机电装备信号系统故障诊断自愈的应用研究  

Research on Application of Mechanical and Electrical Equipment Fault Diagnosis Signal of the Self- Healing System

作　　者：张政[1] 袁宇浩[1] 简丹丹[1] 

机构地区：[1]南京工业大学自动化与电气工程学院,江苏南京211816

出　　处：《计算机仿真》2015年第4期450-454,共5页Computer Simulation

基　　金：国家自然科学基金(51205185)

摘　　要：在机电装备的信号调理系统的故障自愈研究中,针对传统的机电装备信号调理系统故障诊断中存在故障检测器检测率低等问题,不适合故障诊断以及自愈研究。为了提高故障检测器对故障的检测率,对传统阴性选择算法存在问题的修改,提出改进的阴性选择算法的方法,通过对传统的阴性选择算法算子的优化对传统的阴性选择算法进行改进,对故障检测率明显提高。通过对改进的阴性选择算法的仿真,仿真结果验证了改进的阴性选择可以具有更好的信号调理系统故障识别性能。In the signal conditioning of electromechanical equipment fault self recovery system, the traditional negative selection algorithm in fault diagnosis system for electromeehanieal equipment of signal conditioning problems in fault detection rate for low, not suitable for fault diagnosis and self - healing research. In order to improve the fault detection rate, and traditional negative selection algorithm problems modification, improved negative selection algorithm. Methods selection operator on the traditional optimization negative selection algorithm was improved by negative to the traditional, the fault detection rate. Through the simulation of the improved negative selection algorithm, simulation results verify that the improved negative selection can have a better signal conditioning system fault recognition performance.

关 键 词：机电装备系统 自愈 免疫系统 阴性选择算法 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构] TP391.9[自动化与计算机技术—计算机科学与技术]