A fuzzy temporal notation and its application to specify fault patterns for diagnosis
Many systems collect vast amounts of data over time, which is used to perform critical tasks like diagnosis, surveillance, resource management, planning and forecasting. To effectively use the historical data for these purposes, it is important to analyze the data and to gain insight into its significant aspects, by identifying the presence and characteristics of specific patterns. We describe a fuzzy logical notation, enhanced with facilities for expressing approximate temporal patterns, to build compositional and abstract models of syntactic structure of patterns. We present an algorithm, which detects where and how strongly the given pattern (i.e., a formula) is present. The approach is illustrated by specifying and detecting fault patterns for trace-based diagnosis of dynamic systems.
fault patterns fuzzy logic trace-based diagnosis temporal logic