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Research of Method on Faults Diagnosis of Axial Fan in the Environment Control System of Metro

Author: YouLiJing
Tutor: ChenZaiPing；LinZhiLing
School: Tianjin University of Technology
Course: Pattern Recognition and Intelligent Systems
Keywords: Axial Fan Faults Diagnosis Virtual PrototypingTechnology Neural Network
CLC: TH432.1
Type: Master's thesis
Year: 2010
Downloads: 43
Quote: 0
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Abstract


With the rapid development of China’s economy, the railway system has become more and more important to our daily life. The metro is very important for a city or a region in social and economic life. As the Metro is under the ground, the ventilation is carried out by the axial fan. So the research of fault diagnosis of the axial fan, which is the important mechanical and electrical equipment in the MTR system, is of great significance. Axial fan belongs to the rotating machine, then using its vibration signal as the characteristic signal of fault diagnosis. In this paper, the works have benn done in the following areas:1) Combined the working principle of axial fan, do the research of the mechanism of the common faults of the axial fan, such as rotor imbalance, shaft misalignment, connection pieces loose, leaves breakdown and so on. Then summarize the vibration characteristics of the common faults of the axial fans.2) For the fault samples of axial fan in the metro are difficult to obtain, this paper presents a new approach—simulate the faults based on virtual prototype. Build the model of the axial fan in the PRO/ENGINEER software, import the model into the dynamic simulation software ADAMS through the professional interface of MECHANISM/Pro,carry out fault simulation of axial fan in the ADAMS, extract the fault data of the axial fan at last.3) Study the method on fault diagnosis of axial fan based on BP neural network and SOM neural network, set up the network model of the two kinds, then train them, and demonstrate the correctness of the method throuth the example.At the end of the paper, the fault data, which is obtained by fault simulation in the ADAMS, is ueds as the input of the neural network, and do the intelligent fault diagnosis in MATLAB software and get the finally experiment results, through the analysis of experiment results verify the feasibility and accuracy of the program topics.This paper based on virtual prototyping technology and neural network technology achieved the fault diagnosis of the axial fan in the Metro. The simulation experiments of axial fan verify the feasibility and accuracy of the method, also provide an important basis for the feasibility study of the virtual prototype in rotating machinery fault diagnosis. While the SOM neural network achieved axial fan fault diagnosis, which greatly expands the application of neural network in pattern recognition and classification.

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CLC: > Industrial Technology > Machinery and Instrument Industry > Gas compression and transportation machinery > Fan > Centrifugal ( radial flow ) > Axial
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