A VHDL fault diagnosis tool using functional fault models

1992 ◽  
Vol 9 (2) ◽  
pp. 33-41 ◽  
Author(s):  
V. Pitchumani ◽  
P. Mayor ◽  
N. Radia
Author(s):  
Dan Bodoh ◽  
Anthony Blakely ◽  
Terry Garyet

Abstract Since failure analysis (FA) tools originated in the design-for-test (DFT) realm, most have abstractions that reflect a designer's viewpoint. These abstractions prevent easy application of diagnosis results in the physical world of the FA lab. This article presents a fault diagnosis system, DFS/FA, which bridges the DFT and FA worlds. First, it describes the motivation for building DFS/FA and how it is an improvement over off-the-shelf tools and explains the DFS/FA building blocks on which the diagnosis tool depends. The article then discusses the diagnosis algorithm in detail and provides an overview of some of the supporting tools that make DFS/FA a complete solution for FA. It also presents a FA example where DFS/FA has been applied. The example demonstrates how the consideration of physical proximity improves the accuracy without sacrificing precision.


2012 ◽  
Vol 466-467 ◽  
pp. 1186-1190
Author(s):  
Jun Bin Cao ◽  
Er Min Guo ◽  
Yan Li

In order to diagnose and exempt the fault of aircraft electrical system accurately and fast, on the basis of analyzing the lost mode and fault mechanism of certain aircraft electrical system, fault structure are built and structure are built and fault models are analyzed by adopting the analytical technology based on regular fault structure. Two induction mechanisms, namely directional and anti-directional inference are introduced and the component methods are studied based on the knowledge corpus of data corpus technique. The result shows the inference results of fault diagnosis system are in accordance to reality and improve the intelligentized level of fault diagnosis system for aircraft electrical power.


2014 ◽  
Vol 1014 ◽  
pp. 505-509 ◽  
Author(s):  
Ran Tao ◽  
You Cai Xu ◽  
Xin Shi Li ◽  
Shu Guo ◽  
Kun Li ◽  
...  

Empirical mode decomposition (EMD) can extract real time-frequency characteristics from the non-stationary and nonlinear signal. Variable prediction model based class discriminate (VPMCD) is introduced into roller bearing fault diagnosis in this paper. Therefore, a fault diagnosis method based on EMD and VPMCD is put forward in the paper. Firstly, the different feature vectors in the signal are extracted by EMD. Then, different fault models of roller bearing are distinguished by using VPMCD. Finally, an simulation example based on EMD and VPMCD is shown in this paper. The results show that this method can gain very stable classification performance and good computational efficiency.


1996 ◽  
Vol 33 (3) ◽  
pp. 225-238
Author(s):  
C. Garrett ◽  
L. Maikowski ◽  
R. Thomas

Automating the diagnosis of analogue circuits–a tutorial A tutorial study of automatic analogue fault diagnosis is presented. Major issues, namely observability, controllability and deduction are explained but then issues of tolerance and fault models peculiar to diagnosis of faults in analogue systems are discussed. A taxonomy of methods is followed by examples and 25 references.


Author(s):  
Joachim Baehr ◽  
Rolf Isermann

A fault diagnosis method for a three mass torsion oscillator is considered which is subject to different additive faults. By using a bank of fault models three faults of different type are detected, isolated and identified in size and time of occurrence. The bank of fault models is formed by a model of each considered fault. Comparison of simulated fault model outputs and measured signals leads to fault isolation. Fault size and time of occurrence are identified by a parity equation approach and used as fault model parameters. The method is capable to perform the tasks with use of one actuator and one sensor signal. It is shown that common approaches for fault isolation can not be used due to the small number of measured signals.


2012 ◽  
Vol 22 ◽  
pp. 203-211 ◽  
Author(s):  
Haitao Wang ◽  
Youming Chen ◽  
Cary W.H. Chan ◽  
Jianying Qin

2001 ◽  
Vol 18 (1) ◽  
pp. 19-30 ◽  
Author(s):  
S. Venkataraman ◽  
S.B. Drummonds

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