Research On Signal Processing Technique For Suspension System Of Mid-Low Speed PEMS Maglev Train

Permanent magnetic & electromagnetic suspension maglev train adds permanent magnet into electric magnet, thus the energy consumption is effectively reduced and heat emission is declined. The addition of permanent magnet makes suspension control increasingly difficult, and raises the requirement for system security. Taking permanent magnetic & electromagnetic suspension system as the investigated object, this paper develops the study on filtering and fault diagnosis problems. The main contents of this paper are as follows:1. The model of permanent magnetic & electromagnetic suspension module is established and a control law is designed for the module. The effects of sensor noise and sensor failure are simulated and the problems to be solved are proposed.2. Characteristics of gap sensor signals and accelerator signals are studied and a “Simple Discrete Second-Order Nonlinear Tracking-Differentiator Based on Boundary Characteristic Curves” is introduced to design gap signal filter, accelerator signal filter and gap signal differentiator. The effectiveness of filters and differentiator are tested through simulations and experiments on a small maglev experiment platform.3. A fault diagnosis method for accelerator is proposed based on the redundancy of signal acquisition, and a fault diagnosis method for current sensor is proposed based on the property that current in electromagnetic coil can't change abruptly.4. The signal processing algorithm is implemented in FPGA. Simulations and experiments are made and the results prove that the algorithm implemented in FPGA is effective.To enhance the suspension performance and raise system security, this paper studies on signal processing problems in suspension system on maglev train, and the work of this paper is of some theoretical and engineering value.