EMU bogie bearing reliability analysis and fault diagnosis technology research
|School||Central South University|
|Course||Transport equipment and Information Engineering|
|Keywords||EMU bogie bearings Reliability Analysis EMD BP neural network Improved Genetic Algorithm|
EMU efficient means of transport to small groups , large density intercity and suburban railway . Bogie is a high-speed the EMU running gear , decided to train operators speed and running quality . EMU bogie bearings working conditions affecting the safety of railway transport one of the important factors to carry out EMU bogie bearing reliability analysis and fault diagnosis , to ensure the safety of the operators , improve maintenance efficiency and avoiding unnecessary losses have important significance . In this paper, the fault tree analysis method to establish the EMU bogie bearing failure model , and improve its reliability requirements , and a brief introduction EMU Bogie bearing vibration mechanism , fault characteristic frequency . Bearing fault monitoring technologies , vibration monitoring techniques to monitor EMU bogie bearings , and in-depth study of more advanced theories and methods in the field of fault diagnosis . In this paper, two methods of bearing failure diagnosis and monitoring . A time-frequency domain parameters of diagnostic methods , another method is : intelligent diagnostic method , the first vibration signal wavelet packet denoising improve its signal-to-noise ratio , and then based on EMD ( Empirical Mode Decomposition ) method to extract energy characteristics of bearing failure , the fault signal is decomposed to the IMF, the analysis of several important IMF , each IMF component , as BP neural network input vector ; based on genetic algorithm optimization characteristics , combined with improved genetic algorithm BP optimize parameters of the neural network , and then use its bearing failure diagnosis, analysis of the effect of this method diagnosis . The system is based on software as the core of the virtual instrument development , so that the system has scalability , flexible definition , high performance and low maintenance cost advantages . System software development process platform using LabWindows / CVI. Experiment confirmed EMU bogie bearing fault diagnosis system can accurately predict its failure to provide reasonable maintenance recommendations .