IP Library Granted Patent US 8,649,642
Granted Patent B2
US 8,649,642 · App. 13/306,427 · Granted Feb 11, 2014

Methods and systems for predicting an optical fiber performance parameter

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Quick Facts
Patent No.
US 8,649,642
App. No.
13/306,427
Granted
Feb 11, 2014
Kind
B2
Abstract

A method for predicting an optical fiber performance parameter includes measuring N values for the optical fiber performance parameter at N stages during manufacture or installation of a first optical fiber, where N is an integer. A first set of correlation values is generated representing shifts in the measured optical fiber performance parameter values at the N stages. An installed value of the optical fiber performance parameter is estimated for a second optical fiber based on the first set of generated correlation values and at least one measured optical fiber performance parameter value associated with the second optical fiber.

Claims (46)

1. A method for predicting an optical fiber performance parameter, comprising:

measuring N values for the optical fiber performance parameter at N stages during manufacture or installation of a first optical fiber, where N is an integer;

generating a first set of correlation values representing shifts in the measured optical fiber performance parameter values at the N stages; and

predicting an installed value of the optical fiber performance parameter for a second optical fiber based on the first set of generated correlation values and at least one measured optical fiber performance parameter value associated with the second optical fiber.

2. The method of claim 1 , wherein the N stages during manufacture or installation of the first optical fiber comprise N stages at different moments in time.

3. The method of claim 1 , where the optical fiber performance parameter comprises polarization mode dispersion (PMD).

4. The method of claim 3 , wherein the PMD parameter is measured using one of: a Jones Matrix Eigenanalysis (JME) method, a wavelength scanning method, or an interferometric method.

5. The method of claim 1 , wherein the first set of correlation values comprises a first set of N correlation coefficients.

6. The method of claim 5 , wherein the first set of N correlation coefficients comprises a first set of N Pearson Product Moment correlation coefficients.

7. The method of claim 6 , further comprising:

calculating a square of each of the first set of N Pearson Product Moment correlation coefficients to determine a proportion of variance of the respective measurement explained by a preceding measurement.

8. The method of claim 1 , further comprising:

calculating a linear regression based on the first set of correlation values; and

determining a goodness of fit of the linear regression to evaluate a manufacturing or installation process.

9. The method of claim 8 , further comprising:

predicting the installed value of the optical fiber performance parameter for the second optical fiber based on the linear regression.

10. The method of claim 1 , further comprising:

identifying sensitive stages from the N stages based on the first set of generated correlation values;

generating a second set of correlation values based on the identified sensitive stages; and

predicting the installed value of the optical fiber performance parameter for the second optical fiber based on the second set of generated correlation values and the at least one measured optical fiber performance parameter value associated with the second optical fiber.

11. The method of claim 1 , wherein the first set of correlation values includes multi-dimensional correlations based on three or more optical fiber performance parameter values measured at three or more stages.

12. The method of claim 1 , further comprising:

generating a generic correlation value based on the first set of correlation values; and

estimating the value of the optical fiber performance parameter at an m th moment in time based upon the generic correlation, where m is an arbitrary integer.

13. The method of claim 1 , further comprising:

determining whether any of the N values of the optical fiber performance parameter meet or exceed N predetermined thresholds;

discarding the first optical fiber when any of the N values of the optical fiber performance parameter meet or exceed the N predetermined thresholds; and

analyzing the first optical fiber to determine a cause for failure.

14. The method of claim 1 , wherein the first set of correlation values are based on observations of a manner in which the optical fiber performance parameter varies over time.

15. A method for predicting an optical fiber performance parameter, comprising:

measuring N values for the optical fiber performance parameter at N stages during manufacture or installation of a first optical fiber, where N is an integer;

generating a first set of correlation values representing shifts in the measured optical fiber performance parameter values at the N stages; and

predicting a value of the optical fiber performance parameter for a second optical fiber at any stage during manufacture or installation of the second optical fiber based on the first set of generated correlation values.

16. The method of claim 15 , wherein the optical fiber performance parameter comprises polarization mode dispersion (PMD).

17. The method of claim 15 , wherein the N stages during manufacture or installation of the first optical fiber comprise N stages at different moments in time.

18. The method of claim 15 , further comprising:

calculating a linear regression based on the first set of correlation values; and

predicting the value of the optical fiber performance parameter for the second optical fiber based on the linear regression.

19. A method for predicting a value of a performance parameter, comprising:

measuring N values for the performance parameter at N stages during manufacture or installation of a device, where N is an integer;

generating a first set of correlation values representing shifts in the measured performance parameter values at the N stages; and

predicting another value of the performance parameter for a second device based on the first set of generated correlation values and at least one measured value of the performance parameter associated with the second device.

20. The method of claim 19 , further comprising:

calculating a linear regression based on the first set of correlation values;

determining a goodness of fit of the linear regression to evaluate a manufacturing or installation process; and

predicting the other value of the performance parameter for the second device based on the linear regression.

Assignments (6)
CORRECTIVE ASSIGNMENT TO CORRECT THE ASSIGNEE PREVIOUSLY RECORDED AT REEL: 032734 FRAME: 0502. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded Nov 28, 2017
From: VERIZON BUSINESS GLOBAL LLC
To: VERIZON PATENT AND LICENSING INC.
Reel/Frame 044626/0088 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 16, 2016
From: VERIZON PATENT LICENSING, INC.
To: CIENA CORPORATION
Reel/Frame 040054/0950 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 22, 2014
From: VERIZON BUSINESS GLOBAL LLC
To: VERIZON PATENT AND LICENSING INC.
Reel/Frame 032734/0502 →
MERGER Recorded Nov 30, 2011
From: MCI, INC.
To: MCI, LLC
Reel/Frame 027302/0727 →
CHANGE OF NAME Recorded Nov 30, 2011
From: MCI, LLC
To: VERIZON BUSINESS GLOBAL LLC
Reel/Frame 027302/0793 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 30, 2011
From: FEE, JOHN A.
To: MCI, INC.
Reel/Frame 027304/0957 →