故障诊断论文基于聚类分析的卫星姿态控制系统故障诊断方法研究.doc

故障诊断论文：基于聚类分析的卫星姿态控制系统故障诊断方法研究【中文摘要】应用于卫星系统的故障诊断技术是确保卫星系统正常工作必不可少的一项关键技术,它不仅让卫星系统具有智能化修复功能,而且其诊断经验可以优化卫星系统观测点的分布。随着卫星系统越来越复杂与智能化,卫星故障诊断的能力在未来卫星技术发展中变得突出重要,并不断向更高水平发展。现代卫星系统的复杂化,使得基于模的故障诊断方法建模难度大、灵活性差,导致基于模型的方法很难取得较好的故障诊断结果。由于基于聚类分析的故障诊断方法利用历史数据进行建模,不需要实际的物理结构模型,它能够克服基于模型的诊断方法的缺点。本论文采用基于聚类分析的故障诊断方法,开发和利用卫星监控系统所采集的历史数据。论文的研究内容主要包括以下几个方面:首先,研究基于聚类分析的数据分布特征提取方法的特点,学习聚类分析的两种算法,利用聚类算法分析拟合数据与异常数据,设计拟合数据与异常数据的差值模型,初步建立基于聚类分析的故障诊断模型。其次,对标准的飞机控制系统模型进行数值仿真,获取该模型的健康数据和故障数据,采用基于聚类分析的诊断方法进行故障诊断,依据诊断结果来完善该故障诊断模型的建模与诊断推理步骤。再次,结合卫星姿态控制系统的结构,对主要部件的数学模型做了详细分析,并研究飞轮摩擦力矩对姿态角控制效果的影响。建立卫星姿态控制系统的外在干扰力与力矩的数学模型,针对系统的执行部件与测量部件,设置了不同的故障模式并建立相应的数学模型。最后,根据卫星姿态控制系统部件的几种典型的故障模式,建立相应的simulink仿真模型,设置卫星姿态控制系统仿真参数与设定该系统的状态观测点,对这几种仿真模型进行数值仿真模拟并采集系统的健康数据与故障数据。利用聚类分析的方法对该姿态控制系统进行故障诊断。【英文摘要】The Fault Diagnosis Technique (FDT) applied to satellite systems is a special technique adopted to ensure the proper functions of the systems. It can not only realize the intelligent repaire, but the diagnosis experiences can also optimize the observation points of the satellite systems. With the developing tendency of more complex and intelligent of satellite systems, FDT plays a more important role and is pushed to reach a higher level.Because of the complexity of the modern satellite systems, the model-based FDT, which has a complicated modeling process and poor flexibility, can not always obtain a good result of fault diagnosis; while the cluster-analysis-based on history process data FDT (CBHD-FDT), which makes use of historical data and does not need the physical structure of systems, can overcome those short comings. Therefore, the research in this paper is using the CBHD-FDT, and exploring and applying the historical data gathered by the satellite monitering system. The main content of this research is as follows:Firstly, the characteristics of the extraction method into the data distrubuted features of CBHD-FDT are taken into deep research. Then two kinds cluster analysis algorithms are studied, using which the expected fitting data and the actual abnormal data are analyzed, a variance model is built, and the initial CBHD-FDT model is established.Then, the numerical simulation is performed on a standard aircraft control system, from which both the healthy and faulty data are obtained. Further, CBHD-FDT is applied to diagnose this system, based on the results of which, the modeling process and diagnosis reasoning steps can be improved.Whats more, combined with the actural structure of the satellite attitude controling system, the mathematical models of the main components are analyzed in details, with the influence of the flywheel friction torque on the attitude angle controling effects. The analytical models of the external disturbance forces and torques loading on the satellite attitude controling system are established. In addition, in view of specific operating and measuring components, the corresponding mathematical models are set under different faulure modes.Finally, based on several typical failure modes of a satellite attitude controling system, after the parameters of the simulation models and the state-observation points of the system are set, the simulation model is to be built in SIMULINK. From the running of the simulation, both healthy and faulty data of the system can be gathered, and CBHD-FDT is applied to perform the fault diagnosis of this controling system.【关键词】故障诊断 控制系统仿真 历史数据 聚类分析【英文关键词】fault diagnosis simulation of controling system historical data cluster analysis【目录】基于聚类分析的卫星姿态控制系统故障诊断方法研究摘要4-5ABSTRACT5第1章 绪论8-201.1 课题背景和意义8-91.2 故障诊断技术国内外进展9-171.2.1 基于定性模型的故障诊断方法10-121.2.2 基于定量模型的故障诊断方法12-131.2.3 基于历史数据的故障诊断方法13-141.2.4 基于历史数据的定量模型故障诊断方法14-171.3 发展趋势17-181.4 本文工作总结18-20第2章 基于聚类分析的故障诊断方法20-332.1 引言202.2 聚类算法的选取标准20-222.2.1 聚类算法可行性212.2.2 聚类质量评估21-222.3 聚类分析的数据结构和数据类型22-242.3.1 聚类分析的数据结构22-232.3.2 聚类分析的数据类型23-242.4 聚类算法模型建立24-262.4.1 基于划分的方法24-252.4.2 基于密度的方法252.4.3 两种方法的比较25-262.5 建立基于聚类分析的故障诊断模型26-322.5.1 健康状态的聚类学习28-302.5.2 系统异常状态监测30-322.6 本章小结32-33第3章 基于聚类分析的控制系统故障诊断33-463.1 引言333.2 数据矢量的属性对异常检测结果的影响33-403.2.1 输入为常值时34-363.2.2 输入为正弦波时36-383.2.3 输入为方波时38-403.3 健康数据的选择对故障检测结果的影响40-433.3.1 输入为常值40-413.3.2 输入为方波41-423.3.3 输入为正弦波42-433.4 基于聚类算法的复合故障检测43-443.5 本章小结44-46第4章 卫星姿态控制系统仿真模型的建立46-574.1 引言464.2 数学模型46-554.2.1 卫星姿态控制系统的数学模型46-534.2.2 空间环境力与力矩53-