故障軸承振動(dòng)特性分析與典型故障診斷
[Abstract]:Rolling bearing is one of the mechanical parts which are widely used and easy to be damaged in various rotating machinery. Its running state often directly affects the performance of the whole machine. Reliable fault diagnosis of rolling bearings can find faults in time, and can effectively avoid serious accidents such as machine damage and casualties. Especially in rolling machinery, rolling bearing is a very important part, so it is of practical significance to study the fault diagnosis of rolling bearing. Using the electric spark to destroy the rolling bearing is used to simulate the bearing fault, and the simulation fault is used to replace the actual fault to carry on the experiment research. A rolling bearing fault test platform is set up and vibration signals are collected on the platform for experimental research. In this paper, the fault mechanism and vibration characteristics of rolling bearings are analyzed firstly, and the periodic shock and amplitude modulation characteristics of local damage vibration signals of rolling bearings are summarized. Then, in order to extract the fault feature of rolling bearing effectively, a fault feature extraction method based on the combination of empirical mode decomposition method and independent component analysis method is proposed, which is applied to the practical data processing and analysis of rolling bearing experiment. It is shown that the fault characteristics of rolling bearing can be extracted accurately. Secondly, the theory of support vector machine is studied systematically, and the genetic algorithm based on cross-validation is proposed to optimize the penalty parameter C and Gao Si kernel parameter 緯 in support vector machine, which ensures the optimality of classification model. Finally, the singular value of the separation matrix is used as the fault characteristic vector of rolling bearing. Through the vibration experiment of the rolling bearing and the collection of data, the method is proved to be effective in identifying the fault types. The intelligent fault diagnosis system platform of rolling bearing is developed by means of MATLAB and LabVIEW. The platform has a friendly interface and is easy to operate, and the performance of the diagnosis system is proved to be good by simulating the vibration tests of typical faults of rolling bearings on the rolling bearing test stand.
【學(xué)位授予單位】:燕山大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2012
【分類號(hào)】:TH165.3
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