CS代考 EEEE3089 Sensing Systems and Signal Processing Dr Richard

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Click to edit Master title style 01/02/2022 ‹#›

EEEE3089 Sensing Systems and Signal Processing Dr Richard

Module Overview What will we cover?

Lecture Material Overview info: Who we are and how to contact us Over view of Module content Assessment criteria and format of the exam

Who we are Dr Richard 53 (CW 2, week 7) A33a (week 11) A47 content Sensing Systems and Signal Processing Summary: This module covers a selection of topics where information is acquired from sensors and subsequently electronically processed. Applications: optical acoustic non-destructive evaluation medical and bio-photonics. Learning outcomes: By the end of this module, students should be able to: Describe the operating principles of a variety of practical electronic sensors. Select from options when designing an overall sensing system Describe signal processing techniques typically employed with sensors.

Module content {5C22544A-7EE6-4342-B048-85BDC9FD1C3A} Timetable Week Teaching Week Week Beginning Teaching Activities / Teaching Topics Assessment Release Assessment Submission Spring 20 1 31/01/22 L1 Module Introduction, NDE application, introduction to sensing, introduction to Matlab and formative exercise Formative Matlab exercise   21 2 07/02/22 L2 Time domain and frequency domain signals     22 3 14/02/22 L3 Introduction to sensors   CW1 Matlab exercises.   Formative assessment optional submission Monday 9am 23 4 21/02/22 L4 Sensing Temperature       24 5 28/02/22 L5 Sensing light       25 6 07/03/22 L6 Signal conditioning and acquisition,     26 7 14/03/22 L7 CW 2 introduction CW2 design exercise CW1 submission, Thursday 3pm 27 8 21/03/22 L8 Bio-imaging applications, ultrasound applications     28 9 28/03/22 L9 Sensing Displacement     29 10 04/04/22 L10 Sensing Force   CW2 submission, Thursday 3pm. Easter 30-32 – 11/04/22 – 25/04/22       Spring 33 11 02/05/22 L11 Sensing Chemicals, MRI     34 12 09/05/22 L12 Module Review, Revision, Example exam Q’s and solutions     Assessment 35   16/05/22-30/05/22      

Assessment This 10 credit module is assessed by examination and coursework: Coursework 50% Examination 50% Examination Information 2 hour exam Example exam papers are on Moodle. Last year’s is the correct format as previous years were different.

Assessment Formative Exercise: Matlab exercises 0% of module assessment:  Date provided to students: week 20 ( wb . 31/01/2022) Submission date:                week 22 (Monday 14/02/2022, 9am) Method of submission:         via Moodle Coursework Part 1: Matlab exercises 25% of module assessment:  Date provided to students: week 22 ( wb . 14/02/2022) Submission date:                week 26 (Thursday 17/03/2022,3pm) Method of submission:         via Moodle Coursework Part 2: Sensing system analysis report 25% of module assessment:  Date provided to students: week 26 ( wb . 14/03/2022) Submission date:               week 29 (Thursday 07/04/2022, 3pm) Method of submission:        via Moodle More details on the exercises and assessment criteria are given on moodle .

Sensing and signal processing What do these terms mean?

Questions what is ‘sensing’? what is ‘signal processing’?

Some definitions… A sensor is a device that responds to a physical stimulus. Sensitivity is the amount by which the output of a device responds to unit change of the stimulus. A signal conveys information about the behaviour or attributes of some phenomenon, e.g. how a stimulus to a sensor changes over time. Signal processing is the analysis, synthesis or modification of signals. A measurand is the physical quantity or property that is to be measured

Overview of generic sensing system Sensing System Measurand Sensing Unit Analogue Signal Processing ADC Digital Signal Processing Display / Utilising information

Overview of generic sensing system Measurands ….

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 Measurand Sensor Signal Conditioning Useful information {5C22544A-7EE6-4342-B048-85BDC9FD1C3A} 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

Signals Analogue signals , or continuous time signals , are quantities that vary continuously in time. For example the continuous voltage from a microphone. Discrete signals , or digital or sampled signals are usually versions of analogue signals that have been sampled at equal instants in time. The process of sampling an analogue signal to form a discrete signal is known as digitisation or analogue to digital conversion . A discrete signal is usually characterised by a sampling frequency and a resolution , or bit depth. Binary signals are pulse waveforms which exist in only two states, 0 and 1; for example a square wave.

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.

Signals Sampling frequency is the number of samples of the signal that are taken per unit time during the digitisation operation; the units are samples per second, often expressed as Hz, samples s -1 , or Ss -1 . Bit depth is the number of binary bits used to store the discrete signal, typically greater than eight and less than 64. Signal to noise Ratio SNR is the ratio of the power in the signal to the power of the noise in the system. This tells you how well you will be able to detect your signal. Accuracy is how close to the measured value is to the true value. Precision is how close repeated measurements are to each other.

Non Destructive Evaluation (NDE)

Non destructive evaluation (NDE) Several terms used in the field e.g. Non destructive testing (NDT), non destructive evaluation (NDE), Non destructive inspection (NDI) A decent definition is: “Non destructive testing is the process of inspecting, testing or evaluating materials, components or assemblies for discontinuities, or differences in characteristics without destroying the serviceability of the part or system.” ASNT.org visited 06-2018 Encompasses many different techniques: Magnetic Particle Testing (MT), Liquid Penetrant Testing (PT), Radiographic Testing (RT) Ultrasonic Testing (UT), Electromagnetic Testing (ET), Visual Testing (VT), Acoustic Emission Testing (AE), Guided Wave Testing (GW), Laser Testing Methods (LM), Leak Testing (LT), Magnetic Flux Leakage (MFL), Neutron Radiographic Testing (NR), Thermal/Infrared Testing (IR), Vibration Analysis (VA) For many different application areas:

Non destructive evaluation (NDE) An event that changed an industry : Sioux City Airline disaster Flight 232 took off from Stapleton airport, Colorado, July 19 th 1989 An hour into the flight they ‘lost’ engine 2 and control of the plane. Engine 2 was the tail mounted engine and when it disintegrated it damaged the 3 hydraulic systems for providing control of the plane – all at the same time – something that ‘shouldn’t’ have been possible. This left the pilots with no way to control the plane, they ended up using thrust from the remaining engines to steer the plane. Drop

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