An online crack detection device comprising a rolling roll to be incorporated in a rolling device, the rolling roll having a barrel portion and shaft portions extending as a unit from both ends of the barrel portion; an acoustic emission sensor for detecting elastic waves generated on a surface of the barrel portion, the AE sensor being disposed in at least one of the shaft portions of the rolling roll; a calculation unit for calculating a characteristic quantity feature value of the elastic waves detected by the AE sensor; and a discrimination unit for discriminating, from the characteristic quantity feature value, elastic waves attributable to a crack occurring in the barrel portion surface, wherein the calculation unit is configured: to receive the elastic waves generated in the barrel portion of the rolling roll with the AE sensor as voltage signals, to generate filtered signals by removing unnecessary frequencies through filtering of the voltage signals, and to convert the filtered signals into digital signals after quantization, and to calculate the characteristic quantity feature value of the elastic waves from the digital signals, and wherein the discrimination unit is configured to discriminate the elastic waves attributable to the crack occurring in the barrel surface by removing, based on the characteristic quantity feature value of the elastic waves calculated by the calculation unit, elastic waves with rise time of 20 μsec or more as elastic waves attributable to friction between the rolling roll and a steel sheet at a time, when the rolling roll rolls the steel sheet, and detection time-synchronized elastic waves as elastic waves at a time of steel sheet biting when the rolling roll bites the steel sheet, the rise time being the characteristic quantity feature value of the elastic waves and the time of steel sheet biting being identified from time-series data of a load current applied to the rolling device. a rolling roll to be incorporated in a rolling device, the rolling roll having a barrel portion and shaft portions extending as a unit from both ends of the barrel portion; an acoustic emission sensor for detecting elastic waves generated on a surface of the barrel portion, the AE sensor being disposed in at least one of the shaft portions of the rolling roll; a calculation unit for calculating a characteristic quantity feature value of the elastic waves detected by the AE sensor; and a discrimination unit for discriminating, from the characteristic quantity feature value, elastic waves attributable to a crack occurring in the barrel portion surface, wherein the calculation unit is configured: to receive the elastic waves generated in the barrel portion of the rolling roll with the AE sensor as voltage signals, to generate filtered signals by removing unnecessary frequencies through filtering of the voltage signals, and to convert the filtered signals into digital signals after quantization, and to calculate the characteristic quantity feature value of the elastic waves from the digital signals, and to receive the elastic waves generated in the barrel portion of the rolling roll with the AE sensor as voltage signals, to generate filtered signals by removing unnecessary frequencies through filtering of the voltage signals, and to convert the filtered signals into digital signals after quantization, and to calculate the characteristic quantity feature value of the elastic waves from the digital signals, and wherein the discrimination unit is configured to discriminate the elastic waves attributable to the crack occurring in the barrel surface by removing, based on the characteristic quantity feature value of the elastic waves calculated by the calculation unit, elastic waves with rise time of 20 μsec or more as elastic waves attributable to friction between the rolling roll and a steel sheet at a time, when the rolling roll rolls the steel sheet, and detection time-synchronized elastic waves as elastic waves at a time of steel sheet biting when the rolling roll bites the steel sheet, the rise time being the characteristic quantity feature value of the elastic waves and the time of steel sheet biting being identified from time-series data of a load current applied to the rolling device.