基于拓扑动力系统的复杂机械系统故障信息特征提取

发布时间：2019-01-03 11:16

【摘要】：随着现代工业和科学技术的快速发展以及自动化程度的进一步提高，机械系统结构日趋复杂化，因此对复杂机械系统故障诊断的要求也越来越高。而故障信息的特征提取是系统故障诊断的重要部分，国内外学者研究了多种特征提取方法，解决了复杂机械系统故障诊断的一些问题，但还有许多问题值得探讨和研究。本文在拓扑学和拓扑动力系统的基础上，，对复杂机械系统故障信息的特征提取问题进行了研究，具体的内容包括：首先，本文在拓扑学和拓扑动力系统的理论基础上，构建了复杂机械系统状态特征信息拓扑空间，描述系统的拓扑动力系统模型，实现对系统特征的描述，为系统的故障信息特征提取奠定基础。其次，通过研究拓扑动力系统轨道的性质来分析系统的特性，进而实现对系统的特征提取。将系统的轨道符号化，用符号序列的方式描述系统的轨道信息，通过分析符号序列的复杂度，计算符号序列的符号熵即拓扑动力系统的拓扑熵，来识别系统的振动状态，拓扑熵即为系统的故障特征量。并把基于拓扑动力系统的复杂机械系统故障信息特征提取方法应用于旋转机械系统故障特征提取问题中，通过仿真模拟，验证了所提出的理论方法的可行性。最后，对旋转实验平台进行故障诊断实验，通过对实测信号进行特征提取分析，实现了系统不同运行状态的有效识别，从而验证了所提出的基于拓扑动力系统的故障信息特征提取方法的有效性。
[Abstract]:With the rapid development of modern industry, science and technology and the further improvement of automation, the structure of mechanical system is becoming more and more complicated, so the requirement of fault diagnosis of complex mechanical system is more and more high. The feature extraction of fault information is an important part of system fault diagnosis. Scholars at home and abroad have studied a variety of feature extraction methods to solve some problems in fault diagnosis of complex mechanical systems, but there are still many problems worth discussing and studying. On the basis of topology and topological dynamical system, this paper studies the feature extraction of fault information of complex mechanical system. The specific contents are as follows: firstly, based on the theory of topology and topological dynamic system, The topological space of state feature information of complex mechanical system is constructed, and the topological dynamic system model of the system is described. The description of the system features is realized, which lays a foundation for the feature extraction of fault information of the system. Secondly, by studying the properties of the topological dynamical system orbit, the characteristics of the system are analyzed, and the feature extraction of the system is realized. The orbit of the system is symbolized, and the orbit information of the system is described by the symbol sequence. By analyzing the complexity of the symbol sequence, the symbol entropy of the symbol sequence is calculated, that is, the topological entropy of the topological dynamic system, to identify the vibration state of the system. Topological entropy is the fault characteristic quantity of the system. The fault information feature extraction method of complex mechanical system based on topological dynamic system is applied to the fault feature extraction of rotating machinery system. The feasibility of the proposed method is verified by simulation. Finally, the fault diagnosis experiment is carried out on the rotating experimental platform. Through the feature extraction and analysis of the measured signals, the effective recognition of the different running states of the system is realized. Thus, the effectiveness of the proposed fault information feature extraction method based on topological dynamic system is verified.
【学位授予单位】：燕山大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：TH165.3

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