Method and apparatus for characterising instrument error

• US 10,533,833 B2
• Filed: 04/27/2015
• Issued: 01/14/2020
• Est. Priority Date: 05/06/2014
• Status: Active Grant

• Current Assignee: Taylor Hobson Limited (Ametek Incorporated)
• Original Assignee: Taylor Hobson Limited (Ametek Incorporated)
• Inventors: Xiao, Shaojun
• Primary Examiner(s): Lau, Tung S
• Application Number:
  US15/309,012
• Publication Number:
  US 20170067729A1
• Time in Patent Office: 1,723 Days
• Field of Search: None
• CPC Class Codes: G01B 21/042 Calibration or calibration artifacts G01B3/30, G01B9/02072 take precedence
• CPC Class Codes: G01B 5/008 using coordinate measuring machines
• CPC Class Codes: G01B 5/012 Contact-making feeler heads therefor
• CPC Class Codes: G01B 5/20 for measuring contours or curvatures
• CPC Class Codes: G01B 5/28 for measuring roughness or irregularity of surfaces

Abstract

A method for characterising instrument error in a surface measurement instrument, comprising obtaining first calibration measurement data representing a known surface form of a first reference object and obtaining second calibration measurement data representing a known surface form of a second reference object. At least a portion of the second calibration measurement data represents a measurement range that overlaps with at least a portion of a measurement range of the first calibration measurement data. A common error function is obtained that characterises the instrument error.

Claims

1. A method for characterising instrument error in a surface measurement instrument, the method comprising:

obtaining first calibration measurement data representing a known surface form of a first reference object;

obtaining second calibration measurement data representing a known surface form of a second reference object, wherein at least a portion of the second calibration measurement data represents a measurement range that overlaps with at least a portion of a measurement range of the first calibration measurement data, wherein the known surface form of the second reference object is different from the known surface form of the first reference object;

fitting a model of the known surface forms and of the expected form of the instrument error to both the first calibration measurement data and the second calibration measurement data together to determine;

first parameters describing the known surface form of the first reference object;

second parameters describing the known surface form of the second reference object; and

an error function representing the instrument error common to both the first calibration measurement data and the second calibration measurement data;

wherein the error function determined by said fitting characterises the instrument error, wherein the instrument error comprises at least one of error due to gauge non-linearity and error due to stylus tip geometry.

2. The method of claim 1 wherein fitting comprises selecting the first parameters, the second parameters, and the error function to reduce the differences between the model and both the first and second calibration measurement data.

3. The method of claim 1 wherein the error function comprises a function of position of a measurement probe of the measurement instrument.

4. The method of claim 1 wherein:

the first parameters comprise at least one of a location of the first reference object and a radius of curvature of the first reference object,

and the second parameters comprise at least one of a location of the second reference object and a radius of curvature of the second reference object.

5. The method of claim 1 wherein at least one of the first and second calibration measurement data represents a measurement path which is asymmetric with respect to the reference surface from which that measurement data was obtained.

6. The method of claim 1 wherein the error function comprises a linear sum of basis functions.

7. The method of claim 1 wherein the reference objects each comprise a curved surface, wherein the curved surface is at least part spherical.

8. The method of claim 1 wherein the model is based on

(X_ji−

a_j)²+(Z_ji−

b_j)²=R_j²

where,

Z_ji=A*Zm_ji+B*Zm_ji²+C*Zm_ji³,

X_ji=Xm_ji+D*Z_ji+E*Z_ji²+F*Z_ji³

X indicates the true position in a traverse direction of a measurement probe of the Measurement instrument,

Xm indicates the measured position in a traverse direction of a measurement probe of the measurement instrument,

Z indicates the position in a measurement direction of a measurement probe of the measurement instrument,

Zm indicates the measured position in a measurement direction of a measurement probe of the measurement instrument,

i=1, . . . , N, indicating N measurements along a measurement path,

j=1,2 indicating the reference object from which the measurement data was obtained,

A, B, C, D, E and F are calibration coefficients defining the error function, and

a, b, and R are the first (j=1) and second (j=2) parameters respectively.

9. The method of claim 1 wherein the error function is selected to model gauge non-linearity of the measurement instrument, wherein gauge non linearity comprises arcuate error.

10. A non-transitory computer readable medium comprising program instructions operable to program a processor to perform the method of claim 1.

11. A method of configuring a metrological apparatus comprising sending a signal to the metrological apparatus over a network, wherein the signal comprises machine readable instructions operable to program the apparatus to the method of claim 1.

12. A metrological apparatus calibrated according to the method of claim 1.

13. The method of claim 2 wherein reducing the differences comprises reducing a merit function,

wherein the merit function comprises a metric of the closeness of fit of the model to a data set comprising the first calibration measurement data and the second calibration measurement data, thereby to provide a metric of said closeness of fit which is common to both the first calibration measurement data and the second calibration measurement data.

14. The method of claim 3 wherein the instrument is configured to obtain measurement data indicating the position in a measurement direction of a surface by following a measurement path in a traverse direction, wherein the position of the measurement probe comprises position in at least one of the measurement direction and the traverse direction.

15. The method of claim 3 wherein the error function is also a function of a size of the measurement probe, and the method comprises determining the size based on fitting the model to both the first calibration measurement data and the second calibration measurement data, wherein the measurement probe comprises a tip and the size comprises the radius of the tip and wherein the known surface forms comprise curved surfaces and the radius of curvature of the known surface forms are known a priori.

16. The method of claim 4 wherein at least one of:

the location of the first reference object, the radius of curvature of the first reference object, the second reference object, and the radius of curvature of the second reference object are known a priori.

17. The method of claim 14 wherein the error function comprises a model of the error in the measurement direction as a function of measured position in the measurement direction.

18. The method of claim 14 wherein the error function comprises a model of the error in the traverse direction as a function of position in the measurement direction.

19. The method of claim 15 further comprising:

obtaining third calibration measurement data representing the known surface form of a third reference object;

determining measured surface data based on the third calibration measurement data and the error function;

determining a new size of the measurement probe based on differences between the measured surface data and the known surface form, and in the event that the differences exceed a selected threshold, repeating the determination of measured surface data based on the new size.

20. A surface measurement instrument comprising:

a measurement probe configured to follow a surface to be measured;

a measurement data obtainer configured to;

obtain first calibration measurement data representing the known surface form of a first reference object in a first measurement range to be calibrated;

obtain second calibration measurement data representing the known surface form of a second reference object in a second measurement range to be calibrated, wherein at least a portion of the second measurement range overlaps with at least a portion of the first measurement range, wherein the known surface form of the first reference object is different from the known surface form of the second reference object;

a data fitter configured to fit a model of the known surface forms and of the expected form of the instrument error to both the first calibration measurement data and the second calibration measurement data to determine;

first parameters describing the known surface form of the first reference object;

second parameters describing the known surface form of the second reference object; and

an error function representing the instrument error common to both the first calibration measurement data and the second calibration measurement data;

wherein the error function obtained by fitting the model to both the first calibration measurement data and the second calibration measurement data characterises the instrument error, wherein the instrument error comprises at least one of error due to gauge non-linearity and error due to stylus tip geometry.