Instrumentation Course 2001 Prof. G. Hall
Introduction
& Basic concepts
Purposes of course
Experiments in physics
References & sources
Basics: resistors, capacitors,
inductors, Thevenin & Norton
Circuit analysis, equivalent
circuits
Linear systems & superposition,
time invariant & (non-linear, non-time-invariant),
Definition of filter &
transfer function
Precision, Resolution, dynamic
range, units, dB, pole
Limits
Fourier
transforms
basic properties
impulse, convolution in time,
definitions, theorems, convolution
Parsevalís theorem
relation between impulse response
and transfer function
power spectral density, uncertainty
principle
applications
Sensors
& signals
Typical sensors (diode, photodiode,
GM tube, proportional gas detector, scintillator,
thermocouple, thermistor,Cerenkov,...
Some example applications:
particle identification by ToF & Cerenkov
Equivalent circuits
Typical signals. Lasers as
signal source
Linearity, non-ideal features
Operational
amplifiers
Basic principles & definition
Feedback - Inverting, non-inverting,
differentiator, integrator,
Practical examples ? control
systems,..
Amplifier
types
bipolar, FET, when to
use
principles of bipolar circuits
examples of MOS circuits
Impedances
& matching
When to match & mismatch
Transmission lines, optical
fibres, digital data transmission
Digital encoding, error correction,
entropy
Signals,
noise & noise reduction
Origins of noise, extrinsic
& intrinsic noise
Thermal, shot, 1/f noise,
noise spectral density, noise corner
Campbellís theorem, bandwidth
limiting
Noise in amplifiers, location
of noise sources, input equivalent noise, noise sources
Why white noise does not always
give rise to white noise spectrum in system
Noise in lasers, Noise figure
Noise reduction methods, ground
loops, inductive & capacitive pickup
Differential signals, Coaxial
shielding, grounding of amplifier in system
Digital
circuits
why digital? why not all digital?
gates, flip-flops, memory
analogue to digital conversion
, multi-range AD conversion, resolution, types,
components
discrete, FPGA, DSP, µprocessor
comparison
phase sensitive detection
Laplace
transforms
basic properties of
transforms
impulse, convolution in time,
definitions, convolution theorem
poles, stability, Nyquist
criterion
applications control by feedback
with d/dt and *dt
z-transform
Repetitive
& random signal processing
Counting systems, deadtime,
queuing
Sampling
& digital signal processing
Digital filters, FIR &
IIR filtering,
why canít all filters be digital?
advantages and drawbacks
equivalence to continuous
filters, weight function
Nyquist, aliasing
Systems?
Digital oscilloscope
Spectrum analyser
Revision
lecture (3rd term)