Sensors and network administering


How sensors work

A good sensor obeys the following rules:If the output signal slowly changes
1. the sensor should be sensitive to theindependent of the measured property,
measured propertythis is defined as drift.
2. the sensor should be insensitive toLong term drift usually indicates a slow
any other propertydegradation of sensor properties over a
3. the sensor should not influence thelong period of time.
measured propertyNoise is a random deviation of the
In the ideal situation, the outputsignal that varies in time.
signal of a sensor is exactlyHysteresis is an error caused by the
proportional to the value of thefact that the sensor not instantly
measured property. The gain is thenfollows the change of the property being
defined as the ratio between outputmeasured, and therefore involves the
signal and measured property. Forhistory of the measured property.
example, if a sensor measuresIf the sensor has a digital output, the
temperature and has a voltage output,signal is discrete and is essentially an
the gain is a constant with the unit [Vapproximation of the measured property.
K].The approximation error is also called
If the sensor is not ideal, severaldigitization error.
types of deviations can be observed:If the signal is monitored digitally,
The gain may in practice differ from thelimitation of the sampling frequency
value specified. This is called a gainalso causes a dynamic error.
error.The sensor may to some extent be
Since the range of the output signal issensitive for other properties than the
always limited, the output signal willproperty being measured. For example,
eventually clip when the measuredmost sensors are influenced by the
property exceeds the limits. The fulltemperature of their environment.
scale range defines the outmost valuesAll these deviations can be classified
of the measured property where theas systematic errors or random errors.
sensor errors are within the specifiedSystematic errors can sometimes be
range.compensated for by means of some kind of
If the output signal is not zero whencalibration strategy. Noise is a random
the measured property is zero, theerror that can be reduced by signal
sensor has an offset or bias. This isprocessing, such as filtering, usually
defined as the output of the sensor atat the expense of the dynamic behaviour
zero input.of the sensor.
If the gain is not constant, this isResolution
called nonlinearity. Usually this isThe resolution of a sensor is the
defined by the amount the output differssmallest change it can detect in the
from ideal behaviour over the full rangequantity that it is measuring. Often in
of the sensor, often noted as aa digital display, the least significant
percentage of the full range.digit will fluctuate, indicating that
If the deviation is caused by a rapidchanges of that magnitude are only just
change of the measured property overresolved. The resolution is related to
time, there is a dynamic error. Often,the precision with which the measurement
this behaviour is described with a bodeis made. For example, a scanning probe
plot showing gain error and phase shift(a fine tip near a surface collects an
as function of the frequency of aelectron tunnelling current) can resolve
periodic input signal.atoms and molecules.



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