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基于BP神经网络的列车零部件故障诊断研究

Acknowledgement第5-6页
摘要第6-10页
Abstract第10-14页
Preface第15-18页
1 Introduction第18-23页
    1.1 Research Background and Current Status Quo第18-20页
    1.2 The significance of the research第20-21页
    1.3 The main work of this paper第21页
    1.4 The structure of the thesis第21-23页
2 The Working Principle and Fault Analysis of Traction Converter第23-28页
    2.1 The circuit structure and working principle of traction converter第23-25页
        2.1.1 The circuit structure第23-24页
        2.1.2 The working principle of traction converter第24-25页
    2.2 Fault model of traction converter第25-27页
    2.3 Fault Feature Extraction of Traction Converter第27页
    2.4 Chapter Summary第27-28页
3 The Neural Network Theory第28-36页
    3.1 Introduction to Neural Networks第28-30页
    3.2 The principle and algorithm of BP neural networks第30-35页
        3.2.1 The basic principle of BP neural network第30-32页
        3.2.2 Program implementation of BP algorithm第32-33页
        3.2.3 The Importance of Neural Network in Fault diagnosis第33-35页
    3.3 Chapter Summary第35-36页
4 Spark Parallelization of BP Neural Network第36-44页
    4.1 Hadoop Framework第36-38页
    4.2 Spark Framework第38-41页
        4.2.1 Spark Ecosystem第38-40页
        4.2.2 Spark Architecture第40-41页
    4.3 Spark parallel method for BP Neural Network algorithm第41-43页
    4.4 Chapter Summary第43-44页
5 The Application of Spark based BP neural network algorithm in fault diagnosisof traction converter第44-53页
    5.1 Fault mode of the converter第44-45页
    5.2 Fault feature parameters and design of learning samples第45-47页
    5.3 Design of BP neural network based on Spark第47-49页
    5.4 Implementation and Testing of fault neural network based on Spark parallelmethod第49-51页
        5.4.1 The realization of fault diagnosis neural network第49页
        5.4.2 The testing of fault diagnosis neural network第49-51页
    5.5 Chapter Summary第51-53页
6 Summary and Prospects第53-54页
References第54-56页
Author Profile and Research Achievements Obtained during the Study for AMaster's Degree第56-58页
Data for the Master's Thesis第58-59页

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