Design and verification of an improved experimental platform for stray current in urban rail transit

With the rapid development of urban rail transit,there have been an urgent problem of excessive stray current.Because the stray current distribution is random and difficult to verify in the field,we designed an improved stray current experimental platform by replacing the simulated aqueous solution with a real soil environment and by calculating the transition resistance by measuring the soil resistivity,which makes up for the defects in the previous references.Firstly,the mathematical models of rail-drainage net and rail-drainage netground were established,and the analytical expressions of current and voltage of rail,drainage net and other structures were derived.In addition,the simulation model was built,and the mathematical analysis results were compared with the simulation results.Secondly,the accuracy of the improved stray current experimental platform was verified by comparing the measured and simulation results.Finally,based on the experimental results,the influence factors of stray current were analyzed.The relevant conclusions provide experimental data and theoretical reference for the study of stray current in urban rail transit.

基于翻转课堂的答疑方式改革与实践——以《车站信号自动控制》课程设计为例

传统课程答疑方式下,学生的学习积极性不高,学生对课堂内容的掌握程度无从得知,将翻转课堂教学思想应用于课程设计答疑,采用"学生互答+传统答疑"结合的方式。实施结果表明,除了深入掌握相关知识点在具体信号系统设计过程中的应用外,学生学习的积极性、自觉性和主动性大大提高。

Optimization of maintenance strategy for high-speed railwaycatenary system based on multistate model

A multi-objective optimization model considering both reliability and maintenance cost is proposed to solve the contradiction between reliability and maintenance cost in high-speed railway catenary system maintenance activities.The non-dominated sorting genetic algorithm 2(NSGA2)is applied to multi-objective optimization,and the optimization result is a set of Pareto solutions.Firstly,multistate failure mode analysis is conducted for the main devices leading to the failure of catenary,and then the reliability and failure mode of the whole catenary system is analyzed.The mathematical relationship between system reliability and maintenance cost is derived considering the existing catenary preventive maintenance mode to improve the reliability of the system.Secondly,an improved NSGA2(INSGA2)is proposed,which strengths population diversity by improving selection operator,and introduces local search strategy to ensure that population distribution is more uniform.The comparison results of the two algorithms before and after improvement on the zero-ductility transition(ZDT)series functions show that the population diversity is better and the solution is more uniform using INSGA2.Finally,the INSGA2 is applied to multi-objective optimization of system reliability and maintenance cost in different maintenance periods.The decision-makers can choose the reasonable solutions as the maintenance plans in the optimization results by weighing the relationship between the system reliability and the maintenance cost.The selected maintenance plans can ensure the lowest maintenance cost while the system reliability is as high as possible.

Fractional order integral sliding mode control for PMSM based onfractional order sliding mode observer

In view of the variation of system parameters and external load disturbance affecting the high-performance control of permanent magnet synchronous motor(PMSM),a fractional order integral sliding mode control(FOISMC)strategy is developed for PMSM drive system by means of fractional order sliding mode observer(FOSMO).Based on FOISMC technology,a fractional order integral sliding mode regulator(FOISM-based regulator)is designed,and a global integral sliding mode surface design method is presented,which can guarantee the global robustness of the system.Combining fractional order theory and sliding mode control theory,the FOSMO is constructed to achieve better identification accuracy of the speed and rotor position.Meanwhile the sliding mode load observer is used to observe the load torque in real time,and the observed value is transmitted to speed regulator to improve the capability of accommodating the challenge of load disturbance.Simulation results validate the feasibility and effectiveness of the proposed scheme.

Modeling research of train tracing based on UML sequence diagram and UPPAAL

The zone control subsystem is a real-time control system,which requests the correctness of the control process.Train tracing scene is an important function of the zone controller(ZC)in the communication based train control(CBTC)system.In the process of deep development and design,to ensure the safety of the system,the system needs to be modeled,simulated and verified to discover the system design flaws.Unified modeling language(UML)is combined with timed automata,and timed automata network models of train-filter and train tracing demarcation-point are established.At the same time,the verification tool of UPPAAL is applied to simulate the system,and verify the requirements of performance and function of system.The results show that the function of train tracing demaraction-point meets the requirements of system safety and limited activity.Therefore,the method is feasible and can be applied to the modeling and verification of other scenes of train control system.

Multi-objective optimization scheduling for new energy power system considering energy storage participation

For the low utilization rate of photovoltaic power generation,taking a new energy power system constisting of concentrating solar power(CSP),photovoltaic power(PP)and battery energy storage system as an example,a multi-objective optimization scheduling strategy considering energy storage participation is proposed.Firstly,the new energy power system model is established,and the PP scenario generation and reduction frame based on the autoregressive moving average model and Kantorovich-distance is proposed.Then,based on the optimization goal of the system operation cost minimization and the PP output power consumption maximization,the multi-objective optimization scheduling model is established.Finally,the simulation results show that introducing energy storage into the system can effectively reduce the system operation cost and improve the utilization efficiency of PP.

Dynamic obstacles detection of tram based on laser radar

The detection of obstacles in a dynamic environment is a hot and difficult problem.A method of autonomously detecting obstacles based on laser radar is proposed as a safety auxiliary structure of tram.The nearest neighbor method is used for spatial obstacles clustering from laser radar data.By analyzing the characteristics of obstacles,the types of obstacles are determined by time correlation.Experiments were carried out on the developed unmanned aerial vehicle(UAV),and the experimental results verify the effectiveness of the proposed method.

Facial expression feature extraction method based on improved LBP

Local binary pattern(LBP)is an important method for texture feature extraction of facial expression.However,it also has the shortcomings of high dimension,slow feature extraction and noeffective local or global features extracted.To solve these problems,a facial expression feature extraction method is proposed based on improved LBP.Firstly,LBP is converted into double local binary pattern(DLBP).Then by combining Taylor expansion(TE)with DLBP,DLBP-TE algorithm is obtained.Finally,the DLBP-TE algorithm combined with extreme learning machine(ELM)is applied in seven kinds of ficial expression images and the corresponding experiments are carried out in Japanese adult female facial expression(JAFFE)database.The results show that the proposed method can significantly improve facial expression recognition rate.

Simulation on model predictive control for PMSM drive system based on double extended state observer

A novel double extended state observer(DESO)based on model predictive torque control(MPTC)strategy is developed for three-phase permanent magnet synchronous motor(PMSM)drive system without current sensor.In general,to achieve high-precision control,two-phase current sensors are necessary for successful implementation of MPTC.For this purpose,two ESOs are used to estimate q-axis current and stator resistance respectively,and then based on this,d-axis current is estimated.Moreover,to reduce torque and flux ripple and to improve the performance of the torque and speed,MPTC strategy is designed.The simulation results validate the feasibility and effectiveness of the proposed scheme.

Combination forecast for urban rail transit passenger flow based on fuzzy information granulation and CPSO-LS-SVM

In order to obtain the trend of urban rail transit traffic flow and grasp the fluctuation range of passenger flow better,this paper proposes a combined forecasting model of passenger flow fluctuation range based on fuzzy information granulation and least squares support vector machine(LS-SVM)optimized by chaos particle swarm optimization(CPSO).Due to the nonlinearity and fluctuation of the passenger flow,firstly,fuzzy information granulation is used to extract the valid data from the window according to the requirement.Secondly,CPSO that has strong global search ability is applied to optimize the parameters of the LS-SVM forecasting model.Finally,the combined model is used to forecast the fluctuation range of early peak passenger flow at Tiyu Xilu Station of Guangzhou Metro Line 3 in 2014,and the results are compared and analyzed with other models.Simulation results demonstrate that the combined forecasting model can effectively track the fluctuation of passenger flow,which provides an effective method for predicting the fluctuation range of short-term passenger flow in the future.

Peak shaving operation optimization of high proportion new energypower generation considering wind-solar complementationand source-load coupling

To optimize peaking operation when high proportion new energy accesses to power grid,evaluation indexes are proposed which simultaneously consider wind-solar complementation and source-load coupling.A typical wind-solar power output scene model based on peaking demand is established which has anti-peaking characteristic.This model uses balancing scenes and key scenes with probability distribution based on improved Latin hypercube sampling(LHS)algorithm and scene reduction technology to illustrate the influence of wind-solar on peaking demand.Based on this,a peak shaving operation optimization model of high proportion new energy power generation is established.The various operating indexes after optimization in multi-scene peaking are calculated,and the ability of power grid peaking operation is compared whth that considering wind-solar complementation and source-load coupling.Finally,a case of high proportion new energy verifies the feasibility and validity of the proposed operation strategy.

Fault diagnosis method of train control RBC system based on KPCA-SOM network

Radio block center(RBC)system is the core equipment of China train control system-3(CTCS-3).Now,the fault analysis of RBC system mainly depends on manual work,and the diagnostic results are inaccurate and inefficient.Therefore,the intelligent fault diagnosis method of RBC system based on one-hot model,kernel principal component analysis(KPCA)and self-organizing map(SOM)network was proposed.Firstly,the fault document matrix based on one-hot model was constructed by the fault feature lexicon selected manually and fault tracking record table.Secondly,the KPCA method was used to reduce the dimension and noise of the fault document matrix to avoid information redundancy.Finally,the processed data were input into the SOM network to train the KPCA-SOM fault classification model.Compared with back propagation(BP)neural network algorithm and SOM network algorithm,common fault patterns of train control RBC system can be effectively distinguished by KPCA-SOM intelligent diagnosis model,and the accuracy and processing efficiency are further improved.

Application of CS-PSO algorithm in Bayesian network structure learning

In view of the shortcomings of traditional Bayesian network(BN)structure learning algorithm,such as low efficiency,premature algorithm and poor learning effect,the intelligent algorithm of cuckoo search(CS)and particle swarm optimization(PSO)is selected.Combined with the characteristics of BN structure,a BN structure learning algorithm of CS-PSO is proposed.Firstly,the CS algorithm is improved from the following three aspects:the maximum spanning tree is used to guide the initialization direction of the CS algorithm,the fitness of the solution is used to adjust the optimization and abandoning process of the solution,and PSO algorithm is used to update the position of the CS algorithm.Secondly,according to the structure characteristics of BN,the CS-PSO algorithm is applied to the structure learning of BN.Finally,chest clinic,credit and car diagnosis classic network are utilized as the simulation model,and the modeling and simulation comparison of greedy algorithm,K2 algorithm,CS algorithm and CS-PSO algorithm are carried out.The results show that the CS-PSO algorithm has fast convergence speed,high convergence accuracy and good stability in the structure learning of BN,and it can get the accurate BN structure model faster and better.

Life prediction of ZPW-2000A track circuit equipment based on SVDD and gray prediction

Evaluation of the health state and prediction of the remaining life of the track circuit are important for the safe operation of the equipment of railway signal system.Based on support vector data description(SVDD)and gray prediction,this paper illustrates a method of life prediction for ZPW-2000A track circuit,which combines entropy weight method,SVDD,Mahalanobis distance and negative conversion function to set up a health state assessment model.The model transforms multiple factors affecting the health state into a health index named H to reflect the health state of the equipment.According to H,the life prediction model of ZPW-2000A track circuit equipment is established by means of gray prediction so as to predict the trend of health state of the equipment.The certification of the example shows that the method can visually reflect the health state and effectively predict the remaining life of the equipment.It also provides a theoretical basis to further improve the maintenance and management for ZPW-2000A track circuit.

Active disturbance rejection control FCS-MPC strategy based on ESO of PMSM system

In order to improve the control performance of three-phase permanent magnet synchronous motor(PMSM)system,an active disturbance rejection finite control set-mode predictive control(FCS-MPC)strategy based on improved extended state observer(ESO)is proposed in this paper.ESO is designed based on the arc-hyperbolic sine function to obtain estimations of rotating speed and back electromotive force(EMF)term of motor speed.Active disturbance rejection control(ADRC)is applied as speed controller.The proposed FCS-MPC strategy aims to reduce the electromagnetic torque ripple and the complexity and calculation of the algorithm.Compared with the FCS-MPC strategy based on PI controller,the constructed control strategy can guarantee the reliable and stable operation of PMSM system,and has good speed tracking,anti-interference ability and robustness.

Channel characteristics analysis of train-to-train wireless communication

Train-to-train(T2T)communication can provide protection for existing train-to-ground private network communication,and its channel characteristics directly affect the application of upper-layer communication technologies.In this study,based on the spatial distribution structure of railway operation scenarios and Fresnel zone theory,we propose a frequency allocation scheme for direct communication between tracking trains in flatland and long straight tunnel scenario.Then we use the estimation method of radio wave attenuation caused by rainfall to analyze the large-scale path loss fading of multi-band wireless channels.Furthermore,we derive the calculation equation of max Doppler frequency shift suitable for T2T communication and describe the multipath wave in the tunnel by ray tracing method to analyze small-scale fading.Simulation analysis shows that the Doppler shift value of T2T communication low frequency band is significantly lower than the frequency shift value of the train-to-ground communication under the same speed conditions.

Calculation and analysis of losses of magnetic-valve controllable reactor

Magnetic-valve controllable reactor(MCR)has characteristics of DC bias and different types of magnetic flux density in the magnetic circuit and winding current distortion.These characteristics not only lead to loss calculation method of MCR different from that of power transformer,but also make it more difficult to calculate the core loss and wingding loss of MCR accurately.Our study combines core partition method with dynamic inverse J-A model to calculate the core loss of MCR.The winding loss coefficient of MCR is proposed,which takes into account the influence of harmonics and magnetic flux leakage on the winding loss of MCR.The result shows that the proposed core loss calculation method and winding loss coefficient are effective and correct for the loss calculation of MCR.

Fault diagnosis method of track circuit based on KPCA-SAE

At present,ZPW-2000 track circuit fault diagnosis is artificially analyzed and monitored.Its discrimination method not only is low efficient and takes a long period,but also requires highly experienced personnel to analyze the data.Therefore,we introduce kernel principal component analysis and stacked auto-encoder network(KPCA-SAD)into the fault diagnosis of ZPW-2000 track circuit.According to the working principle and fault characteristics of track circuit,a fault diagnosis model of KPCA-SAE network is established.The relevant parameters of key components recorded in the data collected by field staff are used as the fault feature parameters.The KPCA method is used to reduce the dimension and noise of fault document matrix to avoid information redundancy.The SAE network is trained by the processed fault data.The model parameters are optimized overall by using back propagation(BP)algorithm.The KPCA-SAE model is simulated in Matlab platform and is finally proved to be effective and feasible.Compared with the traditional method of artificially analyzing fault data and other intelligent algorithms,the KPCA-SAE based classifier has higher fault identification accuracy.

Improved control strategy for PMSM based on fuzzy sliding mode control and sliding-mode observer

Aimed at the problems of large torque ripple,obvious chattering and poor estimation accuracy of back-EMFs in traditional permanent magnet synchronous motor(PMSM)control system with sliding mode observer(SMO),an improved control strategy for PMSM based on a fuzzy sliding mode control(FSMC)and a two-stage filter sliding mode observer(TFSMO)is proposed.Firstly,a novel reaching law(NRL)used in the speed loop based on hyperbolic sine function is studied,and fuzzy control ideal is shown to achieve the self-turning of the parameter for the reaching law,thus a fuzzy integral sliding mode controller based on the novel reaching law is designed in speed loop.Then the suppression effect upon chattering caused by the novel reaching law is analyzed strictly by discrete equation.Secondly,in order to restrain the high frequency components and measurement noise in back-EMFs,a two-stage filter structure based on a variable cut-off frequency low-pass filter(VCF-LPF)and a modified back-EMF observer(MBO)is conceived,and the rotor position is compensated reasonably.As a result,a TFSMO is designed.The stability of the proposed control strategy is proved by Lyapunov Criterion.The simulation and experiment results show that,compared with traditional SMO,the controller suggested above can obtain very nice system respond when the motor starts and is subjected to external disturbances,and effectively improve the problems about torque ripple,chattering and the estimation accuracy of back-EMF.

Control strategy of LCL-type three-phase photovoltaic grid connected inverter

The grid-connected inverter with LCL filter has the ability of easily attenuating high-frequency current harmonics. However, its suppression effect on the background harmonics in grid voltage is limited. A control strategy is presented, which is composed of an inner loop of capacitor current feedforward, an outer loop of grid-current feedforward and feedforward of grid voltage. The limitations and steps of parameters design for LCL filter are analyzed. Meanwhile, the capacitor current loop is employed to damp the resonant peak caused by the LCL filter and enhance the stability. The properties of different controllers are analyzed and compared, thereinto quasi-proportional-rasonant (PR) controller realizes the control with zero steady-state error of AC variables in static coordinates. In order to suppress the current distortion effected by the background harmonics in grid voltage, the feed-forward function is calculated for the grid-connected inverter with an LCL filter. After simplifying the block diagram, a full-feedforward control strategy for grid voltage is proposed. Theoretical analysis and Matlab/Simulink simulation results show that the proposed method has the advantages of high steady accuracy, fast dynamic response and strong robustness.