The ammunition loading system manipulator is susceptible to gear failure due to high-frequency,heavyload reciprocating motions and the absence of protective gear components.After a fault occurs,the distribution of fau...The ammunition loading system manipulator is susceptible to gear failure due to high-frequency,heavyload reciprocating motions and the absence of protective gear components.After a fault occurs,the distribution of fault characteristics under different loads is markedly inconsistent,and data is hard to label,which makes it difficult for the traditional diagnosis method based on single-condition training to generalize to different conditions.To address these issues,the paper proposes a novel transfer discriminant neural network(TDNN)for gear fault diagnosis.Specifically,an optimized joint distribution adaptive mechanism(OJDA)is designed to solve the distribution alignment problem between two domains.To improve the classification effect within the domain and the feature recognition capability for a few labeled data,metric learning is introduced to distinguish features from different fault categories.In addition,TDNN adopts a new pseudo-label training strategy to achieve label replacement by comparing the maximum probability of the pseudo-label with the test result.The proposed TDNN is verified in the experimental data set of the artillery manipulator device,and the diagnosis can achieve 99.5%,significantly outperforming other traditional adaptation methods.展开更多
To enhance the security of network systems, puts forward a kind of software agent is put forward, which has the induction ability of network frameworks and the ability of behavior independence. It is mobile scanning a...To enhance the security of network systems, puts forward a kind of software agent is put forward, which has the induction ability of network frameworks and the ability of behavior independence. It is mobile scanning agent. More attentions is paid to expound how to design and realize mobile scanning agent. Besides, it is also explained the programs of mobile scanning agent system. In the end, it expects mobile scanning agent.展开更多
Concurrent multipath transfer（CMT） using stream control transmission protocol（SCTP） multihoming has become an appealing option to increase the throughput and improve the performance of increasingly bandwidth-hungr...Concurrent multipath transfer（CMT） using stream control transmission protocol（SCTP） multihoming has become an appealing option to increase the throughput and improve the performance of increasingly bandwidth-hungry applications.To investigate the rate allocation for applications in CMT,this paper analyzes the capacities of paths shared by competing sources,then proposes the rate allocation model for elastic flows based on the framework of network utility maximization（NUM）.In order to obtain the global optimum of the model,a distributed algorithm is presented which depends only on local available information.Simulation results confirm that the proposed algorithm can achieve the global optimum within reasonable convergence times.展开更多
文摘The ammunition loading system manipulator is susceptible to gear failure due to high-frequency,heavyload reciprocating motions and the absence of protective gear components.After a fault occurs,the distribution of fault characteristics under different loads is markedly inconsistent,and data is hard to label,which makes it difficult for the traditional diagnosis method based on single-condition training to generalize to different conditions.To address these issues,the paper proposes a novel transfer discriminant neural network(TDNN)for gear fault diagnosis.Specifically,an optimized joint distribution adaptive mechanism(OJDA)is designed to solve the distribution alignment problem between two domains.To improve the classification effect within the domain and the feature recognition capability for a few labeled data,metric learning is introduced to distinguish features from different fault categories.In addition,TDNN adopts a new pseudo-label training strategy to achieve label replacement by comparing the maximum probability of the pseudo-label with the test result.The proposed TDNN is verified in the experimental data set of the artillery manipulator device,and the diagnosis can achieve 99.5%,significantly outperforming other traditional adaptation methods.
基金Supported by National Natural Science Foundation of P. R. China （60574083）, Key Laboratory of Process Industry Automation, State Education Ministry of China （PAL200514）
文摘To enhance the security of network systems, puts forward a kind of software agent is put forward, which has the induction ability of network frameworks and the ability of behavior independence. It is mobile scanning agent. More attentions is paid to expound how to design and realize mobile scanning agent. Besides, it is also explained the programs of mobile scanning agent system. In the end, it expects mobile scanning agent.
基金supported by the National Natural Science Foundation of China (60833002)the National Basic Research Program of China (973 Program) (2007CB307100)+2 种基金the National High Technology Research and Development Program of China (863 Program) (2007AA01Z202)the Program for Changjiang Scholars and Innovative Research Team in University (IRT0707)the Program of Introducing Talents of Discipline to Universities (111 Project) (B08002)
文摘Concurrent multipath transfer（CMT） using stream control transmission protocol（SCTP） multihoming has become an appealing option to increase the throughput and improve the performance of increasingly bandwidth-hungry applications.To investigate the rate allocation for applications in CMT,this paper analyzes the capacities of paths shared by competing sources,then proposes the rate allocation model for elastic flows based on the framework of network utility maximization（NUM）.In order to obtain the global optimum of the model,a distributed algorithm is presented which depends only on local available information.Simulation results confirm that the proposed algorithm can achieve the global optimum within reasonable convergence times.
