Alumina （Al2O3） particles reinforced copper matrix surface composites were fabricated on the bronze substrate using the vacuum infiltration casting technique. Three cases were obtained in the vacuum infiltration cas...Alumina （Al2O3） particles reinforced copper matrix surface composites were fabricated on the bronze substrate using the vacuum infiltration casting technique. Three cases were obtained in the vacuum infiltration casting technique： no infiltration, partial infiltration and full infiltration （the thickness of preforms do not exceed 3.5mm）. The reason of no infiltration is that the vacuum degree is not enough so that the force acting on the liquid metal is lower than the resistance due to the surface tension. Partial infiltration is because of somewhat lower vacuum degree and pouring temperature. Full desired infiltration is on account of suitable infiltration casting conditions, such as vacuum degree, pouring temperature, grain size and preheating temperature of the preform. The most important factor of affecting formation of surface composites is the vacuum degree, then pouring temperature and particle size. The infiltration mechanism was discussed on the bases of different processing conditions. The surface composite up to 3.5 mm in thickness with uniformly distributed Al2O3 particles could be fabricated via the vacuum infiltration casting technique.展开更多
The performance of existing maneuvering target tracking methods for highly maneuvering targets in cluttered environments is unsatisfactory.This paper proposes a hybrid-driven approach for tracking multiple highly mane...The performance of existing maneuvering target tracking methods for highly maneuvering targets in cluttered environments is unsatisfactory.This paper proposes a hybrid-driven approach for tracking multiple highly maneuvering targets,leveraging the advantages of both data-driven and model-based algorithms.The time-varying constant velocity model is integrated into the Gaussian process(GP)of online learning to improve the performance of GP prediction.This integration is further combined with a generalized probabilistic data association algorithm to realize multi-target tracking.Through the simulations,it has been demonstrated that the hybrid-driven approach exhibits significant performance improvements in comparison with widely used algorithms such as the interactive multi-model method and the data-driven GP motion tracker.展开更多
A novel algorithm that combines the generalized labeled multi-Bernoulli(GLMB) filter with signal features of the unknown emitter is proposed in this paper. In complex electromagnetic environments, emitter features(EFs...A novel algorithm that combines the generalized labeled multi-Bernoulli(GLMB) filter with signal features of the unknown emitter is proposed in this paper. In complex electromagnetic environments, emitter features(EFs) are often unknown and time-varying. Aiming at the unknown feature problem, we propose a method for identifying EFs based on dynamic clustering of data fields. Because EFs are time-varying and the probability distribution is unknown, an improved fuzzy C-means algorithm is proposed to calculate the correlation coefficients between the target and measurements, to approximate the EF likelihood function. On this basis, the EF likelihood function is integrated into the recursive GLMB filter process to obtain the new prediction and update equations.Simulation results show that the proposed method can improve the tracking performance of multiple targets,especially in heavy clutter environments.展开更多
基金This work was financially supported by the National Natural Science Foundation of Gansu Province (No.ZS021-A25-024-C), theChun-Hui Plan of the Ministry of Education of China (Z2004-1-62013) and the Young Teacher Startup Foundation Project of Lanz-hou University of Technology
文摘Alumina （Al2O3） particles reinforced copper matrix surface composites were fabricated on the bronze substrate using the vacuum infiltration casting technique. Three cases were obtained in the vacuum infiltration casting technique： no infiltration, partial infiltration and full infiltration （the thickness of preforms do not exceed 3.5mm）. The reason of no infiltration is that the vacuum degree is not enough so that the force acting on the liquid metal is lower than the resistance due to the surface tension. Partial infiltration is because of somewhat lower vacuum degree and pouring temperature. Full desired infiltration is on account of suitable infiltration casting conditions, such as vacuum degree, pouring temperature, grain size and preheating temperature of the preform. The most important factor of affecting formation of surface composites is the vacuum degree, then pouring temperature and particle size. The infiltration mechanism was discussed on the bases of different processing conditions. The surface composite up to 3.5 mm in thickness with uniformly distributed Al2O3 particles could be fabricated via the vacuum infiltration casting technique.
基金Project supported by the Technology Foundation for Basic Enhancement Plan,China (No.2021-JCJQ-JJ-0301)the National Major Research and Development Project of China (No.2018YFE0206500)+1 种基金the National Natural Science Foundation of China (No.62071140)the National Special for International Scientific and Technological Cooperation of China (No.2015DFR10220)。
文摘The performance of existing maneuvering target tracking methods for highly maneuvering targets in cluttered environments is unsatisfactory.This paper proposes a hybrid-driven approach for tracking multiple highly maneuvering targets,leveraging the advantages of both data-driven and model-based algorithms.The time-varying constant velocity model is integrated into the Gaussian process(GP)of online learning to improve the performance of GP prediction.This integration is further combined with a generalized probabilistic data association algorithm to realize multi-target tracking.Through the simulations,it has been demonstrated that the hybrid-driven approach exhibits significant performance improvements in comparison with widely used algorithms such as the interactive multi-model method and the data-driven GP motion tracker.
基金Project supported by the National Major Research and Development Project of China (No. 2018YFE0206500)the National Natural Science Foundation of China (No. 62071140)+1 种基金the International Scientific and Technological Cooperation Program of China (No. 2015DFR10220)the Technology Foundation for Basic Enhancement Plan,China (No. 2021-JCJQ-JJ-0301)。
文摘A novel algorithm that combines the generalized labeled multi-Bernoulli(GLMB) filter with signal features of the unknown emitter is proposed in this paper. In complex electromagnetic environments, emitter features(EFs) are often unknown and time-varying. Aiming at the unknown feature problem, we propose a method for identifying EFs based on dynamic clustering of data fields. Because EFs are time-varying and the probability distribution is unknown, an improved fuzzy C-means algorithm is proposed to calculate the correlation coefficients between the target and measurements, to approximate the EF likelihood function. On this basis, the EF likelihood function is integrated into the recursive GLMB filter process to obtain the new prediction and update equations.Simulation results show that the proposed method can improve the tracking performance of multiple targets,especially in heavy clutter environments.
