[SystemSafety] Systematic and random error in systems

[Brent Kimberley]

Assume you have a three element array.  Study begins at t=0; study concludes at t=1440.  element one is impacted randomly at time t+1000.  element two receives bias at time t+1001.  Element three is not impacted. Assuming the plant in question is ISO conformant, please tell me that these software calibration events are automatically detected.   

 On Monday, November 5, 2018 8:08 PM, Matthew Squair <mattsquair at gmail.com> wrote:
 

 Another way to view systematic error is that you are not directly measuring the parameter of interest but instead some analogue of it. 

Matthew Squair
MIEAust, CPEngMob: +61 488770655Email; Mattsquair at gmail.comWeb: http://criticaluncertainties.com
On 5 Nov 2018, at 3:59 am, Olwen Morgan <olwen at phaedsys.com> wrote:


 

  All, Picking up on something Martyn Thomas said a little way back;
  In metrology, random error is that kind of error that causes repeated measurements of a quantity to be dispersed about the true value. A systematic error is the kind of error that causes repeated measurements of a quantity to be displaced from the true value. Both kinds of errors can coexist in a single measuring system.
  Now, we know that the effects of software errors are systematic rather than random. Nevertheless, it is very easy to write, say as embedded code for a measuring instrument, software whose behaviour produces measurement errors that are indistinguishable by tractable experiment from random errors. This can be done by adding a pseudorandom quantity to the measured value before giving it as the output. If you choose the parameters of the pseudorandom number generator (PRANG) used, then you can make the output value of a measurement have virtually any form of distribution you like. Moreover, the only way to detect by experiment that the error is systematic rather than random is to run the PRANG through its whole cycle of values at least twice, so that the periodicity shows up. I'm not suggesting that people do this but it is, at least to me, a striking example of how careful we have to be in adapting the principles of physical measurement to software used in measuring instruments. 
  Olwen
  
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