A time-series data processing device comprising: a leg extraction unit configured to take as input time-series data being a sequence of sensor values sequentially obtained from a control system over time, and to extract, as an extension leg, subsequence data which is segmented from the time-series data and in which a value at a terminal point is higher or lower than a value at a start point; and an appearance pattern identification unit configured to identify, from the extension leg extracted by the leg extraction unit, a suite of extension legs where an extension rising leg in which a value at a terminal point is higher than a value at a start point, and an extension falling leg in which a value at a terminal point is lower than a value at a start point, appear in an order of a reference pattern; wherein the extension rising leg is subsequence data in which a value at each time point between a start point and a terminal point is equal to or higher than a value at the start point and equal to or lower than a value at the terminal point, and the extension falling leg is subsequence data in which a value at each time point between a start point and a terminal point is equal to or lower than a value at the start point and equal to or higher than a value at the terminal point; wherein the appearance pattern identification unit is configured to identify a suite of extension legs where an extension rising leg and an extension falling leg appear alternately and characterized in that for each extension rising leg and each extension falling leg of the suite of extension legs, a difference between a value at a terminal point and a value at a start point of the leg is equal to or higher than a given amplitude A wherein the appearance pattern identification unit is configured to identify a suite of extension legs which includes a largest number of extension rising legs and a largest number of extension falling legs. a leg extraction unit configured to take as input time-series data being a sequence of sensor values sequentially obtained from a control system over time, and to extract, as an extension leg, subsequence data which is segmented from the time-series data and in which a value at a terminal point is higher or lower than a value at a start point; and an appearance pattern identification unit configured to identify, from the extension leg extracted by the leg extraction unit, a suite of extension legs where an extension rising leg in which a value at a terminal point is higher than a value at a start point, and an extension falling leg in which a value at a terminal point is lower than a value at a start point, appear in an order of a reference pattern; wherein the extension rising leg is subsequence data in which a value at each time point between a start point and a terminal point is equal to or higher than a value at the start point and equal to or lower than a value at the terminal point, and the extension falling leg is subsequence data in which a value at each time point between a start point and a terminal point is equal to or lower than a value at the start point and equal to or higher than a value at the terminal point; wherein the appearance pattern identification unit is configured to identify a suite of extension legs where an extension rising leg and an extension falling leg appear alternately and characterized in that for each extension rising leg and each extension falling leg of the suite of extension legs, a difference between a value at a terminal point and a value at a start point of the leg is equal to or higher than a given amplitude A wherein the appearance pattern identification unit is configured to identify a suite of extension legs which includes a largest number of extension rising legs and a largest number of extension falling legs. <EOS>