系统故障演化过程中不同类对象分布的确定方法

doi:10.16265/j.cnki.issn1003-3033.2024.07.1863

摘要/Abstract

摘要：

为解决系统故障中不同类对象的分布确定问题,提出一种对象分布确定方法。首先,论述系统故障演化过程的特点和对象分布;其次,给出方法流程图和实现过程;最后,实例研究50个对象6个因素构成的基础数据矩阵,得到最大训练集互相关度为0.8,测试集互相关度为1,以及最优对象标签分布(对象分布)。研究结果表明:演化过程的数据基础是对象集合;方法以无监督核谱回归(UKSR)为基础,配合K-means和互信息方法,构造随机均匀分布的对象标签集合,提出最优对象标签集合的判据;通过循环确定对象标签与对象数据相关性最大时的最优对象标签集合;集合中标签值即为最优的对象分布情况;方法克服无监督学习和非线性映射等问题,且能在无监督且非线性条件下,对系统故障演化过程中测量得到的对象进行分类,分析所有对象的类标签随演化时间的分布情况,缺点是只能用于研究二维平面表示的系统故障演化过程。

关键词: 系统故障演化, 对象分布, 确定方法, 无监督核谱回归(UKSR), K-means, 互信息

Abstract:

In order to solve the problem of determining the distribution of different types of objects in system faults, a method to determine the distribution of objects was proposed. Firstly, the characteristics of the system fault evolution process and object distribution were discussed. Secondly, the method flow chart and implementation process were given. Finally, an example was analyzed. The example studied the basic data matrix composed of 6 factors and 50 objects, and the maximum training set cross-correlation was 0.8, the test set cross-correlation was 1, and the optimal object label distribution (object distribution) was obtained. Finally, the advantages and disadvantages of the method were described. The analysis shows that the database for studying the evolution process is the object set. Methods based on UKSR, combined with K-means and mutual information methods, a randomly distributed object label set is constructed, and the criteria for the optimal object label set are proposed. The optimal object label set is determined through a loop when the correlation between object labels and object data is the largest. The label value of objects in the set is the optimal object distribution. The method overcomes the problem of unsupervised learning and nonlinear mapping. It is concluded that the method can classify the measured objects in the system fault evolution process under unsupervised and nonlinear conditions, and the distribution of class labels of all objects with evolution time. The disadvantage is that it can only be used to study the system fault evolution process represented by two-dimensional.

Key words: system fault evolution, object distribution, determination method, unsupervised kernel spectral regression, K-means, mutual information

中图分类号:

X913安全系统学

李莎莎, 崔铁军. 系统故障演化过程中不同类对象分布的确定方法[J]. 中国安全科学学报, 2024, 34(7): 1-7.

LI Shasha, CUI Tiejun. A method to determine distribution of different class objects in process of system fault evolution[J]. China Safety Science Journal, 2024, 34(7): 1-7.

图/表 4

图1

图2

表1

基础数据矩阵

Γ_MⅹN	O₁	O₂	…			O_n
f₁	$x 11$	$x 12$	…			$x N 1$
︙	︙	︙	…		…	︙
				$x m n$
			…		…
f_M	$x M 1$	$x M 2$		…		$x M N$

表1

图3

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