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- 저자 : Hongmao Qin (검색결과 2 건)
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Zhang Zhigang,Qin Hongmao,Sun Ning 보안공학연구지원센터 2016 International Journal of u- and e- Service, Scienc Vol.9 No.2
For rolling bearing fault, there is a certain mapping relationship between failure state and its each frequency band energy and distribution, this paper proposes a bearing fault diagnosis method based on wavelet packet decompotion energy distribution and gray similar correlation degree. Introducing a concept of soft morphological filtering, combined the EMD method on the original vibration signal de-noising pretreatment. Decomposing bearing vibration acceleration signal after noise reduction into different frequency band signal by adopting the method of wavelet packet decomposition and calculating the energy distribution. Due to the gray similar correlation degree analysis for the classification of the small sample pattern recognition has a good effect, element structure characteristic vector by energy distribution, to judge the fault types by calculating the bearing vibration signal under different status similar correlation degree. Experimental results show that, the proposed can be effectively applied to bearing fault diagnosis.
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COORDINATED COLLISION AVOIDANCE FOR CONNECTED VEHICLES USING RELATIVE KINETIC ENERGY DENSITY
Manjiang Hu,Jian Wu,Hongmao Qin,Yougang Bian,Biao Xu,Qing Xu,Jugang He,Jianqiang Wang 한국자동차공학회 2017 International journal of automotive technology Vol.18 No.5
Vehicular collision often leads to serious casualties and traffic congestion, and the consequences are worse for multiple-vehicle collision. Many previous works on collision avoidance have only focused on the case for two consecutive vehicles using on-board sensors, which ignored the influence on upstream traffic flow. This paper proposes a novel coordinated collision avoidance (CCA) strategy for connected vehicles, which has potential to avoid collision and smooth the braking behaviors of multiple vehicles, leading to an improvement of traffic smoothness. Specifically, model predictive control (MPC) framework is used to formulate the CCA into an optimization problem, where the objective is to minimize the total relative kinetic energy density (RKED) among connected vehicles. Monte Carlo simulations are used to demonstrate the effectiveness of proposed CCA strategy by comparison with other two strategies. Among all the three control strategies, the RKED based control strategy shows the best performance of collision avoidance, including the best crash prevention rates (99.2 % on dry asphalt road and 90.5 % on wet asphalt road) and the best control of distance headways between vehicles.
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