A fault detection apparatus comprising: storage means for storing correlation destruction set information which indicates a correlation on which correlation destruction was detected when a fault occurred, among correlations included in a correlation model representing correlations, in terms of correlation functions, between a plurality of types of performance values of a system, said correlation function being a transform function regarding one of two arbitrary types of performance values as an input and the other as an output, correlation analysis means for applying an actual performance value for a first type among two arbitrary types, calculating a predictive performance value for a second type among the two arbitrary types by using a correlation function between the first type and the second type, comparing an actual performance value with the calculated predictive performance value for the second type to calculate a prediction error, and judging that a correlation between the first type and the second type is destructed if the calculated prediction error is out of a predetermined error range, and correlation model comparison means (25, 325) for calculating a commonality between said correlation included in said correlation destruction set information and correlation on which correlation destruction is detected for actual performance values, wherein said correlation destruction set information includes a fault name of said fault, and said correlation model comparison means (25, 325) outputs said fault name of said fault in case said commonality is equal to or greater than a predetermined threshold value. storage means for storing correlation destruction set information which indicates a correlation on which correlation destruction was detected when a fault occurred, among correlations included in a correlation model representing correlations, in terms of correlation functions, between a plurality of types of performance values of a system, said correlation function being a transform function regarding one of two arbitrary types of performance values as an input and the other as an output, correlation analysis means for applying an actual performance value for a first type among two arbitrary types, calculating a predictive performance value for a second type among the two arbitrary types by using a correlation function between the first type and the second type, comparing an actual performance value with the calculated predictive performance value for the second type to calculate a prediction error, and judging that a correlation between the first type and the second type is destructed if the calculated prediction error is out of a predetermined error range, and correlation model comparison means (25, 325) for calculating a commonality between said correlation included in said correlation destruction set information and correlation on which correlation destruction is detected for actual performance values, wherein said correlation destruction set information includes a fault name of said fault, and said correlation model comparison means (25, 325) outputs said fault name of said fault in case said commonality is equal to or greater than a predetermined threshold value.