Applying a case-based reasoning method for fault diagnosis during maintenance

Author(s):  
Y-T Tsai

The development of a fault-diagnosis system (FDS) could be helpful in identifying the source of faults before the occurrence of complete system failure. Here we report on such a diagnostic procedure for narrowing down maintenance tasks and shortening system downtime. A web-based FDS is developed based on case-based reasoning (CBR) from previous maintenance experience, for an injection moulding machine (IMM). The techniques of fault tree analysis (FTA) and information flow analysis are introduced to systematically clarify possible faults and symptoms shown by a system. A logical process is introduced to determine the correlation between the possible faults and the symptoms for computing case similarity while progressing CBR diagnosing. Some frontpages are developed for the CBR diagnosis using an ASP program in cooperation with a Microsoft Access database. The resultant FDS achieves good results with the potential for supporting remote IMM maintenance.

2012 ◽  
Vol 548 ◽  
pp. 516-520
Author(s):  
Yong Bo He ◽  
Sheng Liang Dou

Aircraft alternator is in the central position of the aircraft AC power system. The existing troubleshooting process is complex and tedious. In this paper, the aircraft alternator fault tree is established, and a fault example of under-voltage condition is analyzed in-depth qualitative and quantitative. According to the importance degree, the order of troubleshooting is obtained, making the fault diagnosis fast and effective. In order to overcome the limitation of the fault tree analysis, case-based reasoning is combined, making the fault diagnosis more comprehensive and accurate.


2020 ◽  
Vol 53 (2) ◽  
pp. 8217-8224
Author(s):  
Jonas Zinn ◽  
Birgit Vogel-Heuser ◽  
Felix Ocker

2014 ◽  
Vol 945-949 ◽  
pp. 1707-1712
Author(s):  
Bin Shen ◽  
Shu Yu Zhao ◽  
Jia Hai Wang ◽  
Juergen Fleischer

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.


2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Zhiwang Zhong ◽  
Tianhua Xu ◽  
Feng Wang ◽  
Tao Tang

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.


2014 ◽  
Vol 635-637 ◽  
pp. 715-721
Author(s):  
Hao Li ◽  
Yao Hui Zhang ◽  
Yi Zheng ◽  
Lin Hong Li

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.


2009 ◽  
Vol 36 (3) ◽  
pp. 7280-7287 ◽  
Author(s):  
Wu He ◽  
Feng-Kwei Wang ◽  
Tawnya Means ◽  
Li Da Xu

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