Main Title Slide
Sensing Systems and Signal Processing
Dr Richard
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Overview of generic sensing system
Sensing System
Sensing Unit
Analogue Signal Processing
Digital Signal Processing
Display / Utilising information
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Overview of generic sensing system
Sensor – detect a physical quantity and convert the information to electrical signal
Transducer – convert energy from one form to another – e.g. pressure into electrical,
Sensors are transducers, but transducers are more than just sensors. They usually have signal conditioning circuits built in.
Transducer
Signal Conditioning
Useful information
Measurand Examples
Mechanical Force, Pressure, Stress, Strain, Mass, Density, Moment, Torque, Viscosity, Stiffness Roughness, Velocity, Acceleration, Position.
Optical Wave, Amplitude, Phase, Polarisation, Spectrum
Electrical Charge, Current, Potential, Potential Difference, Electric Field, Conductivity, Permittivity
Acoustic Wave Amplitude, Wave Velocity, Frequency
Thermal Temperature, Heat Flux, Specific Heat, Thermal Conductivity
Chemical Components, Concentration
Radiation Type, Energy, Intensity
Biological Biomas, Concentration, States,
Magnetic Magnetic Field, Magnetic Flux, Permeability
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We’ve looked at a range of measurands and different ways to measure them:
Mechanical – Motion / Position / Force
Optical – Photodiodes and low light situations
Acoustic – Surface wave velocity, amplitude and frequency measurements
Thermal – Thermo-resistive and thermo-electric
Chemical – Various methods
Biological – Anti body anti gen binding
Magnetic – Hall effect and LVDTs
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Mechanical – Displacement / motion
Ferromagnetic core moves in and out ∆x
2 PD 90 degree offset
Capacitive
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Mechanical – Force
Acceleration
D = electric displacement [C/m2]
d = piezoelectric coefficient [C/N]
T = stress [N/m2]
= permittivity [F/m]
E = Electric field [V/m]
Piezo-electric
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Sensing – Light
Photodiodes
https://www.hamamatsu.com/preview/en/images/xx_pmt_01/img03.png
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Sensing – Light
Optical fibers
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Sensing – Acoustics
http://www3.gehealthcare.com.au/en-au/products/categories/ultrasound/ultrasound_probes
Piezoelectric Ultrasound transducers (NDE) convert electrical signals into vibrations. Used in medical ultrasound imaging
NDE technique – Laser generation and laser detection of ultrasound for characterisation of material properties
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Sensing – Temperature
Resistance Temperature Detectors
when is 0ºC
Thermistors
=3435 = 10Kohm at 25
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Sensing – Temperature
temperature
Reference Junction
Copper wire
Voltage out goes to measuring circuit
Thermo-couple
σ = 5.670367×10−8 W⋅m−2⋅K−4
emissivity – efficiency of the surface of a material to emit energy as thermal radiation.
Type Materials S (μV/K)
E Chromel-Constantan 60
J Iron-Constantan 51
T Copper-Constantan 40
K Chromel-Akumel 40
N Nicrosil-Nisil 38
S Pt(10%Rh)-Pt 11
B Pt(30%Rh)-Pt (6%Rh) 8
R Pt(13%Rh)-Pt 12
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Sensing – Chemical
Affinity Interactions
https://bio.libretexts.org/Bookshelves/Microbiology/Book%3A_Microbiology_(Boundless)/11%3A_Immunology/11.05%3A_The_Adaptive_Immune_Response/11.5A%3A_Humoral_Immune_Response
Nucleic Acid
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Sensing – Chemical
http://webphysics.iupui.edu/webscience/bio_archive/goodfor3.html
Blausen.com staff (2014). “Medical gallery of Blausen Medical 2014”. WikiJournal of Medicine 1 (2). DOI:10.15347/wjm/2014.010. ISSN 2002-4436. – Own work, CC BY 3.0, https://commons.wikimedia.org/w/index.php?curid=29738536
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Sensing – Biological
Surface plasmon resonance – anti-body anti-gen binding for protein concentration
Gas/ solution
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Sensing – Magnetic
Hall device
Hall effect devices
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Classifying sensors
There are a number of different ways to classify different types of sensors. These could include:
The type of signal produced:
Analog sensors produce a signal that is continuous in both magnitude and temporal (spatial) content. Most physical measurands are analogue.
Digital sensors produce an output in discrete steps or states. Digital signals are typically more repeatable, reliable and easier to transmit.
The power requirements of the device:
Passive device directly generate an electrical signal in response to an external stimuli. The output signal power comes from the stimulus. (Thermocouples Piezoelectric sensors)
Active sensors require an external power supply or an excitation signal for their operation. The output signal power comes from the power supply. (Thermistors, Chemo-resistors)
The type of the Measurand
mechanical / thermal / magnetic etc (see table)
Input/output relationship:
the order of the relationship – linear, quadratic, logarithmic.
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Classes of Signals
Periodic signals repeat, such as a fixed frequency sine wave which is continuous over all time.
Aperiodic signals have no observable periods but may not be random.
Deterministic signals have a structure that when analysed allows one to predict or determine the future course of the signal.
Random signals have no structure, but they do have properties. They are indeterministic in that the data could have occurred in any order and the signal would not appear to be different.
Stochastic signals combine both deterministic and random components. Most real engineering signals fall into this class because we have the ‘useful’ components of the signal with unwanted electronic noise superimposed.
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Signal Conditioning
Next Stage
Conversion
Amplification
Signal conditioning
Anything you need to do to get the signal into the right form for subsequent processing comes under signal conditioning.
Linearization – if the sensor produces a nonlinear output you may deal with this here, these days this tends to be done in software
Amplification – to get the signal big enough for the next stage
Filtering – to remove out of band noise or drift.
Other things: Electrical isolation, Power to the sensor (excitation) and monitoring, conversion (current to voltage).
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Data Acquisition
DAQ – Data Acquisition
Not covered in detail but they do have specifications that we care about if we wish to interface to them.
Input range – signal range required, might be programmable, or fixed. +/-1V +/-5V etc.
Bit depth – how many bits are used to represent the signal, 8,12,16 bits etc.
Sample rate – what the sampling frequency range is , 100K, 1M Sa/s
Input impedance – low or high input impedance, typically 50Ohm or High Z.
Dynamic range – essentially the number of bits and the full scale
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and Shot noise
Total noise and NEP
IN = (IS2 + IJ2)0.5
NEP = IN / R(λ)
IJ = (4.k.T.B / Rd)0.5
IJ = Johnson noise current (Arms)
k = Boltzmann’s constant (1.33 x 10-23 JK-1)
T = absolute temperature (K)
Rd = shunt resistance (Ω)
IS = (2.e.iD.B)0.5
IS is the shot noise current (Arms)
e = 1.6 x 10-19 C is the electronic charge
iD = dark leakage current (A)
B = system bandwidth (Hz)
Quantisation Error
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Averaging – The noise reduces by square root of the averages used.
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Signal Processing
Signal processing
Time domain
Correlation
Convolution
Frequency domain
Interpolation (via zero padding)
Convolution
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Using information
https://www.embedded.com/design/system-integration/4028129/ Accelerometers-and-free-fall-detection-protects-data-and-drives
Mammogram. Credit: Blausen.com staff. “Blausen gallery 2014”. Wikiversity Journal of Medicine. DOI:10.15347/wjm/2014.010. ISSN 20018762. CC BY 3.0
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