Sampling Chapter 2 ME 392 Sampling Chapter 2 ME 392 30 January 2012 week 4 Joseph Vignola.

Slides:



Advertisements
Similar presentations
EET260: A/D and D/A conversion
Advertisements

Sensors and Actuators Chapter 4 ME 392 Sensors and Actuators Chapter 4 ME 392 February 13, 2012 week 5 Joseph Vignola.
Adam Diel.  In 1981 IBM PC 150 introduced the first PC Speaker.  Each game had to write support for it (sound cards were impractical during this time)
Analog and Digital Signals AD/DA conversion BME 1008 Introduction to Biomedical Engineering FIU, Spring 2015 Feb 5 Lesson 3.
Number Systems and Codes
Chapter 4: Representation of data in computer systems: Sound OCR Computing for GCSE © Hodder Education 2011.
Chapter 5-Sound.
Analog and digital data Skills: none IT concepts: analog to digital conversion, digital to analog conversion, sample rate, sample size, quality-file size.
Data Acquisition Concepts Data Translation, Inc. Basics of Data Acquisition.
Shuvra Das University of Detroit Mercy
Chapter 2 Digital data Ola A. Younis. Elements of digital media Symbols : representation for something else. Example: a group of letters often serve as.
SIMS-201 Characteristics of Audio Signals Sampling of Audio Signals Introduction to Audio Information.
IT-101 Section 001 Lecture #8 Introduction to Information Technology.
Continuous Time Signals A signal represents the evolution of a physical quantity in time. Example: the electric signal out of a microphone. At every time.
ME 392 Chapter 6 Data Processing ME 392 Chapter 6 Data Processing March 12, 2012 week 9 Joseph Vignola.
Bike3.ppt1 H167 Hands-on Lab LAB 4: Stress and Strain.
ME 322: Instrumentation Lecture 19
 Principles of Digital Audio. Analog Audio  3 Characteristics of analog audio signals: 1. Continuous signal – single repetitive waveform 2. Infinite.
Digital audio. In digital audio, the purpose of binary numbers is to express the values of samples that represent analog sound. (contrasted to MIDI binary.
Computer Based Data Acquisition Basics. Outline Basics of data acquisition Analog to Digital Conversion –Quantization –Aliasing.
LE 460 L Acoustics and Experimental Phonetics L-13
Introduction to Interactive Media 10: Audio in Interactive Digital Media.
ME 392 Chapter 8 Modal Analysis & Some Other Stuff April 2, 2012 week 12 Joseph Vignola.
ME 392 ME January 2012 Week 3 Joseph Vignola.
Engineering H192 - Computer Programming Gateway Engineering Education Coalition Lab 5P. 1Winter Quarter Stress and Strain Lab 5.
COMP Representing Sound in a ComputerSound Course book - pages
Transducers/Sensors Transducer/sensor converts a non- electrical quantity, measurand, into a related electrical output signal Ideally there is a linear.
Seismometry Seismology and the Earth’s Deep Interior Seismometer – The basic Principles u x x0x0 ugug umum xmxm x x0x0 xrxr uground displacement x r displacement.
Computer Some basic concepts. Binary number Why binary? Look at a decimal number: 3511 Look at a binary number: 1011 counting decimal binary
Announcements Chapter 11 for today No quiz this week Instructor got behind…. We'll be back in MGH389 on Friday.
Wireless and Mobile Computing Transmission Fundamentals Lecture 2.
ENGR 104: Data Acquisition Lecturers: Dr. Binh Tran Dr. Otto Wilson Jr. © The Catholic University of America Dept of Biomedical Engineering.
EE 211 Lecture 4 T. H. Ortmeyer Spring This week’s labs Grounding Lab Labview Tutorial.
LECTURER PROF.Dr. DEMIR BAYKA AUTOMOTIVE ENGINEERING LABORATORY I.
COSC 1P02 Introduction to Computer Science 4.1 Cosc 1P02 Week 4 Lecture slides “Programs are meant to be read by humans and only incidentally for computers.
Introduction to SOUND.
Digital Sound Actual representation of sound Stored in form of thousands of individual numbers (called samples) Not device dependent Stored in bits.
More Meaningful Jargon Or, All You Need to Know to Speak Like a Geek Sound.
Floyd, Digital Fundamentals, 10 th ed Slide 1 Digital Fundamentals Tenth Edition Floyd © 2008 Pearson Education Chapter 1.
Instrumentation Overview Spring 2012 The laboratory is a controlled environment where we can measure isolated physical phenomena with a view to eventual.
Resolve the vector into x & y components 40.0 m/s at 45 o SoW.
Student of the Week. Assessment Statements IB Topic 14.1., Analogue and Digital Signals Solve problems involving the conversion between binary.
The Discrete Fourier Transform
Resolve the vector into x & y components 40.0 m/s at 45 o SoW.
1 What is Multimedia? Multimedia can have a many definitions Multimedia means that computer information can be represented through media types: – Text.
Digital Audio I. Acknowledgement Some part of this lecture note has been taken from multimedia course made by Asst.Prof.Dr. William Bares and from Paul.
Chapter 1.3 Acceleration. Types of Acceleration  Acceleration is a vector quantity  Positive Acceleration  1. when change in magnitude and direction.
Analogue to Digital Conversion © D Hoult analogue signal © D Hoult 2011.
Characteristics of Instrumentation An instrument is a device that transforms a physical variable of interest (the measurand) into a form that is suitable.
Data Representation: Sound
EET 2259 Unit 12 Data Acquisition
Data representation – Sound.
COMPUTER NETWORKS and INTERNETS
Chapter 2 Data and Signals
Digital Communication
"Digital Media Primer" Yue-Ling Wong, Copyright (c)2013 by Pearson Education, Inc. All rights reserved.
Descriptive Statistics:
CS 4594 Data Communications
EET 2259 Unit 12 Data Acquisition
Data Representation Keywords Sound
Analogue to Digital Conversion
MECH 373 Instrumentation and Measurements
Chapter 4: Representing sound
Representing Sound 2.6 – Data Representation.
LECTURE 18: FAST FOURIER TRANSFORM
Data Acquisition (DAQ)
Data Representation Chapter 2 Computer HW (Von Neumann Model) Program
Analog to Digital Encoding
Recap In previous lessons we have looked at how numbers can be stored as binary. We have also seen how images are stored as binary. This lesson we are.
LECTURE 18: FAST FOURIER TRANSFORM
Presentation transcript:

Sampling Chapter 2 ME 392 Sampling Chapter 2 ME January 2012 week 4 Joseph Vignola

Assignment 2 Assignment 2 was good I think most people are getting the hang of LabVIEW

Assignment 2 Assignment 2 was good I think most people are getting the hang of LabVIEW You where asked to average noisy data Send and receive it through the BNC 2120 box And write it to have file

Assignment 3 Assignment 3 is about Matlab acquisition

Assignment 3 Assignment 3 is about Matlab acquisition For this one you are being asked to send and receive date through the microphone and headphone jack that are on all modern PCs and Macs. Also you are asked to use Matlab’s handle graphs This assignment requires a little bit of explanation in the write-up

Assignment 3 Assignment 3 is about Matlab acquisition The Matlab notes can be found on the class webpageclass webpage

Measuring Some Changing Quantity In a lot of engineering problem we need to measure some quantity that changes over space or time.

Measuring Some Changing Quantity In a lot of engineering problem we need to measure some quantity that changes over space or time. Think about how the temperature outside changes

Measuring Some Changing Quantity In a lot of engineering problem we need to measure some quantity that changes over space or time. Think about how the temperature outside changes We can think about sampling the temperature every so often and writing it down

Measuring Some Changing Quantity In a lot of engineering problem we need to measure some quantity that changes over space or time. Think about how the temperature outside changes We can think about sampling the temperature every so often and writing it down

Measuring Some Changing Quantity In a lot of engineering problem we need to measure some quantity that changes over space or time. Think about how the temperature outside changes We can think about sampling the temperature every so often and writing it down

Measuring Some Changing Quantity In a lot of engineering problem we need to measure some quantity that changes over space or time. Think about how the temperature outside changes We can think about sampling the temperature every so often and writing it down

Measuring Some Changing Quantity The temperature or any quantity can also change spatially

Measuring Some Changing Quantity For our measurements we will be sampling quantities like acceleration, force, pressure at rates somewhere in the thousands of samples per second range.

Measuring Some Changing Quantity For our measurements we will be sampling quantities like acceleration, force, pressure at rates somewhere in the thousands of samples per second range. Rather then looking at a thermometer or a pressure gauge and writing down the temperature or pressure

Measuring Some Changing Quantity For our measurements we will be sampling quantities like acceleration, force, pressure at rates somewhere in the thousands of samples per second range. Rather then looking at a thermometer or a pressure gauge and writing down the temperature or pressure

Measuring Some Changing Quantity For our measurements we will be sampling quantities like acceleration, force, pressure at rates somewhere in the thousands of samples per second range. Rather then looking at a thermometer or a pressure gauge and writing down the temperature or pressure

Measuring Some Changing Quantity For our measurements we will be sampling quantities like acceleration, force, pressure at rates somewhere in the thousands of samples per second range. Rather then looking at a thermometer or a pressure gauge and writing down the temperature or pressure We use sensors that produce voltage signal that is related to the quantities we are interested in

Measuring Some Changing Quantity For our measurements we will be sampling quantities like acceleration, force, pressure at rates somewhere in the thousands of samples per second range. Rather then looking at a thermometer or a pressure gauge and writing down the temperature or pressure We use sensors that produce voltage signal that is related to the quantities we are interested in And digitally record the measurements on the computer at a regular interval

Sampling Frequency The time between measurements is called the sampling interval, and is generally measured in seconds, ms, micro sec, ns, ps.

Sampling Frequency The time between measurements is called the sampling interval, and is generally measured in seconds, ms, micro sec, ns, ps. The sampling frequency is the reciprocal of the sampling interval and is the number of samples per second Memorize this formula

Sampling Frequency The time between measurements is called the sampling interval, and is generally measured in seconds, ms, micro sec, ns, ps. The sampling frequency is the reciprocal of the sampling interval and is the number of samples per second Sampling frequency is described in Hertz. For example a digital audio is generally sampled at 44,100Hz or 44.1kHz

Digitizing a Continuous Signal Taken from Bishop

Digitizing a Continuous Signal You don’t have any information about what happens between samples when a continuously varying signal is digitized Taken from Bishop

Digitizing a Continuous Signal You don’t have any information about what happens between samples when a continuously varying signal is digitized You would like to know that the assumption “not much interesting” happened between samples is ok Taken from Bishop

Digitizing Levels Digitizers discritize signal to a signal to a finite number of levels within a range.

Digitizing Levels Digitizers discritize signal to a signal to a finite number of levels within a range. The number of levels always 2 to some power

Digitizing Range Digitizers discritize signal to a signal to a finite number of levels within a range. The range limits the largest and smallest signal you can capture

Dynamic Range smallest increment of voltage change that can be resolved by a digitizer is referred to the code width

Dynamic Range smallest increment of voltage change that can be resolved by a digitizer is referred to the code width The ratio of the total voltage range to the code width is the called the dynamic range.

Dynamic Range smallest increment of voltage change that can be resolved by a digitizer is referred to the code width The ratio of the total voltage range to the code width is the called the dynamic range. The dynamic range equal to

Dynamic Range smallest increment of voltage change that can be resolved by a digitizer is referred to the code width The ratio of the total voltage range to the code width is the called the dynamic range. The dynamic range equal to

Matlab and LabVIEW There are a lot of digital recording tools these days In this class we will mostly use LabVIEW BNC 2120

Matlab and LabVIEW There are a lot of digital recording tools these days In this class we will mostly use LabVIEW but you can also use Matlab by way of the headphone outputs and the Microphone inputs.

Time Vector In Matlab you will have to make a time vector to plot of audio signals. This is a vector the same length was the data that starts at zero. If the sampling frequency was 10kHz (10,000 samples per second) t = [0, , , ,…]

Matlab Handle Graphics Matlab has a hierarchal system that lets you control all aspects of a plot. This and other helpful things are described in the Matlab notes on the class webpageclass webpage