Combination of Techniques for the Fault Diagnostics

被引：0

作者：

Trnka, Pavel ^{[1
]}

Hofreiter, Milan

Sova, Jan ^{[2
]}

机构：

[1] Czech Tech Univ, Fac Mech Engn, Dept Instrumentat & Control Engn, Tech 4, Prague 6, Czech Republic

[2] Workswell Sro, Libocka 653-51b, Prague 6, Czech Republic

来源：

2017 18TH INTERNATIONAL CARPATHIAN CONTROL CONFERENCE (ICCC) | 2017年

关键词：

fault diagnostics; fault detection and isolation; FDI; Markov model; Empirical Mode Decomposition; EMD; Intrinsic Modal Function; IMF;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Each autonomous technological process requires an early fault detection system as an integral part of its infrastructure. Complex fault diagnostics system must be able not only to quickly detect any unwanted deviation from nominal function, but also to make a competent estimate of the type and source of possible failure. The article presents the fault diagnostics system based on Markov model. It uses an innovative dynamically oriented classifier of fault states. The other enhancement represents the regression vector used in the diagnostics system which combines directly measured process data with their components obtained using Empirical Mode Decomposition (EMD).

引用

页码：499 / 502

页数：4