Method and apparatus for diagnosing residual life of rolling element bearing

• US 20050246150A1
• Filed: 05/28/2003
• Published: 11/03/2005
• Est. Priority Date: 05/31/2002
• Status: Active Grant

• Current Assignee: Chugoku Electric Power Company Incorporated, Takuzo Iwatsubo
• Original Assignee: Chugoku Electric Power Company Incorporated
• Inventors: Akamatsu, Yoshinobu, Tanaka, Makoto, Iwatsubo, Takuzo, Shiromaru, Isao, Nagayasu, Yoji, Boda, Shingo
• Granted Patent: US 7,813,906 B2
• Time in Patent Office: Days
• US Class Current: 703/7
• CPC Class Codes: G01H 1/003 of rotating machines G01H1/10 takes precedence
• CPC Class Codes: G01M 13/045 Acoustic or vibration analysis

Abstract

An invention that utilizes signals from an accelerometer in resonant frequency bands or high frequency bands to, in a cost-effective manner, measure wear particle penetration of lubricant and lubricant degradation, both of which greatly affect prediction of residual service life; and, using as a basis these measurements of wear particle penetration and lubricant degradation, enables accurate estimation of residual service life for rolling bearings in the early stages. The invention is comprised of a means of obtaining fundamental data that uses a testing device to obtain data regarding the relationship, for rolling bearings (3), of wear particle penetration levels to vibration levels and service life, or to obtain data regarding the relationship, for rolling bearings (3), of lubricant degradation levels to vibration levels and service life; a means of measurement, where an accelerometer (4) is used to obtain vibration signals of diagnostic rolling bearings (3) residing on mechanical rotating devices (1, 2) for the purpose of measuring signals in resonant frequency bands only detectable at extremely high levels of sensitivity or signals in high frequency bands; and a means of prediction that uses readings obtained via said means of measurement and data obtained via said means of obtaining fundamental data to predict, for diagnostic rolling bearings (3), wear particle penetration levels and lubricant degradation levels, and to calculate residual service life for diagnostic rolling bearings (3).

Claims

1. A method of predicting residual service life for rolling bearings comprised of the following:

a means of obtaining fundamental data that uses a testing device to obtain data regarding the relationship for rolling bearings (3) of wear particle penetration levels to vibration levels and service life, and to obtain data regarding the relationship, for rolling bearings (3), of lubricant degradation levels to vibration levels and service life;

a means of measurement where an accelerometer (4) is used to obtain vibration signals of diagnostic rolling bearings (3) residing on mechanical rotating devices (1, 2), such as pumps and fans, for the purpose of measuring signals in resonant frequency bands only detectable at extremely high levels of sensitivity; and

a means of prediction that uses readings obtained via said means of measurement and data obtained via said means of obtaining fundamental data to predict, for said diagnostic rolling bearings (3), wear particle penetration levels and lubricant degradation levels, and to calculate residual service life for said diagnostic rolling bearings (3).

3. The method of predicting residual service life for rolling bearings according to claims 1 or 2, where said means of obtaining fundamental data involves affecting the rolling contact surfaces of said rolling bearings (3) with indentations in order to simulate wear particle penetration, for the purpose of quantifying the relationship of wear particle penetration to bearing vibration and service life.

4. The method of predicting residual service life for rolling bearings according to claims 1 or 2, where said means of obtaining fundamental data involves introducing a foreign substance into the lubricant of said rolling bearings (3) and varying the volume or size of the substance in order to simulate wear particle penetration, for the purpose of quantifying the relationship of wear particle penetration to bearing vibration and service life.

5. The method of predicting residual service life for rolling bearings according to claims 1 or 2, where said means of obtaining fundamental data involves introducing a foreign substance into the lubricant of said rolling bearings (3), and varying the viscosity or elasticity of the foreign substance in order to simulate wear particle penetration, for the purpose of quantifying the relationship of wear particle penetration to bearing vibration and service life.

6. The method of predicting residual service life for rolling bearings according to claims 1 or 2, where said means of obtaining fundamental data involves reducing the volume of lubricant in said rolling bearings (3) in order to simulate lubricant degradation, for the purpose of quantifying the relationship of lubricant degradation to bearing vibration and service life.

7. The method of predicting residual service life for rolling bearings according to claims 1 or 2, where said means of obtaining fundamental data involves affecting oxidative degradation upon lubricant in said rolling bearings (3) in order to simulate lubricant degradation, for the purpose of quantifying the relationship of lubricant degradation to bearing vibration and service life.

8. The method of predicting residual service life for rolling bearings according to claims 1 or 2, where said means of obtaining fundamental data involves introducing water into the lubricant in said rolling bearings (3) in order to simulate lubricant degradation, for the purpose of quantifying the relationship of lubricant degradation to bearing vibration and service life.

9. The method of predicting residual service life for rolling bearings according to claims 1 or 2, where, for said means of obtaining fundamental data, vibration signals from an accelerometer (4) in resonant frequency bands only detectable at extremely high levels of sensitivity are used to quantify the relationship of wear particle penetration to vibration and service life.

10. The method of predicting residual service life for rolling bearings according to claims 1 or 2, where, for said means of obtaining fundamental data, vibration signals from an accelerometer (4) in high frequency bands are used to quantify the relationship of wear particle penetration to vibration and service life.

11. The method of predicting residual service life for rolling bearings according to claims 1 or 2 where, for said means of obtaining fundamental data, vibration signals from an accelerometer (4) in resonant frequency bands only detectable at extremely high levels of sensitivity are used to quantify the relationship of lubricant degradation to vibration and service life.

12. The method of predicting residual service life for rolling bearings according to claims 1 or 2 where, for said means of obtaining fundamental data, vibration signals from an accelerometer (4) in high frequency bands are used to quantify the relationship of lubricant degradation to vibration and service life

13. The method of predicting residual service life for rolling bearings according to claim 1 where said means of measurement utilizes vibration signals from an accelerometer (4) in resonant frequency bands only detectable at extremely high levels of sensitivity to measure wear particle penetration.

14. The method of predicting residual service life for rolling bearings according to claim 12 where said means of measurement utilizes vibration signals from an accelerometer (4) in resonant frequency bands only detectable at extremely high levels of sensitivity to measure the density of wear particle indentations.

15. The method of predicting residual service life for rolling bearings according to claim 12 where said means of measurement utilizes vibration signals from an accelerometer (4) in resonant frequency bands only detectable at extremely high levels of sensitivity to measure the size of wear particle indentations.

19. The method of predicting residual service life for rolling bearings according to claim 1, where said means of measurement utilizes vibration signals from an accelerometer (4) in resonant frequency bands only detectable at extremely high levels of sensitivity to measure lubricant degradation.

21. The method of predicting residual service life for rolling bearings according to claim 1, where said means of prediction utilizes vibration signals from an accelerometer (4) in resonant frequency bands only detectable at extremely high levels of sensitivity to estimate wear particle penetration levels and to calculate residual service life.

22. The method of predicting residual service life for rolling bearings according to claim 1, where said means of prediction utilizes vibration signals from an accelerometer (4) in resonant frequency bands only detectable at extremely high levels of sensitivity to detect the presence of wear particle indentations and to calculate residual service life.

23. The method of predicting residual service life for rolling bearings according to claim 1, where said means of prediction utilizes vibration signals from an accelerometer (4) in resonant frequency bands only detectable at extremely high levels of sensitivity to estimate the size of wear particle indentations and to calculate residual service life.

27. The method of predicting residual service life for rolling bearings according to claim 1, where, for said means of prediction, vibration signals from an accelerometer (4) in resonant frequency bands only detectable at extremely high levels of sensitivity are utilized to obtain estimates regarding lubricant degradation levels, and calculations regarding residual service life.

29. The method of predicting residual service life for rolling bearings according to claims 1 or 2, where said means of prediction utilizes pre-measured data regarding diagnostic rolling bearings (3) in a state of normal fatigue, including,, bearing load, rolling speed, operating time and rolling bearing designation.

30. The method of predicting residual service life for rolling bearings according to claims 1 or 2, where said means of prediction utilizes data obtained via said means of measurement and pre-measured vibration data of diagnostic rolling bearings (3) in a state of normal fatigue in order to, by calculating the rate of increase in vibration signals at low frequencies of vibration acceleration, judge whether said diagnostic rolling bearing (3) is in the stage of first signs of fatigue or in the stage of total fatigue failure.

31. The method of predicting residual service life for rolling bearings according to claims 1 or 2, where said means of prediction utilizes vibration signals from an accelerometer (4) in resonant frequency bands only detectable at extremely high levels of sensitivity to judge whether wear particle penetration has occurred, whether lubricant degradation has occurred, and to judge whether diagnostic rolling bearings (3) are undergoing a process of normal fatigue, a process of wear particle penetration, or a process of lubricant degradation.

32. The method of predicting residual service life for rolling bearings according to claims 1 or 2, where said means of prediction utilizes vibration signals from an accelerometer (4) in high frequency bands to judge whether wear particle penetration has occurred, whether lubricant degradation has occurred, and to judge whether diagnostic rolling bearings (3) are undergoing a process of normal fatigue, a process of wear particle penetration, or a process of lubricant degradation.

33. The method of predicting residual service life for rolling bearings according to claims 1 or 2, where said means of prediction calculates the rating life, and defines residual service life as the rating life of said diagnostic rolling bearings (3) judged to be in a state of normal fatigue, meaning there has been no wear particle penetration or lubricant degradation.

34. The method of predicting residual service life for rolling bearings according to claims 1 or 2, where said means of prediction utilizes vibration data obtained via said means of obtaining fundamental data to, if it has been judged that said diagnostic rolling bearings (3) have undergone wear particle penetration and are in the stage of first signs of fatigue, estimate wear particle size and calculate residual service life.

35. The method of predicting residual service life for rolling bearings according to claims 1 or 2, where said means of prediction utilizes vibration data obtained via said means of obtaining fundamental data to, if it has been judged that lubricant existent in said diagnostic rolling bearings (3) has undergone degradation and that said diagnostic rolling bearings (3) are in the stage of first signs of fatigue, estimate said lubricant'"'"'s degradation levels and calculate residual service life.

36. The method of predicting residual service life for rolling bearings according to claims 1 or 2, where said means of prediction, if it has been judged that the stage of total fatigue failure has been reached, calculates the residual service life, using as a basis the rate of increase in said vibration signals at low frequencies of vibration acceleration.

37. The method of predicting residual service life for rolling bearings according to claims 1 or 2, where said means of prediction, if it has been judged that the stage of total fatigue failure has been reached, calculates residual service life, using as a basis the interval between initial wear particle penetration and the stage of total fatigue failure, or the interval between initial lubricant degradation and the stage of total fatigue failure.

2. A method of predicting residual service life for rolling bearings comprised of the following:

a means of obtaining fundamental data that uses a testing device to obtain data regarding the relationship, for rolling bearings (3), of wear particle penetration levels to vibration levels and service life, and to obtain data regarding the relationship, for rolling bearings (3), of lubricant degradation levels to vibration levels and service life;

a means of measurement where, for diagnostic rolling bearings (3) residing on mechanical rotating devices (1, 2) such as pumps and fans, vibration acceleration signals in high frequency bands are measured; and

a means of prediction that uses readings obtained via said means of measurement and data obtained via said means of obtaining fundamental data to predict, for said diagnostic rolling bearings (3), wear particle penetration levels and lubricant degradation levels, and to calculate residual service life for said diagnostic rolling bearings (3).

16. The method of predicting residual service life for rolling bearings according to claim 2, where said means of measurement utilizes vibration signals from an accelerometer (4) in high frequency bands to measure wear particle penetration.

17. The method of predicting residual service life for rolling bearings according to claim 2, where said means of measurement utilizes vibration signals from an accelerometer (4) in high frequency bands to measure the density of wear particle indentations.

18. The method of predicting residual service life for rolling bearings according to claim 2, where said means of measurement utilizes vibration signals from an accelerometer (4) in high frequency bands to measure the size of wear particle indentations.

20. The method of predicting residual service life for rolling bearings according to claim 2, where said means of measurement utilizes vibration signals from an accelerometer (4) in high frequency bands to measure lubricant degradation.

24. The method of predicting residual service life for rolling bearings according to claim 2 where said means of prediction utilizes vibration signals from an accelerometer (4) in high frequency bands to estimate wear particle penetration levels and to calculate residual service life.

25. The method of predicting residual service life for rolling bearings according to claim 2 where said means ofprediction utilizes vibration signals from an accelerometer (4) in high frequency bands to detect the presence of wear particle indentations and to calculate residual service life.

26. The method of predicting residual service life for rolling bearings according to claim 2 where said means of prediction utilizes vibration signals from an accelerometer (4) in high frequency bands to estimate the size of wear particle indentations and to calculate residual service life.

28. The method of predicting residual service life for rolling bearings according to claim 2, where, for said means of prediction, vibration signals from an accelerometer (4) in high frequency bands are used to obtain estimates regarding lubricant degradation levels, and calculations regarding residual service life.

38. A device for predicting residual service life for rolling bearings comprised of the following:

an accelerometer (4) that measures vibration signals from diagnostic rolling bearings (3) to predict residual service life;

an analogue/digital converter (5) that converts data obtained via said accelerometer (4), a quantitative feature extraction device (6) that extracts vibration signals in resonant frequency bands only detectable at extremely high levels of sensitivity from vibration signals converted by said analogue/digital converter (5);

a database of resulting measurements (7) that has saved in it fundamental data records related to the relationship, for rolling bearings (3), of wear particle penetration to vibration and bearing service life, and the relationship of lubricant degradation to vibration and bearing service life, has saved in it vibration data of diagnostic rolling bearings (3) residing on mechanical rotating devices (1, 2), such as pumps and fans, obtained when said diagnostic rolling bearings (3) are in a state of normal fatigue, and has saved in it data related to bearing load, rolling speed, operating time and rolling bearing designation;

a device for predicting residual service life (8) that, utilizing data stored in said database of resulting measurements (7), predicts wear particle penetration levels and lubricant degradation levels in said diagnostic rolling bearings (3), using as a basis vibration signals from said diagnostic rolling bearings (3) extracted via said quantitative feature extraction device (6) to predict residual service life; and

a display device for predictions (9) that displays the resulting predictions of said device for predicting residual service life (8).

40. The device for predicting residual service life for rolling bearings according to claims 38 or 39 that further includes the following:

an output device for inspection schedules and diagnostic reports (10) that outputs schedules for ensuing inspection times and diagnostic results reports for said diagnostic rolling bearings (3), using as a basis diagnostic results from said device for predicting residual service life (8).

41. The device for predicting residual service life for rolling bearings according to claim 40, where said output device for inspection schedules and diagnostic reports (10) is a printer (12).

42. The device for predicting residual service life for rolling bearings according to claim 40, where said output device for inspection schedules and diagnostic reports (10) is a monitor.

43. The device for predicting residual service life for rolling bearings according to claims 38 or 39 that further includes, but is not limited to, the following:

a data transmission modem (11) that connects said waveform data and diagnostic results to the Internet network.

39. A device for predicting residual service life for rolling bearings comprised of the following:

an accelerometer (4) that measures vibration signals from diagnostic rolling bearings (3) to predict residual service life;

an analogue/digital converter (5) that converts data obtained via said accelerometer (4);

a quantitative feature extraction device (6) that extracts vibration signals in high frequency bands from the vibration signals converted by said analogue/digital converter (5);

a database of resulting measurements (7) that has saved in it fundamental data records related to the relationship, for rolling bearings (3), of wear particle penetration to vibration and bearing service life, and the relationship of lubricant degradation to vibration and bearing service life, has saved in it vibration data of diagnostic rolling bearings (3) residing on mechanical rotating devices (1, 2), such as pumps and fans, obtained when said diagnostic rolling bearings (3) are in a state of normal fatigue, and has saved in it data related to bearing load, rolling speed, operating time and rolling bearing designation;

a device for predicting residual service life (8) that, utilizing data stored in said database of resulting measurements (7), predicts wear particle penetration levels and lubricant degradation levels in said diagnostic rolling bearings (3), using as a basis vibration signals from said diagnostic rolling bearings (3) extracted via said quantitative feature extraction device (6) to predict residual service life; and

a display device for predictions (9) that displays the resulting predictions of said device for predicting residual service life (8).