Rapid and precise location of the faults of on-board equipment of train control system is a significant factor to ensure reliable train operation.Text data of the fault tracking table of on-board equipment are taken a...Rapid and precise location of the faults of on-board equipment of train control system is a significant factor to ensure reliable train operation.Text data of the fault tracking table of on-board equipment are taken as samples,and an on-board equipment fault diagnosis model is designed based on the combination of convolutional neural network(CNN)and particle swarm optimization-support vector machines(PSO-SVM).Due to the characteristics of high dimensionality and sparseness of fault text data,CNN is used to achieve feature extraction.In order to decrease the influence of the imbalance of the fault sample data category on the classification accuracy,the PSO-SVM algorithm is introduced.The fully connected classification part of CNN is replaced by PSO-SVM,the extracted features are classified precisely,and the intelligent diagnosis of on-board equipment fault is implemented.According to the test analysis of the fault text data of on-board equipment recorded by a railway bureau and comparison with other models,the experimental results indicate that this model can obviously upgrade the evaluation indexes and can be used as an effective model for fault diagnosis for on-board equipment.展开更多
The reentry trajectory planning for hypersonic vehicles is critical and challenging in the presence of numerous nonlinear equations of motion and path constraints, as well as guaranteed satisfaction of accuracy in mee...The reentry trajectory planning for hypersonic vehicles is critical and challenging in the presence of numerous nonlinear equations of motion and path constraints, as well as guaranteed satisfaction of accuracy in meeting all the specified boundary conditions. In the last ten years, many researchers have investigated various strategies to generate a feasible or optimal constrained reentry trajectory for hypersonic vehicles. This paper briefly reviews the new research efforts to promote the capability of reentry trajectory planning. The progress of the onboard reentry trajectory planning, reentry trajectory optimization, and landing footprint is summarized. The main challenges of reentry trajectory planning for hypersonic vehicles are analyzed, focusing on the rapid reentry trajectory optimization, complex geographic constraints, and coop- erative strategies.展开更多
LHD's are expensive vehicles; therefore, it is important to accurately define the financial consequences associated with the investment of purchasing the mining equipment. This study concentrates on longterm incre...LHD's are expensive vehicles; therefore, it is important to accurately define the financial consequences associated with the investment of purchasing the mining equipment. This study concentrates on longterm incremental and sensitivity analysis to determine whether it is feasible to incorporate current battery technology into these machines. When revenue was taken into account, decreasing the amount of haulage in battery operated equipment by 5% or 200 kg per h amounts to a $4.0 × 10~4 loss of profit per year. On average it was found that using battery operated equipment generated $9.5 × 10~4 more in income annually, reducing the payback period from seven to two years to pay back the additional $1.0 × 10~5 investment of buying battery powered equipment over cheaper diesel equipment. Due to the estimated 5% increase in capital, it was observed that electric vehicles must possess a lifetime that is a minimum of one year longer than that of diesel equipment.展开更多
Development of man-packable,versatile marine surface vehicle with ability to rescue a drowning victim and also capable of carrying mission specific sensor is explored.Design thinking methodology is implemented by usin...Development of man-packable,versatile marine surface vehicle with ability to rescue a drowning victim and also capable of carrying mission specific sensor is explored.Design thinking methodology is implemented by using existing equipment/platform with the addition of external attachment to make it a functional product.Iterative prototyping process with extensive testing to achieve user-centric solution.Individual prototypes and their possible sub-configurations with their integration and characteristics are studied and compared with numerical model,inferences obtained are utilised to improve for the next iteration.A novel hinge-clamp assembly enables this marine surface vehicle to operate in the event of an overturn,this phenomenon is further studied with the aid of a mathematical model(Pendulum in a fluid).This research project aims to demonstrate a multi-role unmanned surface vehicle.展开更多
The utility model discloses a new type of flat vehicle for emergency patient transfer, comprising a support frame, a bed board, an infusion stand and a transfer assembly;the transfer assembly comprises a trapezoidal b...The utility model discloses a new type of flat vehicle for emergency patient transfer, comprising a support frame, a bed board, an infusion stand and a transfer assembly;the transfer assembly comprises a trapezoidal base fixed on the upper part of the support frame, and a trapezoid mounted on the bottom or side of the bed board. A sliding sleeve, a limit pin, a fixing cylinder and a spring;the trapezoidal sliding sleeve is matched on the trapezoidal base, a pin shaft hole is arranged on the trapezoidal base, the fixing cylinder is fixed on the trapezoidal sliding sleeve, and the limit pin is sleeved in the fixing cylinder, The bottom of the limit pin protrudes from the trapezoidal sliding sleeve, and the upper part is provided with a traction rod;the spring is sleeved on the traction rod, and a limiting plate is arranged at intervals on both sides of the trapezoidal base, and the limiting plate is wrapped in the trapezoidal sliding sleeve. The outer end: by setting the transfer component, the bed board is allowed to be fixed, slid and completely disengaged from the support frame, which is convenient for transferring the bed board together with the patient on it during the patient transfer process. It provides convenience for medical staff.展开更多
The robust guarantee of train control on-board equipment is inextricably linked to the safe functioning of a high-speed train.A fault diagnostic model of on-board equipment is built utilizing the integrated learning X...The robust guarantee of train control on-board equipment is inextricably linked to the safe functioning of a high-speed train.A fault diagnostic model of on-board equipment is built utilizing the integrated learning XGBoost(eXtreme Gradient Boosting)algorithm to help technicians assess the malfunction category of high-speed train control on-board equipment accurately and rapidly.The XGBoost algorithm iterates multiple decision tree models to improve the accuracy of fault diagnosis by lifting the predicted residual and adding regular terms.To begin,the text features were extracted using the improved TF-IDF(Term Frequency-Inverse Document Frequency)approach,and 24 fault feature words were chosen and converted into weight word vectors.Secondly,considering the imbalanced fault categories in the data set,the ADASYN(Adaptive Synthetic sampling)adaptive synthetically oversampling technique was used to synthesize a few category fault samples.Finally,the data samples were split into training and test sets based on the fault text data of CTCS-3train control on-board equipment recorded by Guangzhou Railway Group maintenance personnel.The XGBoost model was utilized to realize the automatic fault location of the test set after optimized parameter tuning through grid search.Compared with other methods,the evaluation index of the XGBoost model was significantly improved.The diagnostic accuracy reached 95.43%,which verifies the effectiveness of the method in text fault diagnosis.展开更多
基金Gansu Province Higher Education Innovation Fund Project(No.2020B-104)“Innovation Star”Project for Outstanding Postgraduates of Gansu Province(No.2021CXZX-606)。
文摘Rapid and precise location of the faults of on-board equipment of train control system is a significant factor to ensure reliable train operation.Text data of the fault tracking table of on-board equipment are taken as samples,and an on-board equipment fault diagnosis model is designed based on the combination of convolutional neural network(CNN)and particle swarm optimization-support vector machines(PSO-SVM).Due to the characteristics of high dimensionality and sparseness of fault text data,CNN is used to achieve feature extraction.In order to decrease the influence of the imbalance of the fault sample data category on the classification accuracy,the PSO-SVM algorithm is introduced.The fully connected classification part of CNN is replaced by PSO-SVM,the extracted features are classified precisely,and the intelligent diagnosis of on-board equipment fault is implemented.According to the test analysis of the fault text data of on-board equipment recorded by a railway bureau and comparison with other models,the experimental results indicate that this model can obviously upgrade the evaluation indexes and can be used as an effective model for fault diagnosis for on-board equipment.
基金supported by the National Natural Science Foundation of China(6127334961203223+1 种基金61175109)the Innovation Foundation of BUAA for Ph.D.Graduates(YWF-14-YJSY-013)
文摘The reentry trajectory planning for hypersonic vehicles is critical and challenging in the presence of numerous nonlinear equations of motion and path constraints, as well as guaranteed satisfaction of accuracy in meeting all the specified boundary conditions. In the last ten years, many researchers have investigated various strategies to generate a feasible or optimal constrained reentry trajectory for hypersonic vehicles. This paper briefly reviews the new research efforts to promote the capability of reentry trajectory planning. The progress of the onboard reentry trajectory planning, reentry trajectory optimization, and landing footprint is summarized. The main challenges of reentry trajectory planning for hypersonic vehicles are analyzed, focusing on the rapid reentry trajectory optimization, complex geographic constraints, and coop- erative strategies.
文摘LHD's are expensive vehicles; therefore, it is important to accurately define the financial consequences associated with the investment of purchasing the mining equipment. This study concentrates on longterm incremental and sensitivity analysis to determine whether it is feasible to incorporate current battery technology into these machines. When revenue was taken into account, decreasing the amount of haulage in battery operated equipment by 5% or 200 kg per h amounts to a $4.0 × 10~4 loss of profit per year. On average it was found that using battery operated equipment generated $9.5 × 10~4 more in income annually, reducing the payback period from seven to two years to pay back the additional $1.0 × 10~5 investment of buying battery powered equipment over cheaper diesel equipment. Due to the estimated 5% increase in capital, it was observed that electric vehicles must possess a lifetime that is a minimum of one year longer than that of diesel equipment.
文摘Development of man-packable,versatile marine surface vehicle with ability to rescue a drowning victim and also capable of carrying mission specific sensor is explored.Design thinking methodology is implemented by using existing equipment/platform with the addition of external attachment to make it a functional product.Iterative prototyping process with extensive testing to achieve user-centric solution.Individual prototypes and their possible sub-configurations with their integration and characteristics are studied and compared with numerical model,inferences obtained are utilised to improve for the next iteration.A novel hinge-clamp assembly enables this marine surface vehicle to operate in the event of an overturn,this phenomenon is further studied with the aid of a mathematical model(Pendulum in a fluid).This research project aims to demonstrate a multi-role unmanned surface vehicle.
文摘The utility model discloses a new type of flat vehicle for emergency patient transfer, comprising a support frame, a bed board, an infusion stand and a transfer assembly;the transfer assembly comprises a trapezoidal base fixed on the upper part of the support frame, and a trapezoid mounted on the bottom or side of the bed board. A sliding sleeve, a limit pin, a fixing cylinder and a spring;the trapezoidal sliding sleeve is matched on the trapezoidal base, a pin shaft hole is arranged on the trapezoidal base, the fixing cylinder is fixed on the trapezoidal sliding sleeve, and the limit pin is sleeved in the fixing cylinder, The bottom of the limit pin protrudes from the trapezoidal sliding sleeve, and the upper part is provided with a traction rod;the spring is sleeved on the traction rod, and a limiting plate is arranged at intervals on both sides of the trapezoidal base, and the limiting plate is wrapped in the trapezoidal sliding sleeve. The outer end: by setting the transfer component, the bed board is allowed to be fixed, slid and completely disengaged from the support frame, which is convenient for transferring the bed board together with the patient on it during the patient transfer process. It provides convenience for medical staff.
基金supported by the Science and Tec hnology Research and Development Plan Contract of China National Railway Group Co.,Ltd(Grant No.N2022G012)the Railway Science and Technology Research and Development Center Project(Project No.SYF2022SJ004).
文摘The robust guarantee of train control on-board equipment is inextricably linked to the safe functioning of a high-speed train.A fault diagnostic model of on-board equipment is built utilizing the integrated learning XGBoost(eXtreme Gradient Boosting)algorithm to help technicians assess the malfunction category of high-speed train control on-board equipment accurately and rapidly.The XGBoost algorithm iterates multiple decision tree models to improve the accuracy of fault diagnosis by lifting the predicted residual and adding regular terms.To begin,the text features were extracted using the improved TF-IDF(Term Frequency-Inverse Document Frequency)approach,and 24 fault feature words were chosen and converted into weight word vectors.Secondly,considering the imbalanced fault categories in the data set,the ADASYN(Adaptive Synthetic sampling)adaptive synthetically oversampling technique was used to synthesize a few category fault samples.Finally,the data samples were split into training and test sets based on the fault text data of CTCS-3train control on-board equipment recorded by Guangzhou Railway Group maintenance personnel.The XGBoost model was utilized to realize the automatic fault location of the test set after optimized parameter tuning through grid search.Compared with other methods,the evaluation index of the XGBoost model was significantly improved.The diagnostic accuracy reached 95.43%,which verifies the effectiveness of the method in text fault diagnosis.
