Branson Krautkramer MIC 10, Руководство пользователя

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12.4 Notes on statistical evaluation
The MIC 10 offers you the opportunity to print the fol-
lowing statistical data into a report:
–
maximum value
–
minimum value
–
average value (is also displayed)
–
absolute and relative range
–
absolute and relative standard deviation
–
minimum material thickness
How this information is printed has been covered in
Chapter 7.1
Printing data . The average value can be
continuously displayed during the measurement and
can also be recalled after termination of the measure-
ment set.
Each measurement has a certain amount of inaccu-
racy. A measuring error includes the following individ-
ual errors:
•
The basic measurement inaccuracy of the applied
testing method
•
The usage of the probes
•
The preparation of the test material (surface or heat
treatment)
•
The homogeneity of the material
•
External influences ((dirt accumulation, moisture,
temperature)
The statistical evaluation is to support your measure-
ment assessments and help you to make a clear deci-
sion about the quality of the tested material. The most
decisive information is derived from the standard devi-
ation; it is the best indicator of the quality of a meas-
urement set.
The average value of a measurement set becomes
more accurate the more measurements you make. On
the other hand, the more single measurements you
make the more measurements can go wrong (mis-
measurements). This is why the difference between
minimum and maximum value is not suited as a re-
liable indicator for the evaluation of a measurement
set which goes beyond 12 measurement points.
Appendix
Notes on statistical evaluation
12-6 Issue 08, 08/01 Krautkrämer MIC 10
12.4 Notes on statistical evaluation
The MIC 10 offers you the opportunity to print the fol-
lowing statistical data into a report:
–
maximum value
–
minimum value
–
average value (is also displayed)
–
absolute and relative range
–
absolute and relative standard deviation
–
minimum material thickness
How this information is printed has been covered in
Chapter 7.1
Printing data . The average value can be
continuously displayed during the measurement and
can also be recalled after termination of the measure-
ment set.
Each measurement has a certain amount of inaccu-
racy. A measuring error includes the following individ-
ual errors:
•
The basic measurement inaccuracy of the applied
testing method
•
The usage of the probes
•
The preparation of the test material (surface or heat
treatment)
•
The homogeneity of the material
•
External influences ((dirt accumulation, moisture,
temperature)
The statistical evaluation is to support your measure-
ment assessments and help you to make a clear deci-
sion about the quality of the tested material. The most
decisive information is derived from the standard devi-
ation; it is the best indicator of the quality of a meas-
urement set.
The average value of a measurement set becomes
more accurate the more measurements you make. On
the other hand, the more single measurements you
make the more measurements can go wrong (mis-
measurements). This is why the difference between
minimum and maximum value is not suited as a re-
liable indicator for the evaluation of a measurement
set which goes beyond 12 measurement points.
Appendix
Notes on statistical evaluation
12-6 Issue 08, 08/01 Krautkrämer MIC 10