适于系统非稳定工况的故障检测与分类诊断方法研究

系统在起动、制动以及运动过程突变等状态下的工作状况称为非稳定工况。由于非稳定工况下故障率相对较高，监测困难，相关的技术研究也日益受到关注。在系统非稳定工况下，由于变量多、变化幅度大、响应速度快、变量间相关性关系复杂等，特别是当系统运动方程未知，又得不到专家系统的知识援助时，无法建立定量模型。并且稳定工况的方法难以对系统非稳定工况进行有效的检测和诊断。.因此，课题组拟从海量信息中获得知识的思路出发，开展适于系统非稳定工况的故障检测和分类诊断方法的研究:1)归纳演绎系统非稳定工况的特征属性和普适性规律；2)建立传统方法在系统非稳定工况的故障检测控制限，进而研究新的检测方法；3)引入有效主元的思想，根据系统非稳定工况的特征属性和规律，结合时空聚类分析方法，研究非稳定工况的故障分类诊断方法。该项研究的开展，将为系统非稳定工况的应用研究提供理论依据和部分参考数据，对于知识发现领域也有一定的积极意义。

The non-steady condition refers to such working conditions as the system is not working steadily during the startup, braking and the mutations of other movement processes. Actually, the failure operations of the system under the non-steady condition is relatively higher than the system under the steady condition, especially when it is difficult to monitor the system under the non-steady condition and when the expertise help is not timely and handy. Consequently, this has already caught much attention of the researchers in this field.. There are mass variables, great changes of the variables in amplitude, higher response speed, more complex correlation relationship among many variables in the system under the non-steady condition. The quantitative model could not be established without the equation of motion or the assistance from expert system under the non-steady condition in particular. Furthermore, the methods for fault detection and diagnosis under the steady condition could barely be detected effectively with the consideration of the system under the non-steady condition. Therefore, the program intends to discovery useful knowledge in database first, and then to find research methods applicable for the fault detection and classification of the diagnosis of the system under the non-steady condition: .1).To induce and deduce the feature attributes and universal laws of the system under the non-steady condition;.2).To build the new fault detection limit suitable for the system under the non-steady condition according to the traditional methods, and then propose some new fault detection methods; .3).To introduce the idea of the Effective Principal Component, and combining with the spatial and temporal clustering analysis methods to develop the failure diagnosis methods according to the characteristic properties and laws of the non-steady condition under the non-steady condition. .The research achievements of this program will provide a theoretical basis and some reference data for the application research of the system under the non-steady condition, and therefore it possess some positive significance for the KDD (Knowledge Discovery in Database) field.