Semiquantitative SDG Graphical Modeling for Complex System Fault Diagnosis

2012 ◽  
Vol 152-154 ◽  
pp. 1601-1606 ◽  
Author(s):  
Yan Su
Keyword(s):  
Complex System ◽  
Fault Diagnosis ◽  
Failure Analysis ◽  
Supply System ◽  
Data Driven ◽  
Graphical Modeling ◽  
Modeling Methods ◽  
Modeling Approach ◽  
Modeling Process ◽  
Air Supply

For the shortcomings of existing SDG modeling methods in fault diagnosis, a data-driven semi-quantitative SDG automatic graphical modeling approach and a direct manual SDG graphical modeling approach are investigated. Function failure analysis procedures and data modeling process based on system principle are introduced in detail, and relevant graphical modeling tool are developed. A fault diagnosis modeling for the air supply system of certain type of aircraft is taken as an illustration to verify the validity of proposed modeling method.

Data-driven reconstruction of interpretable model for air supply system of proton exchange membrane fuel cell

2021 ◽  
Vol 299 ◽  
pp. 117266
Author(s):  
Zhihua Deng ◽  
Qihong Chen ◽  
Liyan Zhang ◽  
Keliang Zhou ◽  
Yi Zong ◽  
...  
Keyword(s):  
Fuel Cell ◽  
Proton Exchange Membrane ◽  
Supply System ◽  
Proton Exchange ◽  
Data Driven ◽  
Air Supply ◽  
Interpretable Model ◽  
Exchange Membrane

Diagnostic Fault Simulation for the Failure Analyst

2004 ◽  
Author(s):  
Dan Bodoh ◽  
Anthony Blakely ◽  
Terry Garyet
Keyword(s):  
Fault Diagnosis ◽  
Failure Analysis ◽  
Complete Solution ◽  
Fault Simulation ◽  
Building Blocks ◽  
Physical World ◽  
Design For Test ◽  
Fault Diagnosis System ◽  
Diagnosis Algorithm ◽  
Diagnosis Tool

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.

Data-driven fault diagnosis of FW-UAVs with consideration of multiple operation conditions

2021 ◽  
Author(s):  
Shaojun Liang ◽  
Shirong Zhang ◽  
Yuping Huang ◽  
Xing Zheng ◽  
Jian Cheng ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Data Driven ◽  
Operation Conditions ◽  
Multiple Operation

Data-Driven Modeling Approach to Predict the Recovery Performance of Low-Salinity Waterfloods

2021 ◽  
Author(s):  
Shams Kalam ◽  
Rizwan Ahmed Khan ◽  
Shahnawaz Khan ◽  
Muhammad Faizan ◽  
Muhammad Amin ◽  
...  
Keyword(s):  
Data Driven ◽  
Low Salinity ◽  
Modeling Approach ◽  
Recovery Performance ◽  
Data Driven Modeling

scholarly journals From SIR to SEAIRD: A novel data-driven modeling approach based on the Grey-box System Theory to predict the dynamics of COVID-19

2021 ◽  
Author(s):  
K. Midzodzi Pekpe ◽  
Djamel Zitouni ◽  
Gilles Gasso ◽  
Wajdi Dhifli ◽  
Benjamin C. Guinhouya
Keyword(s):  
System Theory ◽  
Data Driven ◽  
Modeling Approach ◽  
Data Driven Modeling

Application of data-driven methods for energy system modelling demonstrated on an adaptive cooling supply system

Energy ◽  
2021 ◽  
pp. 120894
Author(s):  
Thomas Schreiber ◽  
Christoph Netsch ◽  
Sören Eschweiler ◽  
Tianyuan Wang ◽  
Thomas Storek ◽  
...  
Keyword(s):  
Energy System ◽  
Supply System ◽  
Data Driven ◽  
System Modelling

scholarly journals Modeling Human Factors Topics in Aviation Reports

2019 ◽  
Vol 63 (1) ◽  
pp. 126-130
Author(s):  
Beth Lyall-Wilson ◽  
Nicolas Kim ◽  
Elizabeth Hohman
Keyword(s):  
Human Factors ◽  
Topic Modeling ◽  
Domain Knowledge ◽  
Aviation Safety ◽  
Subject Matter Experts ◽  
Text Data ◽  
Modeling Approach ◽  
Modeling Process ◽  
Manual Review ◽  
Initial Extraction

This paper describes the development and new application of a text modeling process for identifying human factors topics, such as fatigue, workload, and distraction in aviation safety reports. Current approaches to identifying human factors topic representations in text data rely on manual review from subject matter experts. The implementation of a semi-supervised text modeling method overcomes the need for lengthy manual review through an initial extraction of pre-defined human factors topics, freeing time for focus on analyzing the information. This modeling approach allows analysts to use keywords to define topics of interest up front and influence the convergence of the model toward a result that reflects them, which provides an advantage over classic topic modeling approaches where domain knowledge is not integrated into the generation of derived topics. This paper includes a description of the modeling approach and rationale, data used, evaluation methods, challenges, and suggestions for future applications.

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