Title :
Diagnosis knowledge representation and inference
Author :
Luo, Jianhui ; Tu, Haiying ; Pattipati, Krishna ; Qiao, Liu ; Chigusa, Shunsuke
Author_Institution :
Dept. of Electr. & Comput. Eng., Connecticut Univ., Storrs, CT
Abstract :
In this article, we presented three graphical modeling techniques for diagnostic knowledge representation and inference: behavioral Petri nets (BPNs), multisignal flow graphs, and Bayesian networks (BNs). By using the same example from (Portinale, 1997) we showed that both multisignal flow graph model and BN model yield the same diagnosis. In addition, we showed that the P-invariant concept in BPN is similar to the D-separation concept in BNs
Keywords :
Petri nets; belief networks; graph theory; inference mechanisms; matrix algebra; signal flow graphs; BN model yield; BPN; Bayesian networks; D-separation concept; P-invariant concept; behavioral Petri nets; diagnosis knowledge representation; diagnostic knowledge representation; graphical modeling techniques; inference system; multisignal flow graphs; Bayesian methods; Engines; Fault detection; Fault diagnosis; Flow graphs; Graphical models; Interference; Knowledge representation; Petri nets; Testing;
Journal_Title :
Instrumentation & Measurement Magazine, IEEE
DOI :
10.1109/MIM.2006.1664042
