Title :
Fault diagnosis with continuous system models
Author :
Chu, Bei-Tseng Bill
Author_Institution :
Dept. of Comput. Sci., North Carolina Univ., Charlotte, NC, USA
Abstract :
A unified diagnostic reasoning model that deals with both continuous as well as discrete causal relationships is presented. The diagnostic model significantly extends the formal probabilistic diagnostic reasoning models of other works. Statistical theories are used to formally derive conditional causation probabilities based on continuous system models. The derived conditional causation probabilities can be used along with discrete causal relationships provided by experts to find the most probable diagnostic hypothesis for a given set of observations
Keywords :
diagnostic expert systems; model-based reasoning; probability; conditional causation probabilities; continuous causal relationships; continuous system models; diagnostic reasoning model; discrete causal relationships; fault diagnosis; most probable diagnostic hypothesis; Artificial intelligence; Computer errors; Computer science; Continuous time systems; Fault diagnosis; Instruments; Noise measurement; Probability; Random variables; Volume measurement;
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on
