Study on CBR-Based Automobile Engine Intelligent Fault Diagnosis Technique

2011 ◽  
Vol 460-461 ◽  
pp. 637-641 ◽  
Author(s):  
Pei Feng Sun ◽  
Yong Ni
Keyword(s):  
Fault Diagnosis ◽  
High Technology ◽  
Case Based Reasoning ◽  
Complex Structures ◽  
Intelligent Fault Diagnosis ◽  
Automobile Engine ◽  
Diagnosis System ◽  
Fault Diagnosis System ◽  
Key Techniques ◽  
Diagnosis Technique

It is difficult to do the fault diagnosis on the modern car engines which have high technology and complex structures. In this study, a case-based-reasoning (CBR) based automobile engine intelligent fault diagnosis system was proposed against this problem. The system’s structure and its mechanism of fault diagnosis were introduced. The key techniques to implement the system were analyzed, including the case establishment, the case search, the case learning and the maintenance of case library. The proposed system gave a new way to establish an efficient automobile engine fault diagnosis system.

Fault Diagnosis System for Large-Scale Equipments Based on Hybrid Reasoning

2011 ◽  
Vol 201-203 ◽  
pp. 956-961
Author(s):  
Ming Chen ◽  
Rui Zhang ◽  
Ying Lei Li
Keyword(s):  
Fault Diagnosis ◽  
Large Scale ◽  
Cross Correlation ◽  
Fault Tree ◽  
Case Based Reasoning ◽  
Complex Structures ◽  
Diagnosis System ◽  
Trouble Shooting ◽  
Hybrid Reasoning ◽  
Fault Diagnosis System

Because of their complex structures, diverse functions, and cross-correlation among subsystems, the fault of large-scale equipments occurs easily, but its trouble shooting is difficult. Firstly, a hybrid reasoning method is proposed, and the framework of fault diagnosis system is constructed according to characteristics of case based reasoning (CBR) and rule based reasoning (RBR). Secondly, CBR and RBR applied to fault diagnosis for large-scale NC equipments are analyzed. In RBR process, the fault tree was obtained by reachability matrix, and the rules knowledge is automatically generated by fault tree, so the bottleneck of acquiring rules knowledge is solved. Lastly, this method is used in the fault diagnosis of certain large-scale NC equipment, which verifies the validity of the method.

Remote Fault Diagnosis System of Ultrahigh Speed Grinding Based on Multi-Agent

2009 ◽  
Vol 76-78 ◽  
pp. 67-71
Author(s):  
Wan Shan Wang ◽  
Tian Biao Yu
Keyword(s):  
Fault Diagnosis ◽  
Theoretical Research ◽  
Case Based Reasoning ◽  
Diagnosis System ◽  
Knowledge Reasoning ◽  
Diagnosis Method ◽  
Multi Agent ◽  
Fault Diagnosis System ◽  
Set Up ◽  
Remote Fault Diagnosis

A remote fault diagnosis method for ultrahigh speeding grinding based on multi-agent is presented. The general faults of ultrahigh speed grinding are analyzed and diagnosis model based on multi-agent is established, the dialogue layer, problem decomposition layer, control layer and problem solving layer in the process of diagnosis are studied and the knowledge reasoning model of fault diagnosis is set up based case-based reasoning (CBR) combining rule-based reasoning (RBR). Based on theoretical research, a remote fault diagnosis system of ultrahigh speed grinding is developed. Results of the system running prove the theory is correctness and the technology is feasibility.

Design and Analysis of Fault Diagnosis System of Electrohydraulic Servo Valve Based on ANN

2013 ◽  
Vol 785-786 ◽  
pp. 1380-1383
Author(s):  
Yao Li ◽  
Jian Gang Yi
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Fault Diagnosis ◽  
Servo System ◽  
Intelligent Fault Diagnosis ◽  
Diagnosis System ◽  
Servo Valve ◽  
Pressure Characteristic ◽  
Fault Diagnosis System ◽  
Electrohydraulic Servo System

It is a difficulty to combine artificial neural networks (ANN) with the fault diagnosis of electrohydraulic servo valve. To slolve this problem, the fault diagnosis mechanism of electrohydraulic servo system is analysed, the effecitveness of fault diagnosis based on ANN is verified, and the pressure characteristic data are used to construct ANN samples. Finally, the algorithms of RBF, BP and Elman are compared with the built system and sampled. The results show the RBF algorithm is more rapid and accurate and the proposed intelligent fault diagnosis system of electrohydraulic servo valve is valuable.

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