Maglev Train Fault Diagnosis Technology

The dissertation does research on the features, theories, methods and realizations of fault diagnosis technology for the maglev trains by the numbers, based on being acquainted with the structure and theory of the maglev train, which is linking to the background of the material applied projects. It puts the emphasis on the four technology problems on fault diagnosis for the maglev trains, which is waiting for improvement in the field in homeland today, such as the problem to fault diagnosis to key subsystems, the problem to evaluating the train's rank of the faults, the problem to reliability analysis to the subsystem with the dynamic features, the problem to maglev train's maintenance etc.First, it diagnoses and analyses the maglev train's suspension system and traction system by applying the FTA and fuzzy FTA method. Furthermore, it presents the new way to solute the diagnosis searching arithmetic by building the searching matrix based on the factors such as components' key weightiness, faults happen probability, searching cost. Then it can get optimal searching sequence for seeking the reason to the faults. Second, it builds the train's rank evaluation model based on multiple hiberarchy neural networks, after it takes the strategy that set the component diagnosis and whole train fault rank evaluation into two steps. Third, it deeply analyses reliability of the maglev train's power system with function-correlated feature, by the method that combining the FTA with the Markov model. Finally aiming at maintenance ahead of the fault, it proposes the blue print for the maglev train's maintenance. What's more, it introduces the design and realization to recorder for the train run data in detail.All the research work in the dissertation has been simulated through MATLAB soft or test plat. And they have gotten approving effects, so they possess some value in theory and project applications.