Title :
The Intelligence System of Failures Diagnosis for Robot Base on the Knowledge Decision-Making
Author :
Lin, Li ; Tie, Zhang ; Cunxi, Xie
Author_Institution :
Sch. of Mech. & Automotive Eng., South China Univ. of Technol., Guangzhou
Abstract :
Based on knowledge decision method, an intelligent diagnosis system for robot is introduced. The system combines intelligence decision technology and knowledge of robot failures diagnosis. One dimension structure of data-base is proposed for the knowledge-base. Each failure symptom has its exclusive record number therefore, the complicated nature language is changed to simple code description respective, and avoids to searching problem for the complicated nature language. The arithmetic of knowledge decision is proposed in the intelligence system for robot failures diagnosis. Considering the factors of failure event probability, and diagnosis knowledge validating weight value, methods are used which is compositor for each failure, and the DFS (deep first search) strategy to validate each failures. By this means, the efficiency of the intelligence system for failures diagnosis is improved.
Keywords :
decision making; failure analysis; fault diagnosis; intelligent robots; knowledge based systems; tree searching; code description; deep first search strategy; diagnosis knowledge validating weight value; failure event probability; intelligence system; intelligent diagnosis system; knowledge decision making; nature languages; robot base; robot failures diagnosis; Decision making; Educational robots; Educational technology; Intelligent robots; Intelligent systems; Intelligent vehicles; Robot sensing systems; Robotic assembly; Robotics and automation; Service robots; failures diagnosis; intelligence system; knowledge decision; robot;
Conference_Titel :
Education Technology and Training, 2008. and 2008 International Workshop on Geoscience and Remote Sensing. ETT and GRS 2008. International Workshop on
Conference_Location :
Shanghai
Print_ISBN :
978-0-7695-3563-0
DOI :
10.1109/ETTandGRS.2008.372