Title :
Failure isolation using an associative memory algorithm
Author_Institution :
University of California, Irvine, California
Abstract :
This paper proposes the application of an associative memory algorithm for the identification and isolation of system failures. It is assumed that the system is time-invariant and that prior to the occurrence of the failure all signals are stationary random processes. It is also assumed that the fact that a failure has occurred and its time of occurrence are both known, from some other method. The associative memory algorithm assumes that all possible failure modes are known their signatures have been Stored in a random-access memory and feedback is used to provide a search algorithm. The combination of the memory and the feedback loop produce a dynamic associative memory whose output is a "nearest neighbor" of the actual failure mode.
Keywords :
Associative memory; Autocorrelation; Equations; Filters; Mathematical model; Noise measurement; Random processes; State estimation; Vectors; White noise;
Conference_Titel :
Decision and Control, 1986 25th IEEE Conference on
Conference_Location :
Athens, Greece
DOI :
10.1109/CDC.1986.267552