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:

  1. A 0.9 kg rat in the box (real input).

  2. An empty box with a 0.9 kg bias on the scales due to a temperature change (modifying input).

  3. 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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