As one of the major high-speed railway ballastless track structures in China,CRTSIII slab ballastless track has been laid for more than 6500 km.However,there are no detailed studies on its track irregularity deteriora...As one of the major high-speed railway ballastless track structures in China,CRTSIII slab ballastless track has been laid for more than 6500 km.However,there are no detailed studies on its track irregularity deterioration throughout extended service periods,which may threaten the safety and stability of high-speed vehicles(HSV).In this study,a long-term tracking detection of CRTSIII slab ballastless track irregularities has been conducted,revealing its annual evolution law.An HSV-track coupled dynamics model was established to investigate the HSV dynamic responses under annual evolution of track irregularities.Considering the potential deterioration of track irregularities to extremely bad condition,the recommended classified limits for irregularity are proposed by analyzing the limit-exceeding probability of the safety and stability indexes of HSV.The results show that:taking 10 m wavelength as a demarcation,longer-wavelength irregularities exhibit larger amplitudes,faster evolution rates and a linear increasing trend,primarily affecting the stability of HSV.Conversely,shorter-wavelength irregularities exhibit smaller amplitudes and an insignificant evolution trend,predominantly affecting the safety of HSV.Furthermore,the periodic irregularity induced by the arching of 32 m simply-supported beam bridge should be paid closer attention to,as their evolution rate significantly surpasses that of irregularities at other wavelengths.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
At present, China's urban rail transit projects must pass strict bidding, select qualified planning companies, equipment and personnel, ensure the perfection of hardware, and minimize construction risks. Therefore...At present, China's urban rail transit projects must pass strict bidding, select qualified planning companies, equipment and personnel, ensure the perfection of hardware, and minimize construction risks. Therefore, the bidding management of urban rail transit project is very important. The bidding process must be strictly controlled in order to select the best contractor, save resources for the project, shorten the construction time and reduce the construction risk, so that the project bidding does not lose its significance. Based on the actual work, this paper discusses the standardized bidding management of urban rail transit projects.展开更多
Recently, the enterprises which had joined Japanese textile standard of self-regulation standards(that is white list management system) had been officially announced. Including Qingdao GuiHua knitting limited company,...Recently, the enterprises which had joined Japanese textile standard of self-regulation standards(that is white list management system) had been officially announced. Including Qingdao GuiHua knitting limited company, there are 32 companies accessed to white list qualification.展开更多
To date, Wald sequential probability ratio test(WSPRT) has been widely applied to track management of multiple hypothesis tracking(MHT). But in a real situation, if the false alarm spatial density is much larger than ...To date, Wald sequential probability ratio test(WSPRT) has been widely applied to track management of multiple hypothesis tracking(MHT). But in a real situation, if the false alarm spatial density is much larger than the new target spatial density, the original track score will be very close to the deletion threshold of the WSPRT. Consequently, all tracks, including target tracks, may easily be deleted, which means that the tracking performance is sensitive to the tracking environment. Meanwhile, if a target exists for a long time, its track will have a high score, which will make the track survive for a long time even after the target has disappeared. In this paper, to consider the relationship between the hypotheses of the test, we adopt the Shiryayev SPRT(SSPRT) for track management in MHT. By introducing a hypothesis transition probability, the original track score can increase faster, which solves the first problem. In addition, by setting an independent SSPRT for track deletion, the track score can decrease faster, which solves the second problem. The simulation results show that the proposed SSPRT-based MHT can achieve better tracking performance than MHT based on the WSPRT under a high false alarm spatial density.展开更多
基金Project(2022YFB2602900)supported by the National Key Research and Development Program of ChinaProject(K2022T002)supported by the Scientific Research Plan of China Railway。
文摘As one of the major high-speed railway ballastless track structures in China,CRTSIII slab ballastless track has been laid for more than 6500 km.However,there are no detailed studies on its track irregularity deterioration throughout extended service periods,which may threaten the safety and stability of high-speed vehicles(HSV).In this study,a long-term tracking detection of CRTSIII slab ballastless track irregularities has been conducted,revealing its annual evolution law.An HSV-track coupled dynamics model was established to investigate the HSV dynamic responses under annual evolution of track irregularities.Considering the potential deterioration of track irregularities to extremely bad condition,the recommended classified limits for irregularity are proposed by analyzing the limit-exceeding probability of the safety and stability indexes of HSV.The results show that:taking 10 m wavelength as a demarcation,longer-wavelength irregularities exhibit larger amplitudes,faster evolution rates and a linear increasing trend,primarily affecting the stability of HSV.Conversely,shorter-wavelength irregularities exhibit smaller amplitudes and an insignificant evolution trend,predominantly affecting the safety of HSV.Furthermore,the periodic irregularity induced by the arching of 32 m simply-supported beam bridge should be paid closer attention to,as their evolution rate significantly surpasses that of irregularities at other wavelengths.
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At present, China's urban rail transit projects must pass strict bidding, select qualified planning companies, equipment and personnel, ensure the perfection of hardware, and minimize construction risks. Therefore, the bidding management of urban rail transit project is very important. The bidding process must be strictly controlled in order to select the best contractor, save resources for the project, shorten the construction time and reduce the construction risk, so that the project bidding does not lose its significance. Based on the actual work, this paper discusses the standardized bidding management of urban rail transit projects.
文摘Recently, the enterprises which had joined Japanese textile standard of self-regulation standards(that is white list management system) had been officially announced. Including Qingdao GuiHua knitting limited company, there are 32 companies accessed to white list qualification.
基金supported by National Natural Science Foundation of China (Grant Nos. 61471019, 61501011)
文摘To date, Wald sequential probability ratio test(WSPRT) has been widely applied to track management of multiple hypothesis tracking(MHT). But in a real situation, if the false alarm spatial density is much larger than the new target spatial density, the original track score will be very close to the deletion threshold of the WSPRT. Consequently, all tracks, including target tracks, may easily be deleted, which means that the tracking performance is sensitive to the tracking environment. Meanwhile, if a target exists for a long time, its track will have a high score, which will make the track survive for a long time even after the target has disappeared. In this paper, to consider the relationship between the hypotheses of the test, we adopt the Shiryayev SPRT(SSPRT) for track management in MHT. By introducing a hypothesis transition probability, the original track score can increase faster, which solves the first problem. In addition, by setting an independent SSPRT for track deletion, the track score can decrease faster, which solves the second problem. The simulation results show that the proposed SSPRT-based MHT can achieve better tracking performance than MHT based on the WSPRT under a high false alarm spatial density.
