scholarly journals A concept for fault diagnosis combining Case-Based Reasoning with topological system models

2020 ◽  
Vol 53 (2) ◽  
pp. 8217-8224
Author(s):  
Jonas Zinn ◽  
Birgit Vogel-Heuser ◽  
Felix Ocker
Keyword(s):  
Fault Diagnosis ◽  
Case Based Reasoning ◽  
System Models ◽  
Topological System ◽  
Case Based

Graphical Fault Diagnosis Expert System of CNC Machine Tool Based on B/S

2014 ◽  
Vol 945-949 ◽  
pp. 1707-1712
Author(s):  
Bin Shen ◽  
Shu Yu Zhao ◽  
Jia Hai Wang ◽  
Juergen Fleischer
Keyword(s):  
Fault Diagnosis ◽  
Expert System ◽  
Machine Tool ◽  
Case Based Reasoning ◽  
Cnc Machine Tool ◽  
Cnc Machine ◽  
Rule Based ◽  
Detailed Case ◽  
Case Based ◽  
Remote Fault Diagnosis

Based on the authors previous work of developing an expert system for fault diagnosis of CNC machine tool, this paper studied the theory and method of CNC remote fault diagnosis expert system based on B/S, and presents schema and structure of the expert system in detailed. Case based reasoning is used for the multi-alarm diagnosis, and rule based reasoning is used for single-alarm diagnosis. At last fault diagnosis expert system was designed and developed making use of C# and ASP.NET.

scholarly journals Text Case-Based Reasoning Framework for Fault Diagnosis and Predication by Cloud Computing

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Zhiwang Zhong ◽  
Tianhua Xu ◽  
Feng Wang ◽  
Tao Tang
Keyword(s):  
Cloud Computing ◽  
Fault Diagnosis ◽  
Rough Set ◽  
Best Practice ◽  
Discrete Event ◽  
Scale Up ◽  
Case Based Reasoning ◽  
Case Retrieval ◽  
Fault Features ◽  
Case Based

In Discrete Event System, such as railway onboard system, overwhelming volume of textual data is recorded in the form of repair verbatim collected during the fault diagnosis process. Efficient text mining of such maintenance data plays an important role in discovering the best-practice repair knowledge from millions of repair verbatims, which help to conduct accurate fault diagnosis and predication. This paper presents a text case-based reasoning framework by cloud computing, which uses the diagnosis ontology for annotating fault features recorded in the repair verbatim. The extracted fault features are further reduced by rough set theory. Finally, the case retrieval is employed to search the best-practice repair actions for fixing faulty parts. By cloud computing, rough set-based attribute reduction and case retrieval are able to scale up the Big Data records and improve the efficiency of fault diagnosis and predication. The effectiveness of the proposed method is validated through a fault diagnosis of train onboard equipment.

Research of CBR-Based Organizations on Aromourd Equipment Fault-Diagnosis

2014 ◽  
Vol 635-637 ◽  
pp. 715-721
Author(s):  
Hao Li ◽  
Yao Hui Zhang ◽  
Yi Zheng ◽  
Lin Hong Li
Keyword(s):  
Fault Diagnosis ◽  
Failure Mode ◽  
Complex Structure ◽  
Case Based Reasoning ◽  
Case Based ◽  
The Way

It is the complex structure of the armoured equipment that determines the traditional organizations of the case-warehouse cannot direct the case-based reasoning effectively. Adopting the way to analyse failure mode before the case-warehouse organizations, suming up for the classification. Building the apart index mechanism and establishing the basis of the effective organizations of the case-warehouse at last.

Application of Dynamic Data Mining and Case-Based Reasoning in the Drilling Fault Diagnosis

2012 ◽  
Vol 524-527 ◽  
pp. 1350-1354
Author(s):  
Qi Li ◽  
Peng Zhai ◽  
Yun Li Zhao
Keyword(s):  
Data Mining ◽  
Fault Diagnosis ◽  
Knowledge Base ◽  
Case Based Reasoning ◽  
Dynamic Data ◽  
Mining Technology ◽  
Decision Systems ◽  
Static Data ◽  
Fault Diagnosis System ◽  
Case Based

Most of the traditional drilling fault diagnosis & decision systems use static data mining technology, so the update of knowledge base becomes its bottlenecks in its development. In order to meet the actual needs, this paper puts forward the method, which combines dynamic data mining technology with case-based reasoning technology, to design drilling fault diagnosis & decision systems. First, design drilling fault diagnosis system overall, then describe the realization of how to realize dynamic data mining and case-based reasoning in detail, finally, introduce some question about the update of knowledge base.

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