Railway wheel fault diagnosis using a fuzzy-logic method

A simple method for diagnosis of railway wheel defects using fuzzy-logic is proposed. The method is based on vibration measurements at different train speeds on healthy wheels and wheels with defects known a priori. The measured vibrations are statistically analyzed and confidence intervals for healthy and defective wheels depending on train speed and frequency of analysis are established. To facilitate the implementation of the method a fuzzy-logic is adopted. The fuzzy-logic model stores the obtained experience in a database and performs the decision making on damage extent and consequently the need of preventive maintenance. In view of the obtained results, the advantages and the limitations of the proposed approach as well as suggestions for further improvements are presented and discussed.     

A branch and bound algorithm for scheduling trains in a railway network

The paper studies a train scheduling problem faced by railway infrastructure managers during real-time traffic control. When train operations are perturbed, a new conflict-free timetable of feasible arrival and departure times needs to be re-computed, such that the deviation from the original one is minimized. The problem can be viewed as a huge job shop scheduling problem with no-store constraints. We make use of a careful estimation of time separation among trains, and model the scheduling problem with an alternative graph formulation. We develop a branch and bound algorithm which includes implication rules enabling to speed up the computation. An experimental study, based on a bottleneck area of the Dutch rail network, shows that a truncated version of the algorithm provides proven optimal or near optimal solutions within short time limits.     

Topological laminations on surfaces

We present and prove a topological characterization of geodesic laminations on hyperbolic surfaces of finite type.     

物理实验教学新模式的探索与实践

提出了一种新的物理实验教学模式，论述了建立实验教学模式所遵循的基本原则和基本做法，简要介绍实施新的教学模式所取得的教学成果。     

A green train scheduling model and fuzzy multi-objective optimization algorithm

Train scheduling model is traditionally formulated to minimize the energy consumption for reducing the operation cost. As the European Union formulates the first carbon emission trading scheme in the world, it is necessary to extend the operation cost to include the expenses for buying/selling the carbon emission allowances. In this paper, we propose a multi-objective train scheduling model by minimizing the energy and carbon emission cost as well as the total passenger-time, and named it as green train scheduling model. For obtaining a non-dominated timetable which has equal satisfactory degree on both objectives, we apply a fuzzy multi-objective optimization algorithm to solve the model. Finally, we perform two numerical examples to illustrate the efficiency of the proposed model and solution methodology.     

Train Algèbres Alternatives: Relation Entre Nilindice et Degré

We determine train polynomials for power associative algebras and for alternative train algebras. We show bonds between polynomials and nilindices of some factors of the Peirce decomposition.     

De-noising of wayside acoustic signal from train bearings based on variable digital filtering

In the wayside Acoustic Defective Bearing Detector (ADBD) system, the recorded signal usually includes both the sound from train bearings and the other disturbance sources. The fact of heavy noise corruption and the Doppler Effect of multi-source acoustic signals would badly reduce the effectiveness of online defect detection of the ADBD system. In order to extract useful information from the multi-source signal with Doppler Effect, this paper proposes an effective de-noising method based on the variable digital filter (VDF) for the ADBD system. Specifically, the ridge extraction based on Short-Time Fourier Transform (STFT) is applied to estimate the instantaneous frequencies (IFs), with which the fitting IF curves based on the Morse theory of theoretical acoustics could be achieved by using the nonlinear curve-fitting so that the parameters of the initial position of the acoustic sources could be calculated. By the aid of these parameters, the IFs according to the target train bearing could be then extracted. After that, the FIR variable digital filters could be designed with all the IFs which match the Morse theory with Doppler Shift so that the noise from the other parts could be effectively restrained after filtering the original signal. The effectiveness of this method is verified by means of a simulation with multi-frequency signals and applications to diagnosis of train roller bearing defects. Results indicate that the proposed method is effective.     

Influence of turbulence on train noise

The subject of this paper is the long distance propagation of train noise. The sound exposure level of train noise L_AE was measured. To describe the results of measurements, a semi-analytical model was used. It takes into account the wave-front divergence, air absorption, ground effect, and the turbulence destroying the coherent nature of the ground effect. The model contains three adjustable parameters that must be estimated at the site. To verify the model, we performed measurements of L_AE at the distance D = 450 m from the train track center. The difference between the calculated and measured mean values of L_AE equals 1.3 dB.     

Investigating cross-wind stability of high-speed trains with large-scale parallel CFD

ABSTRACT

The side-wind loading on a simplified train model at scale 1:25 is investigated by parallel large eddy simulation (LES) with incompressible solvers from the OpenFOAM package and a novel dynamically adaptive, parallel LES-type lattice Boltzmann method (LBM) implemented in our own AMROC framework. It is found that the new LBM code provides more accurate time-averaged force predictions, while compute times are reduced.     

A disjunctive graph model and framework for constructing new train schedules

Train scheduling is a complex and time consuming task of vital importance in many countries. To create completely new train schedules that are more accurate and efficient than permitted by current techniques, a novel “hybrid” job shop approach is proposed and implemented in this paper. Unique characteristics of train scheduling are firstly incorporated into a disjunctive graph representation of the solution. Dedicated “stand-alone” constructive algorithms that utilise this representation are then developed. The modelling approach and the constructive algorithms are essential as they provide the basis for which meta-heuristics and other iterative refinement algorithms can be applied. A numerical investigation and case study is provided and demonstrates the viability of the modelling approach. Furthermore it is demonstrated that good quality solutions are provided with reasonable computational effort.