A fault state detection apparatus, comprising: - an input unit; and - a processing unit; wherein the input unit is configured to receive a plurality of non-fault state condition monitoring data and associated ground truth information, and wherein the plurality of non-fault state condition monitoring data comprises vibration data, and wherein the non-fault state condition monitoring data are represented as a plurality of amplitudes in different frequency bins; wherein the input unit is configured to receive a plurality of fault state condition monitoring data and associated ground truth information, wherein the plurality of fault state condition monitoring data comprises vibration data; wherein the processing unit is configured to generate a subset of the plurality of fault state condition monitoring data from one or more non-fault state condition monitoring data, and wherein the generating of fault state conditioning monitoring data in the subset of the plurality of fault state condition monitoring data comprises a transformation of non-fault state condition monitoring data to fault state condition monitoring data, and wherein the transformation of the non-fault state condition monitoring data to the fault state condition monitoring data comprises an increase in the amplitude in a first one of the different frequency bins and an associated decrease in the amplitude in a second one of the different frequency bins; wherein the processing unit is configured to implement a machine learning algorithm; and wherein the processing unit is configured to train the machine learning algorithm on the basis of the plurality of non-fault state condition monitoring data and the associated ground truth information and on the basis of the plurality of fault state condition monitoring data and the associated ground truth information; wherein, the input unit is configured to receive condition monitoring data, and wherein the received condition monitoring data comprises vibration data; wherein, the processing unit is configured to analyse the received condition monitoring data with the trained machine learning algorithm to determine if the received condition monitoring data is associated with a fault state. - an input unit; and - a processing unit; wherein the input unit is configured to receive a plurality of non-fault state condition monitoring data and associated ground truth information, and wherein the plurality of non-fault state condition monitoring data comprises vibration data, and wherein the non-fault state condition monitoring data are represented as a plurality of amplitudes in different frequency bins; wherein the input unit is configured to receive a plurality of fault state condition monitoring data and associated ground truth information, wherein the plurality of fault state condition monitoring data comprises vibration data; wherein the processing unit is configured to generate a subset of the plurality of fault state condition monitoring data from one or more non-fault state condition monitoring data, and wherein the generating of fault state conditioning monitoring data in the subset of the plurality of fault state condition monitoring data comprises a transformation of non-fault state condition monitoring data to fault state condition monitoring data, and wherein the transformation of the non-fault state condition monitoring data to the fault state condition monitoring data comprises an increase in the amplitude in a first one of the different frequency bins and an associated decrease in the amplitude in a second one of the different frequency bins; wherein the processing unit is configured to implement a machine learning algorithm; and wherein the processing unit is configured to train the machine learning algorithm on the basis of the plurality of non-fault state condition monitoring data and the associated ground truth information and on the basis of the plurality of fault state condition monitoring data and the associated ground truth information; wherein, the input unit is configured to receive condition monitoring data, and wherein the received condition monitoring data comprises vibration data; wherein, the processing unit is configured to analyse the received condition monitoring data with the trained machine learning algorithm to determine if the received condition monitoring data is associated with a fault state.