A good sensor obeys the following rules: • it is sensitive to the measured property • it is insensitive to any other property likely to be encountered in its application, and • it does not influence the measured property. Most sensors have a
linear transfer function. The
sensitivity is then defined as the ratio between the output signal and measured property. For example, if a sensor measures temperature and has a voltage output, the sensitivity is constant with the units [V/K]. The sensitivity is the slope of the transfer function. Converting the sensor's electrical output (for example V) to the measured units (for example K) requires dividing the electrical output by the slope (or multiplying by its reciprocal). In addition, an offset is frequently added or subtracted. For example, −40 must be added to the output if 0 V output corresponds to −40 C input. For an analog sensor signal to be processed or used in digital equipment, it needs to be converted to a digital signal, using an
analog-to-digital converter.
Sensor deviations Since sensors cannot replicate an ideal
transfer function, several types of deviations can occur which limit sensor
accuracy: • Since the range of the output signal is always limited, the output signal will eventually reach a minimum or maximum when the measured property exceeds the limits. The
full scale range defines the maximum and minimum values of the measured property. • The
sensitivity may in practice differ from the value specified. This is called a sensitivity error. This is an error in the slope of a linear transfer function. • If the output signal differs from the correct value by a constant, the sensor has an offset error or
bias. This is an error in the
y-intercept of a linear transfer function. •
Nonlinearity is deviation of a sensor's transfer function from a straight line transfer function. Usually, this is defined by the amount the output differs from ideal behavior over the full range of the sensor, often noted as a percentage of the full range. • Deviation caused by rapid changes of the measured property over time is a
dynamic error. Often, this behavior is described with a
bode plot showing sensitivity error and phase shift as a function of the frequency of a periodic input signal. • If the output signal slowly changes independent of the measured property, this is defined as
drift. Long term drift over months or years is caused by physical changes in the sensor. •
Noise is a random deviation of the signal that varies in time. • A
hysteresis error causes the output value to vary depending on the previous input values. If a sensor's output is different depending on whether a specific input value was reached by increasing vs. decreasing the input, then the sensor has a hysteresis error. • If the sensor has a digital output, the output is essentially an approximation of the measured property. This error is also called
quantization error. • If the signal is monitored digitally, the
sampling frequency can cause a dynamic error, or if the input variable or added noise changes periodically at a frequency near a multiple of the sampling rate,
aliasing errors may occur. • The sensor may to some extent be sensitive to properties other than the property being measured. For example, most sensors are influenced by the temperature of their environment. All these deviations can be classified as
systematic errors or
random errors. Systematic errors can sometimes be compensated for by means of some kind of
calibration strategy. Noise is a random error that can be reduced by
signal processing, such as filtering, usually at the expense of the dynamic behavior of the sensor.
Resolution The
sensor resolution or
measurement resolution is the smallest change that can be detected in the quantity that is being measured. The resolution of a sensor with a digital output is usually the
numerical resolution of the digital output. The resolution is related to the
precision with which the measurement is made, but they are not the same thing. A sensor's accuracy may be considerably worse than its resolution. • For example, the
distance resolution is the minimum distance that can be accurately measured by any
distance-measuring devices. In a
time-of-flight camera, the distance resolution is usually equal to the
standard deviation (total noise) of the signal expressed in
unit of length. • The sensor may to some extent be sensitive to properties other than the property being measured. For example, most sensors are influenced by the temperature of their environment. ==Chemical sensor==