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Dou F.,Beijing Jiaotong University | Dou F.,Mass Transit Railway Operation Corporation LTD | Jia L.,Beijing Jiaotong University | Wang L.,Beijing Jiaotong University | And 2 more authors.
Computational Intelligence and Neuroscience | Year: 2014

Passenger flow forecast is of essential importance to the organization of railway transportation and is one of the most important basics for the decision-making on transportation pattern and train operation planning. Passenger flow of high-speed railway features the quasi-periodic variations in a short time and complex nonlinear fluctuation because of existence of many influencing factors. In this study, a fuzzy temporal logic based passenger flow forecast model (FTLPFFM) is presented based on fuzzy logic relationship recognition techniques that predicts the short-term passenger flow for high-speed railway, and the forecast accuracy is also significantly improved. An applied case that uses the real-world data illustrates the precision and accuracy of FTLPFFM. For this applied case, the proposed model performs better than the k-nearest neighbor (KNN) and autoregressive integrated moving average (ARIMA) models. © 2014 Fei Dou et al.


Dou F.,Beijing Jiaotong University | Dou F.,Mass Transit Railway Operation Corporation LTD | Jia L.,Beijing Jiaotong University | Qin Y.,Beijing Jiaotong University | And 2 more authors.
Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology) | Year: 2014

Passenger flow of passenger dedicated line shows the quasi-periodic variations in the short-term forecasts, and also shows complex nonlinear characteristics because of many factors. The traditional prediction model can't fully reflect quasi-periodic and nonlinear characteristics of the passenger flow, which result in larger errors in forecast results. In order to forecast the passenger flow more accurately, the passenger flow characteristics of the high-speed railway were analyzed, and variation of passenger flow in the adjacent period was summed up. Passenger flow change rate was divided into different grades and fuzzified on the basis of passenger flow change rate between adjacent periods. Also, fuzzy k-nearest neighbor prediction model was established on the basis of the fuzzy values timing relationship of passenger flow change rate. By comparing it with other predictive methods, the prediction result of fuzzy k-nearest neighbor prediction model is proved to be more accurate and precise, thus providing a new idea for the railway passenger flow forecast. ©, 2014, Central South University of Technology. All right reserved.


Yao D.,Beijing University of Civil Engineering and Architecture | Yang J.,Beijing University of Civil Engineering and Architecture | Li X.,Mass Transit Railway Operation Corporation Ltd. | Zhao C.,Beijing University of Civil Engineering and Architecture
Mathematical Problems in Engineering | Year: 2016

Vibration signals resulting from railway rolling bearings are nonstationary by nature; this paper proposes a hybrid approach for the fault diagnosis of railway rolling bearings using segment threshold wavelet denoising (STWD), empirical mode decomposition (EMD), genetic algorithm (GA), and least squares support vector machine (LSSVM). The original signal is first denoised using STWD as a prefilter, which improves the subsequent decomposition into a number of intrinsic mode functions (IMFs) using EMD. Secondly, the IMF energy-torques are extracted as feature parameters. Concurrently, a GA is employed to optimize the LSSVM to improve the classification accuracy. Finally, the extracted features are used as inputs for classification by the GA-LSSVM. Actual railway rolling bearing vibration signals are used to experimentally verify the effectiveness of the proposed method. The results show that the novel method is effective and accurate for fault diagnosis of railway rolling bearings. © 2016 Dechen Yao et al.


Yang J.,Beijing University of Civil Engineering and Architecture | Yang M.,Beijing University of Civil Engineering and Architecture | Li X.,Mass Transit Railway Operation Corporation LTD | Wang X.,Taiyuan University of Science and Technology
Open Mechanical Engineering Journal | Year: 2015

Light-weighting of high speed railway equipments has become a major trend, which leads the upgrades of equipments. A new C-shaped bracket has been produced to connect the driving gearbox with the bogie. This paper built a three-dimensions model of a C-shaped bracket, got the maximum and distribution of the stress and deformation under two different working conditions form finite element analysis (FEA). Then it presents a method to perform a corresponding experiment. It is observed that the computed values form FEA are in very good agreement with the experimental values, which both verified the structural strength of this C-shaped bracket. © Yang et al.; Licensee Bentham Open.


Li X.,Beijing Jiaotong University | Li X.,Mass Transit Railway Operation Corporation LTD | Zhang Y.,Mass Transit Railway Operation Corporation LTD | Jia L.,Beijing Jiaotong University
Lecture Notes in Electrical Engineering | Year: 2014

In order to diagnose different kinds of subway vehicle rolling bearing faults, a new method of fault diagnosis methodology based on improved wavelet packet and PNN (Probabilistic Neural Network) was put forward. Vibration signal of subway vehicle rolling bearing was collected by Piezoelectric Accelerometer. The collected signal was denoised by wavelet, and then decomposed by the improved wavelet packet, constructing the eigenvector. The signal was taken as fault samples to train the improved PNN neural network. The whole process finally recognizes fault types and realizes intelligent fault diagnosis. Test results show that the application of fault diagnosis method can effectively diagnose rolling bearing faults such as fatigue, peeling, and crack which occurred in inner ring, outer ring, and the rolling body surface during subway vehicle operation. The fault diagnosis method has high application value in the subway operation process. © 2014 Springer-Verlag Berlin Heidelberg.


Jianwei Y.,Beijing University of Civil Engineering and Architecture | Dechen Y.,Beijing University of Civil Engineering and Architecture | Xi L.,Mass Transit Railway Operation Corporation LTD | Limin J.,Beijing Jiaotong University | Yong Q.,Beijing Jiaotong University
Open Automation and Control Systems Journal | Year: 2015

In this paper, we present an way for railway bearing fault diagnosis with the use of FIR-wavelet packet and LVQ neural network, First, the original vibration signal of trains’ rolling bearing is denoised based on FIR. Then, the signals after de-noised are preprocessed by wavelet packet and the wavelet packet energy eigenvector is reconstructed, those kinds of wavelet packet energy eigenvectors are used to train LVQ neural network. Finally, the intelligent fault diagnosis is realized. The result shows that this approach is effective to distinguish this kind of rolling bearing faults. This method has important practical value. © Jianwei et al.


Yang J.,Beijing University of Civil Engineering and Architecture | Zhao C.,Beijing University of Civil Engineering and Architecture | Li X.,Mass Transit Railway Operation Corporation LTD | Wang F.,Taiyuan University of Science and Technology
Open Mechanical Engineering Journal | Year: 2015

In order to solve reliability evaluation of life of electromagnetic valve of EMUs, this paper evaluates the life of electromagnetic valve under small sample size based on zero-failure data. Firstly, this paper selects the prior distribution of the failure probability, and then the posteriori distribution is obtained by using the Bayes method so that the Bayes estimation can be received under the square loss. Finally, according to the pi received, the reliability parameters of twoparameter exponential distribution are estimated based on weighted least square method. In addition, this paper applies the reliability theory to the reliability life evaluation of electromagnetic valve of EMUs which shows this method can solve the reliability assessment problem which provides certain theoretical basis for the reliability of electromagnetic valve. © Yang et al.

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