基于非参数统计检验的早期故障检测与诊断研究

项目名称： 基于非参数统计检验的早期故障检测与诊断研究

项目编号： No.61203088

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 自动化学科

项目作者： 曾九孙

作者单位： 中国计量学院

项目金额： 26万元

中文摘要： 早期故障的检测和诊断对设备和过程的安全具有重要意义，从统计角度看，早期故障在数据中的表现形式可分为：一阶统计量变化、二阶统计量变化和高阶统计量变化等。本项目针对以上故障类型，提出一套基于非参数统计检验的早期故障检测和诊断方法。首先将待测样本划分为固定长度的子集，将单样本检验问题转化为分布检验问题，具体包括：基于经验似然的故障检测方法，适用于检测一阶统计量的变化；对二阶统计量变化的早期故障，拟利用核均值偏差检验，将样本投影到核空间，比较其均值偏差，实现检测和诊断的目的；为比较正常样本与待测样本的概率分布，设计基于KL距离的早期故障检测与诊断方法。并将研究方法应用于高炉冶炼等冶金和化工过程。基于非参数统计检验的早期故障检测和诊断方法不依赖于任何分布假设，对微小、缓变的早期故障具有更高的灵敏度。项目的研究成果将有助于提高冶金和化工等生产过程的产品质量和控制性能，具有重要的理论和应用价值。

中文关键词： 故障诊断；非参数分布检验；经验似然；核均值偏差；Kullback-Leibler距离

英文摘要： Incipient fault detection and diagnosis is of great significance to the safety of equipment and industrial process. From the aspect of statistics, the influence of incipient fault to data can be divided into three categories, i.e., change in first order, second order and higher order statistics. To deal with the three kinds of incipient faults, this project proposes a fault detection and diagnosis framework based on nonparametric statistical test. The basis idea is to transform the single sample monitoring problem into distribution test between normal sample set and subset of test samples. The following aspects are considered: i) A fault monitoring strategy based on empirical likelihood is proposed to detect change in the first order statistic; ii)By projecting the normal data set and the test subset into a kernel space, the kernel mean discrepancy method uses the discrepancy between mean values of both sets in the kernel space as a test statistic; based on this statistic, a fault monitoring and diagnosis strategy to detect change in second order statistic is proposed. iii)To measure the difference between the probability density distributions of normal data set and test subset, a fault detection and diagnosis scheme is proposed using Kullback-Leibler divergence (KL divergence). The developed methods are then a

英文关键词： fault diagnosis；nonparametric distribution test；empirical likelihood；kernel mean descrepancy；Kullback-Leibler divergence