An analytical model is presented to study vertical dynamic response of the ballastless track on long-span plate-truss cable-stayed bridges based on an explicit dynamic analysis method.In the model,the train,ballastles...An analytical model is presented to study vertical dynamic response of the ballastless track on long-span plate-truss cable-stayed bridges based on an explicit dynamic analysis method.In the model,the train,ballastless track and bridge are treated as a coupled vibration system with interaction.By simulating the dynamic process of the system,this paper discusses the distribution law of dynamic responses of the bridge deck and the bed slab.It shows the necessity of a base plate for the ballastless track on the long-span plate-truss cable-stayed bridge.Comparison of the influence of different train speeds and stiffness of the elastic vibration-damping pad on the dynamic responses of the bridge deck and the bed slab is also made.The reasonable stiffness value of elastic vibration-damping pad is proposed.展开更多
The long baseline （LBL） system is widely used to locate and track autonomous underwater vehicles （AUV） through acoustic communication. Three important issues are presented here in LBL system application with AUV. ...The long baseline （LBL） system is widely used to locate and track autonomous underwater vehicles （AUV） through acoustic communication. Three important issues are presented here in LBL system application with AUV. Those issues which regard the normal acoustic communication between LBL system and AUV are the depth of towed army, the length of beacon cable, and the effective area of the AUV. The first issue is the key of the LBL system, which ensures the normal communication between towed array and beacons. The second issue which impacts the normal communication from the AUV to beacons in available range should be considered after the first one has been settled. Then the last issue determines the safe work area of the AUV. The ordinary differential equations （ODE） algorithm of ray is deduced from Snell＇s law. The ODE algorithm is applied to obtain sound rays from sound source to receiver. These problems are solved by the judgment that whether rays pinging from a sound source arrives at a receiver. The sea trial shows that these methods have much validity and practicality.展开更多
Multi-target tracking is facing the difficulties of modeling uncertain motion and observation noise.Traditional tracking algorithms are limited by specific models and priors that may mismatch a real-world scenario.In ...Multi-target tracking is facing the difficulties of modeling uncertain motion and observation noise.Traditional tracking algorithms are limited by specific models and priors that may mismatch a real-world scenario.In this paper,considering the model-free purpose,we present an online Multi-Target Intelligent Tracking(MTIT)algorithm based on a Deep Long-Short Term Memory(DLSTM)network for complex tracking requirements,named the MTIT-DLSTM algorithm.Firstly,to distinguish trajectories and concatenate the tracking task in a time sequence,we define a target tuple set that is the labeled Random Finite Set(RFS).Then,prediction and update blocks based on the DLSTM network are constructed to predict and estimate the state of targets,respectively.Further,the prediction block can learn the movement trend from the historical state sequence,while the update block can capture the noise characteristic from the historical measurement sequence.Finally,a data association scheme based on Hungarian algorithm and the heuristic track management strategy are employed to assign measurements to targets and adapt births and deaths.Experimental results manifest that,compared with the existing tracking algorithms,our proposed MTIT-DLSTM algorithm can improve effectively the accuracy and robustness in estimating the state of targets appearing at random positions,and be applied to linear and nonlinear multi-target tracking scenarios.展开更多
Based on the statistical characteristics analysis of random noise power and autocorrelation function, this paper proposes a de-noising method for track state detection signal by using Empirical Mode Decomposition (EMD...Based on the statistical characteristics analysis of random noise power and autocorrelation function, this paper proposes a de-noising method for track state detection signal by using Empirical Mode Decomposition (EMD). This method is used to noise reduction refactoring for the first Intrinsic Mode Function (IMF) component in accordance with the “random sort-accumulation-average-refactoring' order. Signal autocorrelation function characteristics are used to determine the cut-off point of the dominant mode. This method was applied to test signals and the actual inertial unit signals;the experimental results show that the method can effectively remove the noise and better meet the precision requirement.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.NNSF-U1334201)the National Basic Research Program of China("973"Project)(Grant No.2013CB036206)the Sichuan Province Youth Science and Technology Innovation Team(Grant No.2015TD0004)
文摘An analytical model is presented to study vertical dynamic response of the ballastless track on long-span plate-truss cable-stayed bridges based on an explicit dynamic analysis method.In the model,the train,ballastless track and bridge are treated as a coupled vibration system with interaction.By simulating the dynamic process of the system,this paper discusses the distribution law of dynamic responses of the bridge deck and the bed slab.It shows the necessity of a base plate for the ballastless track on the long-span plate-truss cable-stayed bridge.Comparison of the influence of different train speeds and stiffness of the elastic vibration-damping pad on the dynamic responses of the bridge deck and the bed slab is also made.The reasonable stiffness value of elastic vibration-damping pad is proposed.
文摘The long baseline （LBL） system is widely used to locate and track autonomous underwater vehicles （AUV） through acoustic communication. Three important issues are presented here in LBL system application with AUV. Those issues which regard the normal acoustic communication between LBL system and AUV are the depth of towed army, the length of beacon cable, and the effective area of the AUV. The first issue is the key of the LBL system, which ensures the normal communication between towed array and beacons. The second issue which impacts the normal communication from the AUV to beacons in available range should be considered after the first one has been settled. Then the last issue determines the safe work area of the AUV. The ordinary differential equations （ODE） algorithm of ray is deduced from Snell＇s law. The ODE algorithm is applied to obtain sound rays from sound source to receiver. These problems are solved by the judgment that whether rays pinging from a sound source arrives at a receiver. The sea trial shows that these methods have much validity and practicality.
基金supported by the National Natural Science Foundation of China(No.62276204)Open Foundation of Science and Technology on Electronic Information Control Laboratory,Natural Science Basic Research Program of Shanxi,China(Nos.2022JM-340 and 2023-JC-QN-0710)China Postdoctoral Science Foundation(Nos.2020T130494 and 2018M633470).
文摘Multi-target tracking is facing the difficulties of modeling uncertain motion and observation noise.Traditional tracking algorithms are limited by specific models and priors that may mismatch a real-world scenario.In this paper,considering the model-free purpose,we present an online Multi-Target Intelligent Tracking(MTIT)algorithm based on a Deep Long-Short Term Memory(DLSTM)network for complex tracking requirements,named the MTIT-DLSTM algorithm.Firstly,to distinguish trajectories and concatenate the tracking task in a time sequence,we define a target tuple set that is the labeled Random Finite Set(RFS).Then,prediction and update blocks based on the DLSTM network are constructed to predict and estimate the state of targets,respectively.Further,the prediction block can learn the movement trend from the historical state sequence,while the update block can capture the noise characteristic from the historical measurement sequence.Finally,a data association scheme based on Hungarian algorithm and the heuristic track management strategy are employed to assign measurements to targets and adapt births and deaths.Experimental results manifest that,compared with the existing tracking algorithms,our proposed MTIT-DLSTM algorithm can improve effectively the accuracy and robustness in estimating the state of targets appearing at random positions,and be applied to linear and nonlinear multi-target tracking scenarios.
文摘Based on the statistical characteristics analysis of random noise power and autocorrelation function, this paper proposes a de-noising method for track state detection signal by using Empirical Mode Decomposition (EMD). This method is used to noise reduction refactoring for the first Intrinsic Mode Function (IMF) component in accordance with the “random sort-accumulation-average-refactoring' order. Signal autocorrelation function characteristics are used to determine the cut-off point of the dominant mode. This method was applied to test signals and the actual inertial unit signals;the experimental results show that the method can effectively remove the noise and better meet the precision requirement.
