A fault tree is established based on structural analysis, working principle analysis, and failure mode and effects analysis (FMEA) of the pantograph-type current collector on the Chinese Rail High-Speed Electric Multiple Unit (CRH EMU) train. To avoid the deficiencies of fault tree analysis (FTA), Petri nets modelling is used to address the problem of data explosion and carry out dynamic diagnosis. Relational matrix analysis is used to solve the minimal cut set equation of the fault tree. Based on the established state equation of the Petri nets, initial tokens and enable-transfer algorithms are used to express the fault transfer process mathematically and improve the efficiency of fault diagnosis inferences. Finally, using a practical fault diagnosis example for the pantographs on CRH EMU trains, the proposed method is proved to be reasonable and effective.

Abstract:The management of information resource has become the key point to the large complicated system with the development of information technologies. Problems of storing pressure and reading efficiency became more serious because of data explotation and large scale of redundant data. A novel redundant data deleting algorithm based on the cloud storage plalform was proposed in this paper to deal with the problem of mess data store. Space division and role division techonlogy was used to insure the security of data sharing in the system. A novel educational administration information system was used to validate the feasibility and effectiveness of the algothrisms proposed in this paper.