Abstract: A monitoring device for monitoring a bearing in an electromagnetic field environment includes a vibration sensor for delivering at least one measurement that includes at least one vibration frequency generated by a bearing, and a processing module that includes a first processing module configured to determine at least one normalized measured value from the at least one vibration frequency, a filtering module configured to compare the normalized measured value to at least one predetermined normalized reference value indicative of electromagnetic phenomena acting on the bearing, and a second processing module configured to process the at least one vibration frequency to determine a bearing defect if the normalized measured value is different from the at least one predetermined normalized reference value.

Abstract: A monitoring device for monitoring a bearing in an electromagnetic field environment includes a vibration sensor for delivering at least one measurement that includes at least one vibration frequency generated by a bearing, and a processing module that includes a first processing module configured to determine at least one normalized measured value from the at least one vibration frequency, a filtering module configured to compare the normalized measured value to at least one predetermined normalized reference value indicative of electromagnetic phenomena acting on the bearing, and a second processing module configured to process the at least one vibration frequency to determine a bearing defect if the normalized measured value is different from the at least one predetermined normalized reference value.

Abstract: A method of identifying at least one defect of a rotating component, where the defect is selected from a group of predefined defects, includes extracting frequency data related to each of the predefined defects in order to form a first spectrum signature for each of the predefined defects. Also measuring at least one vibration signal produced by the rotating component to obtain at least two second spectrums, filtering each second spectrum based on an exponential smoothing algorithm, selecting peaks in each second spectrum according to a prominence of each of the peaks, setting selected peaks to zero if the selected peaks are not present in a predefined number of consecutive second spectrums, and calculating a probability that each first spectrum signature corresponds to at least one of the second spectrums.