Method and apparatus for estimating values for condition indicators

• US 7,136,794 B1
• Filed: 12/04/2001
• Issued: 11/14/2006
• Est. Priority Date: 05/24/2001
• Status: Expired due to Term

• Current Assignee: Simmonds Precision Products, Inc. (Rtx Corporation)
• Original Assignee: Simmonds Precision Products, Inc. (Rtx Corporation)
• Inventors: Bechhoefer, Eric Robert
• Primary Examiner(s): FERRIS III, FRED O
• Application Number:
  US10/011,428
• Time in Patent Office: 1,806 Days
• Field of Search: 703 1- 7, 702/56, 702/181, 702/183
• US Class Current: 703/7
• CPC Class Codes: G01H 1/003 of rotating machines G01H1/10 takes precedence
• CPC Class Codes: G01N 2291/2693 Rotor or turbine parts
• CPC Class Codes: G01N 2291/2696 Wheels, Gears, Bearings
• CPC Class Codes: G01N 29/11 by measuring attenuation of acoustic waves
• CPC Class Codes: G01N 29/12 by measuring frequency or resonance of acoustic waves measuring frequency or resonant frequency of mechanical vibrations or acoustic waves in general G01H1/06, G01H3/04, G01H13/00; acoustic resonators G10K11/04; vibration or shock testing of structures G01M7/00
• CPC Class Codes: G01N 29/4445 Classification of defects
• CPC Class Codes: G01N 29/449 Statistical methods not provided for in G01N29/4409, e.g. averaging, smoothing and interpolation
• CPC Class Codes: G01N 29/46 by spectral analysis, e.g. Fourier analysis or wavelet analysis spectral signal processing per se G06F17/14
• CPC Class Codes: G05B 23/0221 Preprocessing measurements, e.g. data collection rate adjustment; Standardization of measurements; Time series or signal analysis, e.g. frequency analysis or wavelets; Trustworthiness of measurements; Indexes therefor; Measurements using easily measured parameters to estimate parameters difficult to measure; Virtual sensor creation; De-noising; Sensor fusion; Unconventional preprocessing inherently present in specific fault detection methods like PCA-based methods
• CPC Class Codes: G05B 23/0235 based on a comparison with predetermined threshold or range, e.g. "classical methods", carried out during normal operation; threshold adaptation or choice; when or how to compare with the threshold
• CPC Class Codes: G05B 23/0254 based on a quantitative model, e.g. mathematical relationships between inputs and outputs; functions: observer, Kalman filter, residual calculation, Neural Networks

Abstract

Disclosed are techniques used in connection with determining a health indicator (HI) of a component, such as that of an aircraft component. The HI is determined using condition indicators (CIs) which parameterize characteristics about a component minimizing possibility of a false alarm. Different algorithms are disclosed which may be used in determining one or more CIs. The HI may be determined using a normalized CI value. Techniques are also described in connection with selecting particular CIs that provide for maximizing separation between HI classifications. Given a particular HI at a point in time for a component, techniques are described for predicting a future state or health of the component using the Kalmán filter. Techniques are described for estimating data values as an alternative to performing data acquisitions, as may be used when there is no pre-existing data.

Claims

1. A computer-implemented method for estimating a conditional indicator value associated with a gear pair comprising:

modeling said gear pair as a damped spring model having a contact line between said gears;

determining a force, P, at a point of contact along said contact line causing linear and torsional response to each of said two gears in said gear pair;

determining a relative movement, d, of said gear pair, in accordance with said force, P, as a sum of four responses and a contact deflection, said relative movement d representing a gear model having two degrees of freedom, said contact deflection being due to a contact stiffness of a contact patch where two gears of said gear pair come into contact, and a linear damping coefficient of the contact patch; and

using said relative movement, d, in determining said conditional indicator value for transmission error associated with said gear pair.

2. The method of claim 1, further comprising:

varying parameter values in accordance with simulating different fault conditions; and

determining mean and threshold values for said different fault conditions.

19. The method of claim 1, wherein a first of said four responses utilizes a linear damping coefficient of a pinion, a second of said four responses utilizes an angular damping coefficient of the pinion, a third of said four responses utilizes a linear damping coefficient of a wheel, and a fourth of said four responses utilizes an angular damping coefficient of the wheel.

20. The method of claim 1, wherein P is an estimated value represented as

P=(1/kp*rp)+(1/sp)+(1/sw)+(1/kwrw), and wherein

kp is the angular effective stiffness of a pinion,

rp is a radius of the pinion,

sp is a linear stiffness of the pinion,

sw is a linear stiffness of a wheel,

kw is an angular effective stiffness of the wheel, and

rw is a radius of the wheel.

21. The method of claim 2, further comprising:

using one or more manufacturer supplied data values to determine said parameter values corresponding to a modeled healthy state of said gear pair; and

modifying said one or more parameter values to determine additional parameter values corresponding to one or more of said different fault conditions.

22. The method of claim 21, wherein one of said fault conditions corresponds to simulated alarm level having one or more of said parameter values estimated as a percentage of a manufacturer supplied value corresponding to a healthy state.

3. A method executed in a computer system for estimating a conditional indicator value associated with a bearing comprising:

modeling said bearing with a bearing model using a plurality of parameters including a bearing frequency ratio, a periodic impulse, an intensity of an impulse, and a decay of a unit impulse, wherein said bearing model is used to model at least one condition associated with said bearing, wherein said periodic impulse is determined in accordance with said bearing frequency ratio, said periodic impulse representing a modeled impulse train corresponding to said bearing rolling for a simulation time period, said intensity of an impulse on a bearing surface being determined as a function of an angle relative to a bearing fault;

modeling a movement of said bearing using said bearing model; and

determining a conditional indicator value associated with said bearing in accordance with said movement.

4. The method of claim 3, wherein said bearing frequency ratio corresponds to one of:

an inner race frequency and an outer bearing race frequency.

5. The method of claim 3, further comprising:

varying parameter values in determining conditional indicator values associated with different health classifications of said bearing.

6. The method of claim 5, further comprising:

estimating values associated with a gear noise;

estimating values associated with a bearing noise; and

estimating a condition indicator of a gear and bearing noise as a combined signal using said values associated with said gear noise and said bearing noise.

27. The method of claim 3, wherein said impulse train has a period dependent on a location of a fault.

29. The method of claim 3, wherein said at least one condition includes a fault condition associated with said bearing.

7. A method executed in a computer system for estimating a conditional indicator value associated with a bearing comprising:

determining a bearing frequency ratio for said bearing;

determining a periodic impulse in accordance with said bearing frequency ratio;

determining an intensity of an impulse on a bearing surface as a function of an angle relative to a bearing fault;

determining a decay of a unit impulse;

determining a movement of said bearing;

determining a conditional indicator value associated with said bearing in accordance with said movement;

varying parameter values in determining conditional indicator values associated with different health classifications of said bearing;

estimating values associated with a gear noise;

estimating values associated with a bearing noise;

estimating a condition indicator of a gear and bearing noise as a combined signal using said values associated with said gear noise and said bearing noise; and

determining said combined signal s(t) as;

s(t)=[d(t)f(t)q(t)a(t)]*e(t)*h(t)

where;

h(t) is a frequency response of a gear case;

d(t) is a signal associated with gear and shaft transmission error;

f(t) is a bearing frequency ratio;

q(t) is an amplitude at a particular time t,

a(t) is a cosine for one of an inner and outer race condition at a location theta at which an impulse is applied to said bearing; and

e(t) is a decay rate of unit impulse.

8. The method of claim 7, wherein h(t) is determined using one of:

a linear predictive coding (LPC) technique and modal hammer analysis.

9. The method of claim 7, further comprising:

determining a frequency spectrum of signals of s(t) as S(f) in the frequency domain by forming;

S(f)=[D(f)*F(f)*Q(f)*A(f)]E(f)H(f)

in the frequency domain.

10. A computer readable medium for estimating a conditional indicator value associated with a gear pair comprising machine executable code stored thereon causing a computer to perform:

modeling said gear pair as a damped spring model having a contact line between said gears;

determining a force, P, at a point of contact along said contact line causing linear and torsional response to each of said two gears in said gear pair;

determining a relative movement, d, of said gear pair, in accordance with said force, P, as a sum of four responses and a contact deflection, said relative movement d representing a gear model having two degrees of freedom, said contact deflection being due to a contact stiffness of a contact patch where two gears of said gear pair come into contact, and a linear damping coefficient of the contact patch; and

using said relative movement, d, in determining said conditional indicator value for transmission error associated with said gear pair.

11. The computer readable medium of claim 10, further comprising machine executable code stored thereon for:

varying parameter values in accordance with simulating different fault conditions; and

determining mean and threshold values for said different fault conditions.

23. The computer readable medium of claim 10, wherein a first of said four responses utilizes a linear damping coefficient of a pinion, a second of said four responses utilizes an angular damping coefficient of the pinion, a third of said four responses utilizes a linear damping coefficient of a wheel, and a fourth of said four responses utilizes an angular damping coefficient of the wheel.

24. The computer readable medium of claim 10, wherein P is an estimated value represented as P=(1/kp*rp)+(1/sp)+(1/sw)+(1/kwrw), and wherein

kp is the angular effective stiffness of a pinion,

rp is a radius of the pinion,

sp is a linear stiffness of the pinion,

sw is a linear stiffness of a wheel,

kw is an angular effective stiffness of the wheel, and

rw is a radius of the wheel.

25. The computer readable medium of claim 11, further comprising executable code stored thereon for:

using one or more manufacturer supplied data values to determine said parameter values corresponding to a modeled healthy state of said gear pair; and

modifying said one or more parameter values to determine additional parameter values corresponding to one or more of said different fault conditions.

26. The computer readable medium of claim 25, wherein one of said fault conditions corresponds to simulated alarm level having one or more of said parameter values estimated as a percentage of a manufacturer supplied value corresponding to a healthy state.

12. A computer readable medium for estimating a conditional indicator value associated with a bearing comprising machine executable code stored thereon causing a computer to perform:

modeling said bearing with a bearing model using a plurality of parameters including a bearing frequency ratio, a periodic impulse, an intensity of an impulse, and a decay of a unit impulse, wherein said bearing model is used to model at least one condition associated with said bearing, wherein said periodic impulse is determined in accordance with said bearing frequency ratio, said periodic impulse representing a modeled impulse train corresponding to said bearing rolling for a simulation time period, said intensity of an impulse on a bearing surface being determined as a function of an angle relative to a bearing fault;

modeling a movement of said bearing using said bearing model; and

determining a conditional indicator value associated with said bearing in accordance with said movement.

13. The computer readable medium of claim 12, wherein said bearing frequency ratio corresponds to one of:

an inner race frequency and an outer bearing race frequency.

14. The computer readable medium of claim 12, further comprising machine executable code stored thereon for:

varying parameter values in determining conditional indicator values associated with different health classifications of said bearing.

15. The computer readable medium of claim 14, further comprising machine executable code stored thereon for:

estimating values associated with a gear noise;

estimating values associated with a bearing noise; and

estimating a condition indicator of a gear and bearing noise as a combined signal using said values associated with said gear noise and said bearing noise.

28. The computer readable medium of claim 12, wherein said impulse train has a period dependent on a location of a fault.

30. The computer readable medium of claim 12, wherein said at least one condition includes a fault condition associated with said bearing.

16. A computer readable medium for estimating a conditional indicator value associated with a bearing comprising machine executable code stored thereon causing a computer to perform:

determining a bearing frequency ratio for said bearing;

determining a periodic impulse in accordance with said bearing frequency ratio;

determining an intensity of an impulse on a bearing surface as a function of an angle relative to a bearing fault;

determining a decay of a unit impulse;

determining a movement of said bearing;

determining a conditional indicator value associated with said bearing in accordance with said movement;

varying parameter values in determining conditional indicator values associated with different health classifications of said bearing;

estimating values associated with a gear noise;

estimating values associated with a bearing noise;

estimating a condition indicator of a gear and bearing noise as a combined signal using said values associated with said gear noise and said bearing noise; and

determining said combined signal s(t) as;

s(t)=[d(t)f(t)q(t)a(t)]*e(t)*h(t)

where;

h(t) is a frequency response of a gear case;

d(t) is a signal associated with gear and shaft transmission error;

f(t) is a bearing frequency ratio;

q(t) is an amplitude at a particular time t,

a(t) is a cosine for one of an inner and outer race condition at a location theta at which an impulse is applied to said bearing; and

e(t) is a decay rate of unit impulse.

17. The computer readable medium of claim 16, wherein h(t) is determined using one of:

a linear predictive coding technique and modal hammer analysis.

18. The computer readable medium of claim 16, further comprising machine executable code stored thereon for:

determining a frequency spectrum of signals of s(t) as S(f) in the frequency domain represented as

S(f)=[D(f)*F(f)*Q(f)*A(f)]E(f)H(f)

in the frequency domain.