Modifying Inputs in Measurement Systems
About modifying inputs in measurement
systems
The fact that the static and dynamic
characteristics of measuring instruments are specified for particular
environmental conditions (e.g. of temperature and pressure) has
already been known. These specified conditions must be reproduced as
closely as possible during calibration exercises because, away from
the specified calibration conditions, the characteristics of measuring
instruments vary to some extent. The magnitude of this variation is
quantified by the two constants known as sensitivity drift and zero
drift, both of which are generally included in the published
specifications for an instrument. Such variations of environmental
conditions away from the calibration conditions are described as
modifying inputs to the system and are a further source of systematic
error. The environmental variation is described as a measurement
system input because the effect on the system output is the same as if
the value of the real input (the measured quantity) had changed by a
certain amount.
Without proper analysis, it is impossible to establish how much of an
instrument's output is due to the real input and how much to one or
more modifying inputs. This is illustrated by the following example
below.
Suppose that we have a small closed box weighing 0.1 kg empty which we
think contains a rat or a mouse. If we put the box on to bathroom
scales and observe a reading of 1.0 kg, this does not immediately tell
us what is in the box because the reading may be due to one of three
things:
A 0.9 kg rat in the box (real input).
An empty box with a 0.9 kg bias on the scales due to a temperature
change (modifying input).
A 0.4 kg mouse in the box together with a 0.5 kg bias (real +
modifying inputs).
Thus, the magnitude of any modifying input must be measured before the
value of the measured quantity (the real input) can be determined from
the output reading of an instrument.
In any general measurement situation, it is very difficult to avoid
modifying inputs, because it is either impractical or impossible to
control the environmental conditions surrounding the measurement
system. System designers are therefore charged with the task of either
reducing the susceptibility of measuring instruments to modifying
inputs or alternatively quantifying the effect of modifying inputs and
correcting for them in the instrument output reading.
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Measurement System Errors
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