Sensor
A sensor is a device that produces an output signal for the purpose of detecting a physical phenomenon.
In the broadest definition, a sensor is a device, module, machine, or subsystem that detects events or changes in its environment and sends the information to other electronics, frequently a computer processor.
Sensors are used in everyday objects such as touch-sensitive elevator buttons (tactile sensor) and lamps which dim or brighten by touching the base, and in innumerable applications of which most people are never aware. With advances in micromachinery and easy-to-use microcontroller platforms, the uses of sensors have expanded beyond the traditional fields of temperature, pressure and flow measurement,[1] for example into MARG sensors.
Analog sensors such as potentiometers and force-sensing resistors are still widely used. Their applications include manufacturing and machinery, airplanes and aerospace, cars, medicine, robotics and many other aspects of our day-to-day life. There is a wide range of other sensors that measure chemical and physical properties of materials, including optical sensors for refractive index measurement, vibrational sensors for fluid viscosity measurement, and electro-chemical sensors for monitoring pH of fluids.
A sensor's sensitivity indicates how much its output changes when the input quantity it measures changes. For instance, if the mercury in a thermometer moves 1 cm when the temperature changes by 1 °C, its sensitivity is 1 cm/°C (it is basically the slope dy/dx assuming a linear characteristic). Some sensors can also affect what they measure; for instance, a room temperature thermometer inserted into a hot cup of liquid cools the liquid while the liquid heats the thermometer. Sensors are usually designed to have a small effect on what is measured; making the sensor smaller often improves this and may introduce other advantages.[2]
Technological progress allows more and more sensors to be manufactured on a
Classification of measurement errors
A good sensor obeys the following rules:[4]
- 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. [citation needed]
- 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.
- Nonlinearityis 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 plotshowing 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, aliasingerrors 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
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
- 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
A chemical sensor is a self-contained analytical device that can provide information about the chemical composition of its environment, that is, a
Chemical sensor array
Biosensor
In
Neuromorphic sensors
MOS sensors
Biochemical sensors
A number of MOSFET sensors have been developed, for measuring
By the mid-1980s, numerous other MOSFET sensors had been developed, including the
Image sensors
MOS technology is the basis for modern
The MOS active-pixel sensor (APS) was developed by Tsutomu Nakamura at Olympus in 1985.[19] The CMOS active-pixel sensor was later developed by Eric Fossum and his team in the early 1990s.[20]
MOS image sensors are widely used in
Monitoring sensors
MOS monitoring sensors are used for
See also
References
- ISBN 978-0-86341-280-6The source states "controls" rather than "sensors", so its applicability is assumed. Many units are derived from the basic measurements to which it refers, such as a liquid's level measured by a differential pressure sensor.)
{{cite book}}
: CS1 maint: postscript (link - ^ ISBN 9781118638729.
- ISBN 978-81-7482-180-5.
- ^ PMID 31094032.
- S2CID 211012680.
- ISBN 978-1-118-35423-0.
- S2CID 219902328.
- PMID 11749297.
- PMID 26132346.
- S2CID 206542436.
- PMID 24091381.
- PMID 27065784.
- ^ "1960: Metal Oxide Semiconductor (MOS) Transistor Demonstrated". The Silicon Engine: A Timeline of Semiconductors in Computers. Computer History Museum. Retrieved August 31, 2019.
- ^ ISSN 0250-6874.
- ^ Chris Toumazou; Pantelis Georgiou (December 2011). "40 years of ISFET technology: From neuronal sensing to DNA sequencing". Electronics Letters. Retrieved 13 May 2016.
- ^ PMID 12375833.
- ^ ISBN 9783319490885.
- .
- S2CID 108450116.
- ^ Eric R. Fossum (1993), "Active Pixel Sensors: Are CCD's Dinosaurs?" Proc. SPIE Vol. 1900, p. 2–14, Charge-Coupled Devices and Solid State Optical Sensors III, Morley M. Blouke; Ed.
- ISBN 9783319093871.
- ISBN 978-3-642-68404-3.
- ^ Brain, Marshall; Carmack, Carmen (24 April 2000). "How Computer Mice Work". HowStuffWorks. Retrieved 9 October 2019.
- ^ "LiDAR vs. 3D ToF Sensors — How Apple Is Making AR Better for Smartphones". Retrieved 2020-04-03.
- ISBN 9781119107354.
- PMID 30424341.
- ISBN 978-1-4613-1639-8.
- ISBN 9781461416708.
Further reading
- M. Kretschmar and S. Welsby (2005), Capacitive and Inductive Displacement Sensors, in Sensor Technology Handbook, J. Wilson editor, Newnes: Burlington, MA.
- C. A. Grimes, E. C. Dickey, and M. V. Pishko (2006), Encyclopedia of Sensors (10-Volume Set), American Scientific Publishers. ISBN 1-58883-056-X
- Blaauw, F.J., Schenk, H.M., Jeronimus, B.F., van der Krieke, L., de Jonge, P., Aiello, M., Emerencia, A.C. (2016). Let’s get Physiqual – An intuitive and generic method to combine sensor technology with ecological momentary assessments. Journal of Biomedical Informatics, vol. 63, page 141–149.