Dear colleagues, I have used the attached "Outlier Rejection
procedure" for over 20 years to detect outlier data from acquired
thermo-structural tests.
I have tried, unsuccessfully, offering the procedure to AEDC (Arnold
Engineering Development Center) because I use one of the two
Outlier Detection Methods but they have not shown interest.
Therefore, I am donating it to the PTC Community.
The method is a simple average of the of AEDC's and Chauvenet's
Outlier detection methods criteria resulting in the formula:
C_ABC(n) = (C(n)_AEDC + C(n)_Chauvenet(n)/2
Where "n = sample size"
Ultimately, entered the numerical results into TableCurve 2D
resulting in the formula provided in the attached workbook.
I have successfully used to determine the outlier of:
- Bolt torque (n < 16) in a pipe-to-pipe flange assembly.
- Metal temperature around turbojet engine inlets, n < 24.
- Metal temperature around turbojet engine nozzles, n < 18.
It is my hope that the community members will utilize the
ABC (AEDC-Banks-Chauvenet) Outlier Rejection Criterion.
to your particular applications.
Enjoy it ☺
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References
The proposed ABC Outlier Detection Criterion is a result of the
interest inspired by the reference article and reading about the
life Leonhard Euler converting me into a maven or mavin).
1) "The Unreasonable Effectiveness of Mathematics in the
Natural Sciences"- is a 1960 article by the physicist.
Eugene Wigner"
2) “A maven (also mavin) is a trusted expert in a particular field,
who to seeks pass knowledge on to others. The word maven
comes from Hebrew, and it means one who understands,
based on an accumulation of knowledge”
