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RISS 인기검색어
- 검색키워드
- 저자 : Jingan Wang (검색결과 3 건)
- 무료
- 기관 내 무료
- 유료
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Objective Evaluation of Fabric Wrinkles Based on 2-D Gabor Transform
Kangjun Shi,Jingan Wang,Lei Wang,Ruru Pan,Weidong Gao 한국섬유공학회 2020 Fibers and polymers Vol.21 No.9
In order to establish an objective, stable and efficient wrinkle evaluation system for fabric wrinkle evaluation, amethod based on 2-D Gabor transform was proposed. Among this system, the directions of Gabor filter were determinedaccording to the range of amplitude response. Then a set of Gabor filters were obtained by selecting and optimizing thecentral frequency, the half peak bandwidth and the shape factor of the Gaussian surface. After Gabor transform by such filterbank, the amplitudes of different response spectrums were extracted, constructing a multi-dimensional feature vector. Finally,the feature vectors of the fabric image samples, whose wrinkle degrees were evaluated manually in advance, were extractedand used to train a support vector machine (SVM), which achieved 81.82 % evaluation accuracy on the 345 samples. Thetrained SVM was applied to evaluate the wrinkle degree of the fabric samples acquired in different illumination directions,and verified the stability of the proposed method to illumination environment. Compared with the existing method, theproposed method has higher classification accuracy. The comparison results indicate the Gabor amplitude feature proposedby this research has a high correlation with the fabric wrinkle grades.
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MAXIMUM CORRENTROPY EXTENDED KALMAN FILTER FOR VEHICLE STATE OBSERVATION
Qi Dengliang,Feng Jingan,Ni Xiangdong,Wang Lei 한국자동차공학회 2023 International journal of automotive technology Vol.24 No.2
For vehicle state estimation, the conventional Kalman filter performs well under the Gaussian assumption, but in the real non-Gaussian situation (especially when the noise is non-Gaussian heavy-tailed), it shows poor accuracy and robustness. In this paper, an extended Kalman filter (EKF) algorithm based on the maximum correntropy criterion (MCC) is proposed (MCCEKF), and a lateral-longitudinal coupled vehicle model is established, while a state observer containing the yaw rate, vehicle sideslip angle, and longitudinal vehicle speed is designed using the easily available measurement information of on-board sensors. After analyzing the complexity of the proposed algorithm, the new algorithm is verified on the Simulink/CarSim simulation experimental platform by Double Lane Change and Sine Sweep Steer Torque Input maneuver. Experimental results show that the MCC-based EKF algorithm has stronger robustness and better estimation accuracy than the traditional EKF algorithm in the case of non-Gaussian noise, and the MCCEKF is more applicable for vehicle state estimation in practical situations.
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Design of vortex finder structure for decreasing the pressure drop of a cyclone separator
Yaquan Sun,Junzhi Yu,Weibing Wang,Shanglin Yang,Xue Hu,Jingan Feng 한국화학공학회 2020 Korean Journal of Chemical Engineering Vol.37 No.5
The structure of the vortex finder has an important influence on the pressure drop and separation efficiency of a cyclone, which mainly governs the separation process. In this paper, the traditional vortex finder is slotted on side wall and its bottom is closed, i.e., a slotted vortex finder. The impact of slotted vortex finder on the separation performance of a cyclone is explored by using numerical simulation and experimental validation. Specifically, the gas phase is studied by the Reynolds stress model (RSM), and the particle phase is simulated by the discrete phase model (DPM). The simulation results are in good agreement with the experimental results, revealing higher prediction accuracy. The results indicate that the slotted vortex finder can effectively suppress the generation of the downward swirling flow at the center of the vortex finder and decrease the turbulence intensity at the bottom of the vortex finder and the outer vortex, thereby decreasing the energy loss and increasing the separation efficiency. When the slot length is 0.2De, the slotted vortex finder can reduce the pressure drop by 143.33 Pa while increasing the collection efficiency by 5.51%.
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