Method and data processing device for severity assessment of bearing defects using vibration energy
First Claim
1. A method for detecting a bearing defect severity based on a rotation speed of a bearing and on at least one data sample of sensor data obtained by a sensor configured to measure vibrations of a bearing ring, the method comprises the steps of:
- a. converting the data sample from time domain to frequency domain by applying a Fourier Transform to obtain a signal frequency spectrum;
b. determining a defect center frequency of the bearing using the rotation speed;
c. identifying a predetermined number of frequency peaks of the signal frequency spectrum;
d. determining a total vibration energy in an overall frequency band including the predetermined number of frequency peaks;
e. determining, for each of the frequency peaks, a peak energy as a spectral energy of signal components giving rise to the frequency peaks;
f. calculating a bearing defect spectral energy using the peak energies of the frequency peaks; and
g. using a ratio of the bearing defect spectral energy and the total vibration energy to assess a severity of the bearing defect.
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Accused Products
Abstract
Method for detecting bearing defect severity based on bearing rotation speed and at least one data sample of sensor data obtained to measure vibrations of a bearing ring is provided. The method includes converting the data sample from time domain to frequency domain to obtain a signal frequency spectrum; determining a defect center frequency of the bearing using the rotation speed; and identifying a predetermined number of frequency peaks of the signal frequency spectrum. A total vibration energy in an overall frequency band including the predetermined number of frequency peaks is first determined; next, for each of the frequency peaks, a peak energy as a spectral energy of signal components giving rise to the frequency peaks is determined; calculating a bearing defect spectral energy using the peak energies; and finally a ratio of the bearing defect spectral energy and a total vibration energy to assess a defect severity is obtained.
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Citations
10 Claims
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1. A method for detecting a bearing defect severity based on a rotation speed of a bearing and on at least one data sample of sensor data obtained by a sensor configured to measure vibrations of a bearing ring, the method comprises the steps of:
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a. converting the data sample from time domain to frequency domain by applying a Fourier Transform to obtain a signal frequency spectrum; b. determining a defect center frequency of the bearing using the rotation speed; c. identifying a predetermined number of frequency peaks of the signal frequency spectrum; d. determining a total vibration energy in an overall frequency band including the predetermined number of frequency peaks; e. determining, for each of the frequency peaks, a peak energy as a spectral energy of signal components giving rise to the frequency peaks; f. calculating a bearing defect spectral energy using the peak energies of the frequency peaks; and g. using a ratio of the bearing defect spectral energy and the total vibration energy to assess a severity of the bearing defect. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A condition monitoring system for monitoring a machine comprising:
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at least one bearing equipped with a sensor configured to measure vibrations of a bearing ring, and a data processing device, wherein the data processing device is configured to process data samples of sensor data obtained by the sensor by converting the data sample from time domain to frequency domain by applying a Fourier Transform to obtain a signal frequency spectrum;
determining a defect center frequency of the bearing using the rotation speed;
identifying a predetermined number of frequency peaks of the signal frequency spectrum;
determining a total vibration energy in an overall frequency band including the predetermined number of frequency peaks;
determining, for each of the frequency peaks, a peak energy as a spectral energy of signal components giving rise to the frequency peaks;
calculating a bearing defect spectral energy using the peak energies of the frequency peaks; and
using a ratio of the bearing defect spectral energy and the total vibration energy to assess a severity of the bearing defect.
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10. A machine comprising:
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at least one bearing equipped with a sensor, and a condition monitoring system having at least one bearing equipped with a sensor configured to measure vibrations of a bearing ring, and a data processing device, wherein the data processing device is configured to process data samples of sensor data obtained by the sensor by converting the data sample from time domain to frequency domain by applying a Fourier Transform to obtain a signal frequency spectrum;
determining a defect center frequency of the bearing using the rotation speed;
identifying a predetermined number of frequency peaks of the signal frequency spectrum;
determining a total vibration energy in an overall frequency band including the predetermined number of frequency peaks;
determining, for each of the frequency peaks, a peak energy as a spectral energy of signal components giving rise to the frequency peaks;
calculating a bearing defect spectral energy using the peak energies of the frequency peaks; and
using a ratio of the bearing defect spectral energy and the total vibration energy to assess a severity of the bearing defect, whereinthe data processing device of the condition monitoring system is configured to process data samples of sensor data obtained by the sensor.
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Specification