Measured valueMeasured value

(1)

Development of Complex Curricula for Molecular Bionics and Infobionics Programs within a consortial* framework**

Consortium leader

PETER PAZMANY CATHOLIC UNIVERSITY

Consortium members

SEMMELWEIS UNIVERSITY, DIALOG CAMPUS PUBLISHER

The Project has been realised with the support of the European Union and has been co-financed by the European Social Fund ***

**Molekuláris bionika és Infobionika Szakok tananyagának komplex fejlesztése konzorciumi keretben

***A projekt az Európai Unió támogatásával, az Európai Szociális Alap társfinanszírozásával valósul meg.

PETER PAZMANY CATHOLIC UNIVERSITY

SEMMELWEIS UNIVERSITY

(2)

Peter Pazmany Catholic University Faculty of Information Technology

ELECTRICAL MEASUREMENTS

Introduction and principles of measurement

www.itk.ppke.hu

(Elektronikai alapmérések)

Bevezetés és a méréstechnika alapelvei

Dr. Oláh András

(3)

Electrical measurements: Introduction and principles of measurement

Outline

• Measurement in everyday life

• Pillars of the information technologies

• Course information

• History of measurements

• Trends in measurement technology

• Fundamentals and principles

• Modeling and measurements methods

• Structure of measuring systems

• The computer measuring systems (Labview)

(4)

Measurement in everyday life

• Measurement of ordinary people for every day

– “It is cold today” : it describes the result of measurement carried out by our senses (receptors). Such measurement is performed in a subjective way - another person could state in the same conditions that it is not cold. But generally we estimate the temperature by comparison with the temperature memorized as a reference one. Thus we performed the measurement.

– “I do not feel well today” : it describes the result of the analysis of the state of our organism. Our receptors tested the parameters: blood pressure, body temperature, pulse heart rate, level of adrenaline in blood, etc. as incorrect. The receptors (the sensors) determine the value of many quantities which are transmitted to the brain (central computer) as the electrical signals (current is about 100pA) by the interface consisting of billions of nervous fibers.

(5)

Measurement in everyday life (cont’)

• Goal of measurement: measurement is the process of gathering

• Information from physical world.

• Intuitive definition: measurement is estimation of the quantity of certain value (with known uncertainty) by comparison with the standard unit.

• Practically almost the whole activity of our lives is related to measurements we:

– constantly compare various objects – evaluate their properties

– determine their quantities.

(6)

Measurement in everyday life: an example

• Examples:

– While paying in cash at the supermarket.

– While listening to our favorite band at the rock concert.

– While choosing the color of the walls before painting.

• Fundamentals of colour vision:

– Physical colour = specific wavelengths of radiation (combination of pure spectral colours in the visible range)

– Psychophysical colour = Chromaticity = To achieve a standard, shared technical description of the perceptual effects of light stimuli on human observers, international organizations have developed a "standard observer". This is a hypothetical typical human visual system that is described in terms of equations relating its quantitative visual responses to measurable physical statistics of light stimuli. The descriptions are therefore "psychophysical".

(7)

Measurement in everyday life: an example (cont’)

Photometric quantities

Eyes Optic

nerves

Brain- Visual cortex Optical

lens

Optical

filter Optical sensor Optical

lens Optical sensor

(8)

• Colour: it is the visual perceptual property corresponding in humans to the categories called red, green, blue and others.

• Colourfulness: it is the difference between a colour against gray (eg.:

grayish pink)

• Lightness: is a property of a colour, or a dimension of a colour space, that is defined in a way to reflect the subjective brightness perception of a colour for humans along a lightness–darkness axis.

Eye sensitivity diagram. The colored vertical lines are the wavelengths of some common laser

colours. The yellow line is the 589nm sodium line.

Measurement in everyday life: an example (cont’)

http://en.wikipedia.org/wiki/File:Eyesensitivity.png

(9)

Measurement in everyday life: an example (cont’)

chromaticity space (CIE)

Comparative colour measurement (subjective)

Unknown light source Known light

source prism

(10)

Pillars of the information technologies

• Technology: electronic, optic, magnetic, algorithmic, …..

technologies advanced products, such as building blocks (e.g.:

processor, optical cable, magnetic storage, Fast Fourier Transformation, etc. …) and the blocks form complex systems (e.g.: computers, communication networks, server farms, etc.

…)

• Information sources: information is generated and utilized by IT tools (e.g.: speeches, images, papers, books, films, music, financial transactions, etc. …)

(11)

Pillars of the information technologies (cont’)

• Interfaces: among physical and digital worlds Ee.g.: sensors, Man Machine Communication interfaces, etc. )

• Signal porcessing: signal processing and evaluation by machine intelligence

• Infocommunications: information transfer, communication, preprocessing and presentation. (e.g.: GSM, broadcasting, speech synthesis, etc. …)

(12)

Which pillar is more important than the other?

Technologies

http://en.wikipedia.org/wiki/File:Rock_paper_scissors.jpg

(13)

Features of a succsessful computer-engineer

• He/she should possess a deep knowledge in his/her field of activity (q.v. pillar of information technology)

• He/she should be receptive to (all) new scientific achievements or products and also to altered opinions but also should stay critical evaluating them.

• An excellent/the favourable computer-engineer works in team.

He/she is competent not only in his/her own field of activitiy but also in the other team members’. An engineer is supposed to have a substantive opinion in consultations and to argue in emerging discussions.

• A fundamental tool/ source of knowledge in science is making experiments (performing measurements) and taking decisions in substantive arguements of technological field is in most cases measurement-based.

(14)

What is measurement techniques used for …

… in the molecular bionics faculty?

… in clinical practice ?

N. Szigeti-Csucs MD.

everyday routine of a Hungarian clinician

(15)

The (fundamental) role of the course Electric

measurements in training computer engineers at PPKU

• Acquiring pillars of knowledge is hard not only because of comnplexity but also because working principles of building blocks is not always easily sensible

• Measurement can make processes sensible which helps understanding the working principles before deep understanding of technical

• Don’t be afraid! Everyone will and should get used to the regime, the procedure the required discipline before starting work in major courses.

• Electrical measurement can aim at beauty of our profession, which help to understand and accept the hard work while attending the initial courses of computer engineering.

(16)

What does electrical measurement stands for?

• Principles and basics of electrical measurement

• Essential electronical knowledge

• Obtaining a primary routine in performing measurements

• Measuring elementary electrical quantities

• Fundaments of measuring non-electrical quantities (time, distance, geographical location)

• Elucidation of some basic problems in signal processing and circuit theory

• Structure of basic measurement devices (unique general instruments, devices connected to the computer, measurements utilizing a computer, virtual instruments)

• Medical electronical measuremnents, measurement of biological signals

(17)

Course Syllabus and Scheduling

1. Introduction and principles of measurement (Chapter 1)

– Focus of the course and pre requisites – History of measurements

– Fundamentals and principles

– Modelling and measurement methods

– Structure of measuring systems, compter measuring systems

2. Uncertainty of measurements (Chapter 2)

– Basic statistical terms and concepts – Interpretation of uncertainty

3. Measurement of voltage and time (Chapter 3)

– Measurement of voltage and current – Measurement of frequency and time – The ELVIS system

(18)

Course Syllabus and Scheduling (cont’)

4. Fundamentals of signal processing (Chapter 4)

– About the decibel

– Analog to Digital conversion (sampling, quantization) – Signal transformation

– The concept of noise

5. Positioning systems (Chapter 5)

– Positioning and localization methods

– Sattelite based positioning systems (GPS)

6. Theoretical approach to networks and system (Chapter 6)

– Kirchhoff circuit laws

– Network and system analysis

– Linear resistive and dynamic networks

(19)

Course Syllabus and Scheduling (cont’)

7. Semiconductors basics: diodes and transistors (Chapter 7)

– circuit model, characteristics and applications

→Midterm exam

8. Nonlinear resistive networks (Chapter 8)

– setting of the operation point

9. Logic system (Chapter 9)

– binary system and basic operation

10. Basics of microcontrollers (Chapter 10)

– Complex logic problems

– Fundamentals (structure and programming) of microcontroller

(20)

Course Syllabus and Scheduling (cont’)

11. Biological and medical measurements (Chapter 11)

→Final exam

Measurment Lab (Chapter 12)

– Labview (3x3) – ELVIS (2x3) – GPS (1x3) – Diode (1x3) – Transistor (1x3)

– Microcontroller (1x3)

– Medical measurements: blood pressure, respiration (2x3)

(21)

Course Information

Requisite:

• To pass the physics test;

• To complete each measurement task of the lab

– How to prepare for a measurement task? With the help of the instructions for the given measurement and with use of the related curriculum (??) knowledge. This letter is to be checked by mini tests.

– Missed measurement(s) can be fulfilled on the disposed extra lab (only once)

• Test grades should be at least

• Grading

– Practical grade: rounded grades from the tests before the measurements and the grade received for the measurement reports

– Final grade:

Round (1/2 x (1. Exam grade + 2. Exam grade ) + 1/2 x practical grade) Electrical measurements: Introduction and principles of measurement

(22)

Requirements of measurement reports

• Should include

– Place and date of measurement, names of the measuring team

– The title of the measurement , the list of the instruments/devices applied, the sheme of the measurement procedure if needed

– Results of the measurement (indicating the unit of the quantity !!) – Evaluation and interpretation of the measurement results

• Measurement report should be written in electronic form and shlould be sent as e-mail attachement to the adress always given in the syllabus of the measurement task. Subject is also given in the description. Should be sent not later then midnight of the day of measurement

• Copying or borrowing parts of others measurement results will lead to a disciplinary procedure

(23)

• From the very beginning of our civilization people tried to understand and comprehend the surrounding world.

• Art of measurements appeared in Egypt.

• Science of measurements apperaed by Greeks.

• The ancient wonders were not only designed, but accurate measurements were needed to implement them.

History of measurements: the ancient wonders

http://en.wikipedia.org/wiki/File:SevenWondersOfTheWorld.png

(24)

http://en.wikipedia.org/wiki/Pont_du_gard

History of measurements: the ancient Roman aqueduct

• Roman aqueducts were extremely sophisticated constructions.

• Pont du gard (year 19 BC)

– It is a 50 km long aqueduct that runs between Uzès and Nîmes.

– It was built with remarkably fine tolerances, and of a technological standard that had a gradient of only 34cm per km (3.4:10000), descending only 17 m vertically in its entire length of 50 km.

(25)

History of measurements: story of the chronometer

• The first European voyages of discovery, have made it increasingly important for ships' captains to be able to calculate their position accurately in any of the world's seas. With the help of the simple and ancient astrolabe, the stars will reveal latitude. But on a revolving planet, longitude is harder. You need to know what time it is, before you can discover what place it is.

• Main stages of time measurement:

– Sundial and water clock (from the 2nd millennium BC) – Hero's dioptra (1st century AD)

– The hour (14th century AD)

– Minutes and seconds (14th - 16th century AD) – Barometer (AD 1643-1646)

– Mercury thermometer (AD 1714-1742) – Chronometer (AD 1714-1766)

– Sextant (AD 1731-1757)

(26)

Sir Clowdisley is lost in a fog in the English Channel. He gathers the navigators of his fleet to get a definite fix on their location. Satisfied that they are safely off the coast of France, he orders a course home. When a sailor tries to warn him that he's in danger of wrecking on the Scilly Isles, the admiral orders the man hanged as a mutineer.

Hours later, his flagship and three other ships of his fleet smash into the rocks. He is swept ashore only to be murdered by a woman who wanted his emerald ring.

History of measurements: story of the chronometer (cont’)

http://en.wikipedia.org/wiki/File:Sir_Cloudesley_Shovell,_1650-1707.jpg

Sir Cloudesley Shovell (1650-1707)

Toulon Isles of Scilly

(27)

The British government, in 1714, sets up a Board of Longitude and offers a massive £20,000 prize to any inventor who can produce a clock capable of keeping accurate time at sea.

To win the prize a chronometer must be sufficiently accurate to lose or gain not more than three seconds a day a level of accuracy unmatched at this time by the best clocks in the calmest London drawing rooms.

The challenge appeals to John Harrison. It is nearly fifty years before he wins the money.

History of measurements: story of the chronometer (cont’)

John Harrison (1693-1776)

http://en.wikipedia.org/wiki/File:Harrison%27s_Chronometer_H5.JPG http://en.wikipedia.org/wiki/File:John_Harrison_Uhrmacher.jpg

(28)

History of measurements: Budapest (1980)

• It was built in 1980, Budapest

• Constructor: Peter Wellner, civil engineer Hídépítő Co. Recently known as Hídépítő Zrt. 1

• The legends:

– The cause of the failure is that a different point of reference was used while measuring elevation level (there is a difference as much as 0.675m between elevation measured with an Adrian and Baltic zero point

– One end of the overpass subsides more than the other because building materials were stolen from both parts, but not the same extent

(29)

History of measurements: Budapest (1980) (cont’)

• In fact:

– „When positioning, spanning and spudding steelcables it behaves like a rubber cable first bent then released: the cable would compress if let. This feature will gain pressure which is used for load-bearing. If a large force is loaded on the bridge before the jointing material can solidify, then the parts expand at the bottom and angle topwards.”

– They were ordered (by the management of the city) to hurry up with the works as tram service should be restored. This lead to the result, that the contractors have put the parts together not waiting for the jointing material to solidify”

(30)

The Mars Climate Orbiter was intended to enter orbit at an altitude of 140.5–150 km (460,000- 500,000 ft) above Mars. However, a navigation error caused the spacecraft to reach as low as 57 km (190,000 ft.)

The spacecraft was destroyed by atmospheric stresses and friction at this low altitude. The navigation error arose because Lockheed Martin, the contractors for the craft's thrusters, did not use SI units to express their performance

History of measurements: NASA spacecraft

http://en.wikipedia.org/wiki/File:Mars_Climate_Orbiter_2.jpg

Mars Climate Orbiter

~125 millió $

(31)

The concept of the measurement and measuring

• Measurement = obtaining information about the state of the process

– physical , chemical, biological, economical, social phenomenon

• Measuring = methods and tools

Transducer Signal

processor Physical

phenomenon

x(t) Sensor y(t)

Clear and known relationship

z(t) Essential features FEATURE EXTRACTION

Electrical signal

Computer→ processing + storage

(32)

Application of measurement techniques

Measuring Techniques

Production

Metrology

Measuring Techniques

Transport

Production

(33)

Traditional measuring system

• Most of them did not have output interfaces.

• Each instrument enabled the measurement of different signals.

• A typical researcher was surrounded by many instruments.

• The experiment required the activity and presence of a researcher.

(34)

Measuring system

Bosch Automotive Sensors 2002 Recently the measuring techniques changed significantly.

real revolution in measurements Informatics

Microelectronics Mechatronics Sensor technology

Interface systems

Signal processing techniques Digital signal processors

Virtual instruments

Widespread of computer

systems

Today, dozens of various sensors are installed in any new car

(35)

Computer measuring system

LabVIEW – National Instruments TestPoint – Capital Equipment Corp.

(36)

WSN based measuring system

(37)

• Processing unit – Microprocessor – Microcontroller

• Transceiver unit – Short range radio

• Sensing unit – Sensors – Actuators

– Location finding system

• Power supply subsystem – Battery

– DC-DC converter

System architecture of a canonical wireless sensor node

~20%

~50%

~30%

(38)

• The Bell’s law describes how computer classes form, evolve and may eventually die out. New classes create new applications resulting in new markets and new industries.

• A new class forms about every decade:

– mainframes (1960s) – minicomputers (1970s)

– personal computers evolving into a network enabled by LAN or Ethernet (1980s)

– web browser client-server structures enabled by the Internet (1990s)

– web services (2000s)

– small form-factor devices such as cell phones and other cell phone sized devices (2000)

– Wireless Sensor Networks (>2005)

• Home and body area networks will form by 2010

Wireless sensor networks (outlook)

Gordon Bell (1934-)

(39)

Wireless sensor networks (outlook)

• Many cheap nodes

– Wireless → easy to install

– Intelligent → collaboration and cooperation – Low-power → long lifetime

• Wireless networks characteristics

– Energy is the driving constraint – Data flows to centralized location

– Low per-node rates but tens to thousands of nodes

– Intelligence is in the network rather than in the devices

(40)

Wireless Sensor Networks: envisioned applications

• Smart homes/buildings

• Smart structures

• Search and rescue

• Homeland security

• Battlefield surveillance

• Event detection

• Agriculture

• Medical

Agriculture Urban Warfare

Fire Fighting Medical

Process Industry

AND MANY MORE….

(41)

Main trends in the measurements science

• Replacing analog devices with digital devices

• Automated computer based measuring systems instead of operator centered traditional measuring systems.

– „user friendly” software enabling the design to be made directly by end-users of the measuring instruments and even the whole measuring systems. These softwares mostly have simple graphical programming language. The most popular software of such type is LabVIEW proposed by National.

– Because the measuring device is inside the computer it is often called as a “virtual instrument”.

• Globalization of measurement science and techniques: measurements are performed by almost everyone (physicists, medical doctors, engineers, farmers, etc.). It is available for everyone to measure with better or worse results.

(42)

What is the role of engineering knowledge?

• Specialists are still needed, since:

– If we use incorrect model or methods, then one can usually obtain completely false result (eg.: the researcher was investigating an insect).

– Such good performances may lead to misunderstanding.

– Analysis of the measuring accuracy (crucial for correct measurements).

• Interdisciplinarity:

– Digital signal processing.

– Microcomputer applications.

– Microelectronics and nanotechnology.

– Signal analysis and transmission.

(43)

Principles of measurements

• Measurement equals to comparison

• Each measurement has some uncertainty!

• The measurement changes the investigated phenomenon! Fitting of the measurand and measurement system.

• Calibration and certification.

(44)

Measurement = comparision

• Goal of the measurement: determination the value of the measured quantity with appropriate precision.

• The task of the measurement: comparision between the measured value and measurement standard (etalon).

• The etalon is not always present! But it can be indirectly measured

by the use of a measuring instrument (which is calibrated via

traceability chain).

(45)

System of measurement

• Different systems of units are based on different choices of a set of fundamental units. Eg: Planck units (as one among systems of natural units)

– Speed of light (c), gravitational constant (G), Planck constant (h), Boltzmann constant (k), electric constant (ε₀)

http://en.wikipedia.org/wiki/Planck_units

(46)

International System of Units (SI)

• Metric system, Antoine-Laurent Lavoisier

– On 1 August 1793: the decimal metre is adopted – On 7 April 1795: the gram is adopted

• 1948, The 9

^th

General Conference on Wights and Measures (CGPM)

• 1954, The 10

^th

CGPM decided that international system should be derived from six base units

• 1960, The 11

^th

CGPM named the system the International System of Units, abbreviated SI

• 1971, The seventh base unit, the mole, was added by the 14

^th

CGPM

(47)

SI penetration

http://en.wikipedia.org/wiki/SI

(48)

SI base units

(49)

SI derive units

(50)

Measurement standards (or etalon) can be a physical measure, measuring instrument, reference material or measuring system intended to define, realize, conserve or reproduce a unit or one or more values of a quantity to serve as a reference.

For example, the unit of the quantity 'mass' is given its physical form by a cylindrical piece of metal of one kilogram, which represents the international standard, and gauge blocks represent certain values of the quantity 'length'.

Definition of etalon

http://en.wikipedia.org/wiki/File:Denmark’s_K48_Kilogram.jpg

(51)

Traceability

Traceability of measurement results on a material is pivotal to the use of this material. Indeed, the planning of the measurements related to the characterization of the material depends on the standard to which traceability should be established and the means by which traceability will be established. To be able to establish traceability of a value to a certified value of a stated reference material, all measurement results that are used for the assignment of this value (and its uncertainty) need to be traceable to this stated reference. Three different kinds of traceability can be envisaged:

• traceability to the international system of unit (SI);

• traceability to a method;

• traceability to an artefact (to a standard, to a particular instrument).

(52)

Measurement traceability chain

CIPM

International Committee for Weights and Measures

BIPM

International Bureau of Weights and Measures

National Metrology Institute

User calibrator Working standards

Secondary standards Primary National standard

Defination of SI unit International prototypes

Precision level/ Uncertainty

(53)

Estimation of error = measurement uncertainty

• Uncertainty is a parameter that characterises the dispersion of values.

• Example: If a value of a mess is givan as (1.24 ± 0.13) kg, the actual value is asserted as like to be somewhere between 1.11 kg and 1.37 kg. The uncertainty is 0.13 kg and we note that uncertainty, like standard deviation, is a positive quantity (an error may be positive or negative).

• We are unable to determine the true value of the measured quantity,

because the measurement is always performed with some

uncertainty. Therefore, we can state that the measurement without

the estimation of this uncertainty is worthless.

(54)

Each measurement has some uncertainty!

• ISO:„Guide to the expression of uncertainty in measurement”, 1993.

• Analysis of measurement uncertainty – Metrology

• The resultant uncertainty of measurement can comprise several components:

– corrections

– random uncertainty

– uncertainty related to the imperfect accuracy of measuring devices and methods

– uncertainty related to non-perfect model of investigated phenomenon – mistakes (validation could be effective).

(55)

Source of uncertainty

• Type-B uncertainties (Systematic or system errors)

– It will give exactly the same results.

– This type of uncertainties may be evaluated by calibration,

– A type of systematic errors is instrument error (calibration needed)

– The other type of systematic errors is method or model error (the instrument is not suitable or the measurement disturbs the measurend object)

• Type A uncertainties (random errors)

– Display error

– Chang in the environment of the measurement (temperature, voltage or pressure fluctuations)

– Noise, external interference

(56)

Type-A uncertainties

• When we repeat the measurement, we will obtain a different value.

The reason for this lack of perfect repeatability is that the instrument we use or the measurend, or both, will be affected by uncontollable and small changes in the environment or within the measurend itself. Such changes may be due, for example, to electrical interference, mechanical vibration or changes in temperature.

• Errors that fluctuate, because of the variabality in our

measurements even under what we consider to be the same

conditions, are called random errors.

(57)

Type-B uncertainties

• During any measurement, there will probably be an error that remains constant when the measurement is repeated under same conditions. An example of such an error is a constant offset in a measuring instrument.

• Examples of intentional change that may uncover a systematic error:

– Exchanging one instrument for another that is capable of the same accuraccy and preferably made by a different manufacturer.

– Having a different person perform the measurement.

– An established method of measurement and a novel method that promises higher accuraccy may give discrepant results, which will be interpreted as revealing a systematic error in the earlier method.

(58)

Evaluation of uncertainties

• Type A uncertainties are evaluated by statistical methods

– This kind of evaluation requires certain number (K) of measurements.

• Type B uncertainties are evaluated by non-statistical methods

– It may be determined by looking up specific information about a measurand such as that found in calibration report or data book.

• We can reduce costs of measuring procedure by decreasing the uncertainty but there occures the risk that the costs of incorrect decisions can raise higher, it can even cause a dangerous situtation. It is possible to establish the optimal value of uncertainty.

(59)

Fitting of the measurand and measurement system

• It is necessary to fit the instrument to the measurand.

• Example: voltage measuring by real voltmeter

U=U

^g

R

²

R

¹

+R

²

U’= U

^g

R

²

R

²

+

R

¹

+ R

¹

R

^m

R

²

R

1

R

²

U

^g

U U

^g

R

¹

R

2

U’

R

^m

(60)

Accuracy vs. precision

• A value obtained through measurement may or may not be close to the real value. In situations where we believe that the measured value is close to the real value, we say that the measured value is accurate.

• When values obtained by repeated measurements of a particular

quantity exhibit little variability, we say that those values are

precise.

(61)

Modelling

• Model = it seeks to represent empirical objects, phenomena, and physical processes in a logical and objective way (functional, physical, mathematical, etc. ... models).

• The model is characterized by its goodness ? (or its error).

• Necessary model: it can not be further reduced because of the intolerable error.it can not reduced…?

• Sufficient model: more complex models lead to unnecessary costs.

• Measurement planning= selecting the optimal model.

(62)

Modelling (cont’)

• Example: determining the distance between the Earth and Moon.

– 1. Model : The orb is point → the distance between the points!

– 2. Model: The orb is perfect sphere → distance between the centers of the spheres?

• Example: the model of resistance

– 1. Model:

– 2. Model:

i

R u=Ri

i

R L

dt L di Ri

u = +

(63)

Main methods of measurements

• Direct measurement method

• Indirect measurement method

• Differential measurement method

• Substitution measurement method

• Analogue and digital methods

(64)

Direct measurement method

G^x Gⁿ

Ux Un

N

In equilibrium: G

_x

=G

_n

The nullindicator show zero: U

_x

=U

_n

Weighing

Voltmeter

(65)

Indirect measurement method (cont’)

Notes:

• R

_x

=f(I

_x

) is known!

• Automatical weighing ← Feedback!

• Transient state!

(66)

Differential measurement method

Ux Un

V Um

U

_x

=U

_n

+U

_m

U

_m

<<U

_n

(67)

Substitution method

G^x G^e

k

¹

Gⁿ G^e

k

1

k

²

k

²

2

1

G k

k

G

_x

=

_e

G

_n

k

1

= G

_e

k

2

n

x

G

G =

(68)

Substitution method (cont’)

G^x Gⁿ

k

¹

Gn’ G^x

k

¹

k

²

k

²

1 2

k G k G

_x

=

_n

2 ' 1

k G k G

x

=

n

' n n

x

G G

G =

(69)

Calibration

• In order that an instrument or artefact should accurately indicate the value of a quantity, the instrument or artefact requires calibration. This procedure is essential for establishing the traceability of the instrument or artefact to a primary standard.

• Direct calibration by voltmeters:

Calibrator U

_r

V U

_m

Error= U

_m

-U

_r

(70)

Calibration (cont’)

• Indirect calibration by voltmeters:

Error= U

_xm

-U

_rm

Source U

_r

V U

_rm

V U

_xm

Source requirements:

• Wide voltage range

• Stability

• „Noiseless” signal

(71)

Self-calibration by substitution method

• Error of digital voltmeter:

Error of nullpoint (offset) Error of gain

Actual quantity Actual quantity

Measured value Measured value

theoretical correlation

Real correlation

theoretical correlation

Real correlation

(72)

Self-calibration by substituiton method (cont’)

In position 1: U

₁

=U

_o

A

In position 2: U

₂

=(U

_r

+ U

_o

)A In position 3: U

₃

=(U

_x

+ U

_o

)

A U

_o

2 1 U

_x

3 U

_r

U

₁

U

₃

U

₂

(73)

Self-calibration by substituiton method (cont’)

A U

_o

2 1 U

_x

3 U

_r

U

₁

U

₃

U

₂

3 equations,

Unknown: U

_x

, U

_o

, A

2 1

1 3

U U

r

x

−

= − No offset, no gain!

(74)

Some additional errors of digital voltage meter

Error of linearity Error of hysteresis

Measured value

Actual quantity

Measured value

Actual quantity

(75)

Structure of measuring system

• General purpose measurement devices (analog and digital)

• Specific purpose measurement devices (eg. biomedical )

• Computer based measurement and data aquisition systems

(76)

Structure of measuring system (cont’)

• Biomedical measurement devices

Pulse oximeter

Electrocardiograph (ECG) Electomyograph (EMG)

Electroencephalograph (EEG) Electrooculograph (EOG)

(77)

Computer measuring systems

• Real part - hardware

– Data acquisition board

– Real measuring instruments, etc.

• Virtual part - software

– Signal processing.

– Visualization.

– Graphical interfeces.

– Modifiable frontpanel.

– User friendly!

(78)

Computer measuring systems (cont’)

• Programs:

– VEE Pro – Agilent

– TestPoint – Capital Equipment Corporation – DasyLab Dasitec

– MATLAB Data Acquisition Toolbox – LabVIEW –National Instruments

(79)

LabVIEW of National Instruments

• National Instuments with LabVIEW program is a leader of graphical user friendly programming of virtual measuring instruments.

• LabVIEW is a programming system developed for data acquisition and processing.

• The LabVIEW designers developed special graphical programming language (G programming language) enabling users to work with such programs, even by not experienced in programming using higher level language, as for example C programming language.

• This language is platform neutral which means it should run on

any machine that has a compatible virtual machine

(80)

• Front panel for design the user interface

– Front panel input functions (controls):

pushbuttoms, indicators, etc.

– Front panel output functions: LEDs, displays, graphs, etc.

• Block Diagram for graphical programming

The main windows of LabVIEW

(81)

Live show: Design the front panel! Lets design…

• We need a buttom to control the amplitude.

• We need a buttom to control the frequency.

• We need an oscilloscope screen.

• We need analog and digital voltmeters screen

(82)

Live show: Design the block diagram !

• We need a signal generator.

• We need an effective value calculator.

• All these should be connected together.

(83)

What kind of tasks will be on the measurement practice?

• Everybody will get a simple task to solve it independently .

• With the help of the instructors everybody can construct and test the device.

• Second step is to measure real circuits simultaneusly with the use of virtual and real instruments.

• Basic concepts from the lecture will be checked on the practice.

(84)

Summary

• The distinguish of the everyday life activities and the measurement technique is very fluent and relative.

• At present, the measuring devices can be found almost everywhere.

• Measurement is a process of gathering information from phisical world.

• According to measurement there are three important terms: i) estimation, ii) standard unit, but there is a lack of a third, absolutely indispensable term –the accuracy of estimaton, or better iii) uncertainty of estimation.

• Today, it is not the knowledge preserved for a narrow group of engineers.

Measurements are performed by almost everyone. Therefore, the knowledge of the measurement principles is obligatory for all.

• By a computer measuring system we usually mean the set of tools, methods and operations (software and hardware) designed for realization of operations necessary to perform measurements.

• Next lecture: Uncertainty of measurements