Abstract: A method for detecting at least one machine defect provides defining from the machine kinematic data at least one condition indicator reflecting its condition, recording operating condition data of the machine and condition monitoring data of the machine during a predetermined period when the machine is operating normally, determining condition indicator values using condition monitoring data, and for determining current condition indicator values from the at least one condition indicator and the current condition monitoring data, a machine learning algorithm, predicting condition indicator values with respect to the current operating condition data, training the machine learning algorithm to establish a relation between the operating condition data and condition indicator values, and comparing the current condition indicator values and the predicted condition indicator values, and for determining if the machine is presumed to operate normally or not according to the result of the comparison.

Abstract: A method for detecting at least one machine defect provides defining from the machine kinematic data at least one condition indicator reflecting its condition, recording operating condition data of the machine and condition monitoring data of the machine during a predetermined period when the machine is operating normally, determining condition indicator values using condition monitoring data, and for determining current condition indicator values from the at least one condition indicator and the current condition monitoring data, a machine learning algorithm, predicting condition indicator values with respect to the current operating condition data, training the machine learning algorithm to establish a relation between the operating condition data and condition indicator values, and comparing the current condition indicator values and the predicted condition indicator values, and for determining if the machine is presumed to operate normally or not according to the result of the comparison.