed to demonstrate the influences of the helical gear geometric eccentricity and the coupling between gear geometric eccentricity and rotor mass unbalance.
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Cao Tong,Zhili Sun,Qianli Zhao,Qibin Wang,Shuang Wang 대한기계학회 2015 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.29 No.8
To solve the problem of large computation when failure probability with time-consuming numerical model is calculated, we proposean improved active learning reliability method called AK-SSIS based on AK-IS algorithm [1]. First, an improved iterative stopping criterionin active learning is presented so that iterations decrease dramatically. Second, the proposed method introduces Subset simulationimportance sampling (SSIS) into the active learning reliability calculation, and then a learning function suitable for SSIS is proposed. Finally, the efficiency of AK-SSIS is proved by two academic examples from the literature. The results show that AK-SSIS requiresfewer calls to the performance function than AK-IS, and the failure probability obtained from AK-SSIS is very robust and accurate. Thenthis method is applied on a spur gear pair for tooth contact fatigue reliability analysis.
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The Development and Application of a External Coating for Buried Pipeline Rehabilitation
Zhang, Liping,Lin, Zhu,Zhang, Qibin,Qin, Yanlong,Wang, Xueying 한국부식방식학회 2003 Corrosion Science and Technology Vol.2 No.3
With the development of Chinese petroleum and gas industry, about 20,000 km long-distance pipeline and 250,000 km gathering pipeline have been constructed in China. After operating for many years, most of the coatings on buried pipelines have aged so severe that the steel pipes are subject to corrosion environment underground. Focusing on the need of extemal coating for buried pipeline rehabilitation, a new type of coating has been developed. The development and application of the coatings has been introduced in this paper.
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