Title :
Study of fault diagnosis approach based on rules of deep knowledge representation of signed directed graph
Author :
Cao, Wen-liang ; Wang, Bing-shu ; Ma, Liang-Yu ; Yan, Qin ; Hao, Wei ; Xin, Yufeng
Author_Institution :
Sch. of Control Sci. & Eng., North China Electr. Power Univ., Baoding
Abstract :
The fault diagnosis method using a signed directed graph (SDG) based on qualitative model as a model of the system is useful to real-time diagnosis of failures that occur in process. First, it establishes the SDG of the systems and components, simplifies these SDG corresponding to the fault modes needing to be diagnosed, at the same time SDG are described the many rules forms for shortening the calculating time of making use of SDG, then expands the diagnosing rule with expert knowledge to construct the diagnosing rule bank of the system. Second, the fault modes can be primary diagnosed by using the constructed rules. And then the modes that can not be distinguished are diagnosed by adding adequate quantitative information. The case studies show that the problem of misoperation autodiagnosis during computer simulation training can be solved effectively, and the SDG diagnosis method has good completeness, fine resolution and detailed explanation in actual industrial process
Keywords :
diagnostic expert systems; directed graphs; fault diagnosis; knowledge representation; adequate quantitative information; constructed rules; deep knowledge representation; diagnosing rule bank; expert knowledge; fault diagnosis approach; qualitative model; signed directed graph; Computer industry; Computer simulation; Fault diagnosis; Industrial relations; Industrial training; Knowledge representation; Power engineering and energy; Power generation; Power system modeling; Real time systems;
Conference_Titel :
Industrial Technology, 2005. ICIT 2005. IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7803-9484-4
DOI :
10.1109/ICIT.2005.1600741