A plant abnormality diagnosis device , comprising: an abnormality rate calculating unit configured to calculate an abnormality rate of an entire diagnosis target plant from a plurality of items of measurement data of various sensors installed in the diagnosis target plant based on a distance difference in a space between data and the plurality of items of measurement data, the data belonging to a category determined during a learning processing based on data during a normal time of the diagnosis target plant by an Adaptive Resonance Theory algorithm; an ART processing unit configured to execute category determination processing by the Adaptive Resonance Theory algorithm; and an ART control unit configured to control an activation timing of the ART processing unit , wherein the abnormality rate calculating unit is configured to calculate an abnormality rate of each of the plurality of items of measurement data based on a distance difference in a signal direction between the data and each of the plurality of items of measurement data, the data belonging to the category determined based on the data during the normal time of the diagnosis target plant , and characterized in that the ART control unit is configured to activate the ART processing unit , when a number of times that the abnormality rate of the entire diagnosis target plant calculated by the abnormality rate calculating unit exceeds a predetermined threshold is a fixed number of times or more, wherein the predetermined threshold is appropriately set based on calculation results of the abnormality rate of the entire diagnosis target plant taking into account a data fluctuation during the learning processing. an abnormality rate calculating unit configured to calculate an abnormality rate of an entire diagnosis target plant from a plurality of items of measurement data of various sensors installed in the diagnosis target plant based on a distance difference in a space between data and the plurality of items of measurement data, the data belonging to a category determined during a learning processing based on data during a normal time of the diagnosis target plant by an Adaptive Resonance Theory algorithm; an ART processing unit configured to execute category determination processing by the Adaptive Resonance Theory algorithm; and an ART control unit configured to control an activation timing of the ART processing unit , wherein the abnormality rate calculating unit is configured to calculate an abnormality rate of each of the plurality of items of measurement data based on a distance difference in a signal direction between the data and each of the plurality of items of measurement data, the data belonging to the category determined based on the data during the normal time of the diagnosis target plant , and characterized in that the ART control unit is configured to activate the ART processing unit , when a number of times that the abnormality rate of the entire diagnosis target plant calculated by the abnormality rate calculating unit exceeds a predetermined threshold is a fixed number of times or more, wherein the predetermined threshold is appropriately set based on calculation results of the abnormality rate of the entire diagnosis target plant taking into account a data fluctuation during the learning processing. <EOS>