| Electrification is widely adopted in railway operation in china, which, in comparison with traditional modes of traction, is more complex in both equipment and its structure.Along with frequent attendance in actual situation, its performance gradually becomes changed and some of the worsen condition began to pose a negative influence on the safe operation of high speed railway. As such, it is imperative that we maintain the well going of the tractive power supply system so that security could be ensured. Under the background that national design, manufacturing and integration for tractive power supply system in high speed railway play a bridgehead role in the world, main challenges that persist still lie in the management of tractive power supply system in high speed railway.On the one hand, owing to the electrical sectioning in the industrial frequency AC electric locomotive, breakpoint occurred, which falls into the main constraint for the pronounced problem of transportation capacity and speed and the major solvent for this issue lies in the cophase power supply. Despite the fact that cophase power supply technology has witnessed remarkable improvement in its development and application,study for operation maintenance of such equipment remains far from being satisfying,making it even harder to see the further development. On the other hand, the state of catenary pantograph system in operation would leave a direct impact on tractive power supply system in high speed railway. Resulted in the long-term service of the facility,performance of its key parts could be lowered due to the degradation; hence, power supply breakdown happens frequently. Although we have launched the study of safety inspection monitoring (6C System) for high speed tractive power supply system, the way for efficiency use of mass data remains vague so that we could not grasp the degradation pattern of the facility not to mention the conduction of according maintenance. In other words, this problem remains a challenging one which needs the best endeavor of us.To conclude, the long-term use of high speed railway tractive power supply system could be changed in its security condition, which would pose great challenges on the maintenance for the facility. To meet the challenging needs for this problem, we could conduct on-line monitoring and state inspection on the basis of the data analysis monitoring.By studying the traction substation, overhead line system, pantograph device and the relevant data and dynamic parameter changing, we could find the changing pattern of degradation in traction power supply in failure state, which, in turn, could facilitate the work of pointed maintenance. As such, based on modeling optimization study for monitoring information of the tractive power supply system,this paper aims to conduct a synthesized study which comprises the main part of the study for "cophase supply maintenance study and technology study" and "the prediction failure prediction and healthy maintenance of high speed railway tractive power supply system ". Main contents for this passage are as follows:(1) According to the construction plan for the new type cophase power supply device and analysis on its reliability, this coupled with the synthesized discussion over the status of the degradation of the device and the in-depth research of Markov Process, we have devised an optimized modeling for the condition-based maintenance, which, on the one hand, laid a solid theoretical foundation for cophase power supply in electrified railway, on the other hand, it could also help to promote the reliability and efficiency of the device in operation process.(2) Through the analysis on the monitoring data from the inspection over vibration signal of ratcheted wheel compensation device in high speed railway catenary, the passage proposes a way for observing and optimizing the machinery breakdown in overhead line system. By utilizing the interdependence relation of characteristics and classifier parameters,the passage also builds up a wavelet-analysis-based KNN parameter (abbreviated as k-NearestNeighbor) and detection model for machinery breakdowns.?(3) On the basis of fixed point vibration monitoring system, the passage also comes out with a method to detect the breakdowns in high speed railway catenary. Procedures for this method go as the following: first, improving the recognition of wavelet signal by the modified form of wavelet decomposition by finite variation in the definition for wavelet entropy; thence, decomposing the wavelet in individual anchoring section of typical breakdown signals in high speed railway catenary, extracting the subband wavelet entropy to reveal the complexities in the signals at different dimensions; finally, classifying and detecting the decomposed wavelet signal by using the support vector machine (SVM). The simulation has proved its advantage.(4) Characteristics of machinery abrade in process and breakdown occurs the high speed railway catenary-pantograph-system was also introduced in this paper. After this, the paper proposes the dynamic simulation of interface wear under the influence of stiffness coefficient of the pantograph material. Without regard to the mass of spring damping model(MLSD), the paper conducted a kinetic analysis for the high speed railway pantograph equipment. Besides,based on the Winkler calculation model for elasticity,this passage discretizes the problem of catenary system. Finally, the optimized time and cost for maintenance is decided by predicting the abrasion loss in contact strips.(5) Based on the real-time reliability theory, the passage constructs the evaluation model for high speed railway tractive power supply equipment, by which the lowering degree of equipment reliability could be detected. By using the data detecting model of high speed railway breakdowns in time sequence, decreasing tendency for reliability is predicted on the foundation of echo state network, the results of prediction could be the reference for conducting the condition-based maintenance of the high speed railway tractive power supply system. |
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