Described herein are acoustic emission damage classification methods and systems employing intensity analysis to monitor the state of rotating machinery to classify the damage occurring to a mechanical object.

Described herein are acoustic emission damage classification methods and systems employing intensity analysis to monitor the state of rotating machinery to classify the damage occurring to a mechanical object.

A bearing ring having a main part ring provided with at least one groove formed a surface of the main part ring. The bearing ring further provides at least one fiber sensor mounted inside the groove. The bearing ring also include at least one counterpart ring mounted into the groove of the main part ring and coming into contact with the fiber sensor to maintain the fiber sensor against a groove bottom, the counterpart ring being secured to the main part ring.

A bearing ring having a main part ring provided with at least one groove formed a surface of the main part ring. The bearing ring further provides at least one fiber sensor mounted inside the groove. The bearing ring also include at least one counterpart ring mounted into the groove of the main part ring and coming into contact with the fiber sensor to maintain the fiber sensor against a groove bottom, the counterpart ring being secured to the main part ring.

A computer-implemented process determines, based on bearing fault frequencies, optimum values for the maximum frequency (F.sub.max) and the number of lines of resolution (N.sub.lines) to be used in collecting machine vibration data so as to adequately distinguish between spectral peaks for identifying faults in machine bearings. The process can be extended to any other types of fault frequencies that a machine may exhibit, such as motor fault frequencies, pump/fan fault frequencies, and gear mesh fault frequencies. Embodiments of the process also ensure that the time needed to acquire the waveform is optimized. This is particularly useful when collecting data using portable vibration monitoring devices.

A computer-implemented method analyzes periodic information in digital vibration data associated with a machine. The method involves generating a spectral periodic information plot (PIP) based on the digital vibration data, and locating amplitude peaks in the PIP at frequencies associated with fundamental frequencies of interest. Peaks occurring at fundamental fault frequencies and at related harmonic frequencies are removed from the PIP, while retaining energy values associated with the removed peaks. Remaining peaks in the PIP are classified as synchronous periodic peaks and non-synchronous periodic peaks. The remaining peaks in the PIP are graphically plotted along with the fault frequencies and related harmonic frequencies in different colors or different line styles on a display device to identify different groups of frequencies of interest. The method implements an algorithm that locates peaks in the PIP at frequencies associated with the fundamental frequencies of interest even though frequencies of the located peaks do not precisely match the fundamental frequencies of interest.

A computer-implemented method analyzes periodic information in digital vibration data associated with a machine. The method involves generating a spectral periodic information plot (PIP) based on the digital vibration data, and locating amplitude peaks in the PIP at frequencies associated with fundamental frequencies of interest. Peaks occurring at fundamental fault frequencies and at related harmonic frequencies are removed from the PIP, while retaining energy values associated with the removed peaks. Remaining peaks in the PIP are classified as synchronous periodic peaks and non-synchronous periodic peaks. The remaining peaks in the PIP are graphically plotted along with the fault frequencies and related harmonic frequencies in different colors or different line styles on a display device to identify different groups of frequencies of interest. The method implements an algorithm that locates peaks in the PIP at frequencies associated with the fundamental frequencies of interest even though frequencies of the located peaks do not precisely match the fundamental frequencies of interest.

A computer-implemented method of Condition Monitoring (CM) for rotating machines like motors, a corresponding computer program, computer-readable medium and data processing system for CM for rotating machines as well as a system including the data processing system for CM for rotating machines. M accumulator variables are updated in real-time based on L samples including a current sample sn and at least one preceding sample Sn−1 of input data. Based on the M accumulator variables N spectral features are computed in real-time. A condition of the rotating machine is determined based on the N spectral features.

A computer-implemented method of Condition Monitoring (CM) for rotating machines like motors, a corresponding computer program, computer-readable medium and data processing system for CM for rotating machines as well as a system including the data processing system for CM for rotating machines. M accumulator variables are updated in real-time based on L samples including a current sample sn and at least one preceding sample Sn−1 of input data. Based on the M accumulator variables N spectral features are computed in real-time. A condition of the rotating machine is determined based on the N spectral features.

A computer-implemented process determines, based on bearing fault frequencies, optimum values for the maximum frequency (F.sub.max) and the number of lines of resolution (N.sub.lines) to be used in collecting machine vibration data so as to adequately distinguish between spectral peaks for identifying faults in machine bearings. The process can be extended to any other types of fault frequencies that a machine may exhibit, such as motor fault frequencies, pump/fan fault frequencies, and gear mesh fault frequencies. Embodiments of the process also ensure that the time needed to acquire the waveform is optimized. This is particularly useful when collecting data using portable vibration monitoring devices.