data acquisition with labview

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Data Acquisition with LabVIEW: Introduction K. Craig 1

Data Acquisition with LabVIEW

Physical &Mathematical

Modeling

EngineeringMeasurement

EngineeringAnalysis &Computing

EngineeringDiscovery

Physic

sMat

hematics

SocialScience

Hands-On Minds-On

Technical

Communications

Teamwork Professionalism

Engineering System Investigation Process

Engineering System Design Process

MechanicalEngineering

Electrical &Computer

Engineering

Civil &EnvironmentalEngineering

BiomedicalEngineering

SelectionofEngineeringMa

terials P

ro

cessestoMakeProducts


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Other Components

Communications

ComputationSoftware, Electronics

OperatorInterface

Human Factors

ActuationPower Modulation

Energy Conversion

Physical SystemMechanical, Fluid,

Thermal, Chemical,Electrical, Mixed

InstrumentationEnergy Conversion

Signal Processing

ModernMultidisciplinary

Engineering

System

SimultaneousOptimization

of allSystem Components


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Anti-Aliasing

FilterSensor

Plant /

ProcessActuator

A/D

Converter

D/A

Converter

DigitalComputer

Sampling

System

Digital Set Point

Sampled &

Quantized

Measurement

Sampled & Quantized

Control Signal

Sampling

Switch

Power Domain

Information Domain


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Discretein

Time

Continuous

in

Time

Discrete

in

Amplitude D-D D-CContinuous

in

Amplitude C-D C-C

Signal Classification


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Introduction

Measurement System

This term measurement system includes all components in a chain

of hardware and software that leads from the measured variable to

processed data.

In a modern automobile there are as many as 4050 sensors

(measuring devices) used in implementing various functions

necessary to the operation of the car.

Knowledge of the instruments available for various measurements,

how they operate, and how they interface with other parts of thesystem is essential for every engineer.

Modern engineering systems rely heavily on a multitude of sensors

for monitoring and control to achieve optimum operation.


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Every application of measurement, including those not yet

invented, can be put into one of these three categories or some

combination of them:

Monitoring of processes and operations

Control of processes and operations

Experimental engineering analysis

All Engineers must be able to confidently, with minimal error,

and automatically measure physical properties with acomputer data acquisition system (DAQ).

Common Applications

Input to a design project

Evaluate a physical / mathematical model

Test a product before shippingquality control

Conserve energy; Understand and preserve the environment

Help an operator control a machine; Provide safe workplaces


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Why Automate Measurements?

Reduce the risk of errors

Remove humans from system doing repetitive tasks

Perform complex tasks that can not easily be done by hand

Automate systems

Avoid having to write new computer programs

Used extensively in industry

DAQ provides essential information for product testing and new

product design. DAQ also improves speed and precision by

controlling computer hardware with software.

Software design is extremely important to stop the spread of

poorly-programmed applications used in industry and research

today. These poorly-programmed applications run slow, have

errors, use too many computer resources, often cause energy

inefficiency, and are difficult to read, scale up, and maintain.


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Correct, successful DAQ applications require knowledge of

hardware and software.

The LabVIEW general graphical programming language is

an excellent environment for learning how to program

correctly, and it is more enjoyable than learning the syntax

and format common to text programming.

DAQ applications are not limited to making measurements.

They also include analyzing and presenting data and

performing real-time control.


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In making measurements, some things to consider

are:

What variables should be measured? Range and precision

of values to be measured?

How often does data need to be recorded? Timing of

measurements? How much data to collect?

Reliability of measurement system? Budget and system

cost?

What sensors are available?

What type of signals will be generated?

Where will the system be located?


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Error

Difference between true value and recorded value.

Two main sources:

Transducer / Instrument errors

Errors caused by the person taking the measurements

Described in two ways:

% accuracy = 100 * (error/true value)

% precision = 100 * (measurementmean ofn steady-state

measurements)/(mean ofn steady-state measurements)

Accuracy is the degree of closeness of a measured or

calculated quantity to its actual (true) value. Precision, also

called reproducibility or repeatability, is the degree to whichfurther measurements or calculations show the same or

similar results.

The results of calculations or a measurement can be accurate

but not precise, precise but not accurate, neither, or both.


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High PrecisionLow Accuracy

High AccuracyLow Precision


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Types of Transducer/Instrument Errors

HysteresisIf you make a set of sequential measurements

upscale and downscale and there is a difference in thevalues, the error is called hysteresis.

LinearitySome transducers/instruments have a linear

relationship between the property measured and their

output value. Linearity error occurs when the measuredvalue doesnt exactly fit the linear relationship.

RepeatabilityA repeatability error occurs when you

measure the same value repeatedly over time and the value

varies.

BiasSome transducers/instruments give consistently high

or low values, causing bias error.


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ResolutionErrors result from the analog-to-digital

conversion process in data acquisition.

Zero offsetIf the transducer/instrument should read zero,

but gives a nonzero value, it has a zero-offset error.

DynamicDynamic variables vary with time. An error

occurs when the dynamic response of the

transducer/instrument does not instantaneously capture the

variable value at the time the measurement should occur.

OverallThe overall error of a transducer/instrument is the

square root of the sum of all the instrument errors.


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Types of Errors Caused by the Person Taking the

Measurements

Readingreading the value incorrectly

Dynamic readinginability to read and record the data

quickly enough to capture the dynamic variations in the values

Interpolationincorrect interpolation between the markings

on a meter Misusing an Instrumentnot following the correct procedures

Misapplication of an instrumentusing the wrong

transducer/instrument for the measurement

Inadequate calibrationusing an instrument without knowingits errors

Recordingtyping or writing the measurement value

incorrectly


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Date Acquisition Process

Steps to Data Acquisition

1. Converter physical properties to electrical signals with

transducers

2. Convert electrical signals into digital data for computer

processing

3. Process digital data

4. Display and/or record test data


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Common transducers for measuring physical

properties


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Common Data Types


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LabVIEW Program

LabVIEW program to count the number of zeros in an

array


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Some other uses for LabVIEW

Can be used to create Virtual Instruments (VI) Virtual instruments can be easily transported unlike

traditional instruments

Can perform file input, processing, and output

Can develop graphical user interfaces


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Rotary Inverted

PendulumSystem

(See Video on D2L)


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LabVIEW Block Diagram


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LabVIEW Front Panel

data acquisition with labview

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