unknown systematic errors and the method of least squares michael grabe

23
Unknown systematic errors and the method of least squares Michael Grabe alternative error model: true values and biases

Upload: sivan

Post on 11-Feb-2016

54 views

Category:

Documents


0 download

DESCRIPTION

Unknown systematic errors and the method of least squares Michael Grabe. alternative error model: true values and biases. Quantity to be measured true value. First Principle. Does metrology exist without a net of true values?. Not likely!. Impact of true values and biases - PowerPoint PPT Presentation

TRANSCRIPT

Page 1: Unknown systematic errors and the method of least squares Michael Grabe

Unknown systematic errors and the method of least squares

Michael Grabe

alternative error model: true values and biases

Page 2: Unknown systematic errors and the method of least squares Michael Grabe

2

Quantity to be measured true value

Does metrology exist without a net of true values?

First Principle

Not likely!

Page 3: Unknown systematic errors and the method of least squares Michael Grabe

3

Impact of true values and biases in least squares

Gauß-Markoff theorem Assessment of uncertainties

Traceability

Key Comparisons

Page 4: Unknown systematic errors and the method of least squares Michael Grabe

4

xAβ

Least squares adjustment

mrmm

r

r

aaa

aaaaaa

...............

...

...

21

22221

11211

A

r

...2

1

β

mx

xx

...2

1

xTraceability

Page 5: Unknown systematic errors and the method of least squares Michael Grabe

5

xAβ xAβ0

m

1iix

m1β

n

1lili xn

1x

Mean of means

averaging is permitted if and only if the respective true values are identical

m

2

1

x...xx

β

1...11

Page 6: Unknown systematic errors and the method of least squares Michael Grabe

6

mass

mg1kg0.25

mg1kg0.75

Adjustment ad hoc ?

Page 7: Unknown systematic errors and the method of least squares Michael Grabe

7

m

2

1

x...xx

empirical variance-covariance matrix

A different approach

Page 8: Unknown systematic errors and the method of least squares Michael Grabe

8

m

1iii xwβ

Mean of means

Page 9: Unknown systematic errors and the method of least squares Michael Grabe

9

xAβ xAβ

m

2

1

x...xx

x

Let the input data be arithmetic means

xAAAβ T1T

00 xAAAβ T1T

Page 10: Unknown systematic errors and the method of least squares Michael Grabe

10

Gauß-Markoff Theorem

The uncertainties are minimal...

...if the system has been weighted appropriately

Page 11: Unknown systematic errors and the method of least squares Michael Grabe

11

biases abolish the theorem ...

according to the GUM we should have

rmQE min rmQmin

but we encounter

Page 12: Unknown systematic errors and the method of least squares Michael Grabe

12

no more test of consistency

how to weight the system to minimize uncertainties?

Consequences ...

Page 13: Unknown systematic errors and the method of least squares Michael Grabe

13

more ... and of utmost importance:

reduce measurement uncertainties

weightings

shift estimators and

Page 14: Unknown systematic errors and the method of least squares Michael Grabe

14

a picture

reduction

before after

shift

true value

Page 15: Unknown systematic errors and the method of least squares Michael Grabe

15

Traceability:

vary the weights by trial and error ...

Assessment of uncertainties

Page 16: Unknown systematic errors and the method of least squares Michael Grabe

16

Key ComparisonNational Standards

1β 2β mβ...

true value

true valuetrue value

...

Page 17: Unknown systematic errors and the method of least squares Michael Grabe

17

Round RobinCalibration of a Travelling Standard T

...(1)T (2)T (m)T

(1)β (2)β (m)β...

T

Page 18: Unknown systematic errors and the method of least squares Michael Grabe

18

Key comparisons do more ...

m1,...,i;βTd (i)i

and the differences

Consider the grand mean

(i)m

1iiTwβ

KCRV

Page 19: Unknown systematic errors and the method of least squares Michael Grabe

19

m

1jjs,jis,iis,

m

1j

Tijj

2i

Pd

fwf2wf

wswsw2sn

1ntu

i

βuTuu 2(i)2d i

„consistent“ with

and look forid

(i) uβT where

Page 20: Unknown systematic errors and the method of least squares Michael Grabe

20

Problem:

In some cases the GUM may localize the true value of the travelling standard, in others not ...

whenShould we test (i)T against β

(i)T constributes to β ?

Page 21: Unknown systematic errors and the method of least squares Michael Grabe

21

Differences between KCRV and individual calibrations

1du

2du

mdu

...(2)T

β(m)T

(1)T

true valueKCRV

Page 22: Unknown systematic errors and the method of least squares Michael Grabe

22

Individual Calibrations

a horizontal line should intersect each of the uncertainties

...(1)T

(2)T

(m)Ttrue value

Page 23: Unknown systematic errors and the method of least squares Michael Grabe

23

β KCRV

(1)T

(2)T

...(m)T

true value

KCRV and individual calibrations