APPENDIX A-5 THE CORRESPONDING FREQUENCY DOMAIN VALIDATION. APPENDIX A-5 shows plots for the corresponding time domain validation response

Size: px
Start display at page:

Download "APPENDIX A-5 THE CORRESPONDING FREQUENCY DOMAIN VALIDATION. APPENDIX A-5 shows plots for the corresponding time domain validation response"

Transcription

1 APPENDIX A-5 THE CORRESPONDING FREQUENCY DOMAIN VALIDATION APPENDIX A-5 shows plots for the corresponding time domain validation response records illustrated in chapter 7 for further validation. The following pattern of plots is recognized: A5.1 PLOTS AND QUANTIZED VALIDATION 1. Acceleration Amplitude Frequency Response Rectangular, time Window filter applied 2. Acceleration Amplitude Frequency Response Henning, time Window filter applied 3. Amplitude, time domain and power spectrum, Frequency-Domain of the prediction and measured responses. 4. Signal phase angle for both predicted and measured responses 5. Phasors response both real and imaginary 6. Magnitude Phase and Real-Imaginary combination semi-log Plots 7. Magnitude Phase and Real-Imaginary combination Log-Log Plots. These plots are results of processed measured excitation and measured responses, as well as model calculated response into the frequency domain. Frequency range is filtered into the relevant frequency ranges that affect human responses. In some cases a wider band of frequency spectrum is shown for just future study. A5.2.1 Power Spectrum The distribution of the "power" value of a signal as s function of frequency is named 1

2 Power-Spectrum. Power is measured in a signal as the average of the squared value of a signal. That is equals the squared value of FFT magnitude in the frequency domain in a signal is considered to be the average of the signal Frequencies that contain most of the power of the signal. That can be shown in the distribution of power values as a function of frequency, where in the frequency domain; this is the square of FFT s magnitude The corresponding time domain relevant excitation records are: S1 acc_251 non-filtered S1 acc_251 filtered into a cut-off frequency of 100 Hz S3 acc_25 S3 acc_27 S4 acc_33 S3 acc_305 S4 acc_350 A5.2 MRAP TESTS: July Tests MRAP S1:[acc:251] and S2 [acc:258] S1 - July MRAP [acc_251] Low-Pass-Filtered with a 100 Hz cutoff Figure A5.1 Rectangular-Time-Window Filter Applied on S1 Bladder MRAP Test (excitation acc_251_) Spectrum of Calculated (Top Subplot) Compared to Measured Signal (Bottom Subplot) 2

3 Figure A5.2 Hanning Time-Window Filter Applied on S1 Bladder July-MRAP Test (excitation acc_251_) Spectrum of Calculated (Top Subplot) Compared to Measured Signal (Bottom Subplot) Figure A5.3 Right-Side Subplots: Show State Equation Prediction/Measured Time History Response (Top/Bottom). (Left Subplots): Power Spectrum of both Prediction (Top) and Measured (Bottom) Response. July MRAP-S1_acc_251 Test 3

4 Figure A5.4 Signal Phase Angle as a Function of Frequency: S1 Bladder July-MRAP Test (Excitation Acc_251_) Calculated (Top Subplot), Compared To Measured Signal (Bottom Subplot) Figure A5.5 Signal Phasors Real Value (Left) and Imaginary Value (Right), as a Function of Frequency, S1 Blackhawk Test (Excitation acc_251_) Calculated (Top Subplot) Compared to Measured (Bottom) 4

5 A B Figure A5.6 Both Figures (A) and (B) Shows Signal Magnitude and Phase Angle (Left Top-Bottom), Real and Imaginary (Right-Top- Bottom), for both Measured Response (A) and State Eqns. Prediction (B). All Versus Frequency up to 100Hz. Bladder Tested is S1_Onboard MRAP- July (Excitation _Acc_251). Semi-Log Scale 5

6 A B Figure A5.7 Both Figures (A) and (B) Shows Signal Magnitude and Phase Angle (A): Semi-Log-Scale (Top Eqns, Bottom- Measured), (B): Log-Log Scale (Left-Magnitude, Right, and Phase), Both Measured Response (Bottom) and State Eqns. Prediction (Top). Low-Pass-Frequency cutoff is to 100 Hz. Bladder Tested is S1_Onboard MRAP- July (Excitation _acc_251). 6

7 Table A5.1 Percentage Accuracy Measure For S1_251 All Models Prediction. (Two Iterations Of Sblt Values) Linear Hammerstein Wiener H-W yddt_ St-Eqns. % Accuracy of Model for Bladder S1 Excitation acc_251_ (%) / % Test Duration (sec) Data points Vehicle Speed (mph) Tested Mass (kg) SBlt / July Tests MRAP S1:[acc:251] and S2 [acc:258] S1 - July MRAP [acc_251] Un-Filtered (No low pass filter) Figure A5. 8 Rectangular, time Window filter applied on S1 bladder July-MRAP test (excitation acc_251). Spectrum of Calculated (Top subplot) compared to measured signal (Bottom subplot) 7

8 Figure A5. 9 Hanning time-window filter applied on S1 bladder JULY-MRAP test (excitation acc_251..). Spectrum of Calculated (Top subplot) compared to measured signal (Bottom subplot) Figure A5. 10 Power spectrum (right) and acceleration signal amplitude for S1 bladder July-MRAP test (excitation acc_251). Spectrum of Calculated (Top subplot) compared to measured signal (Bottom subplot) 8

9 Figure A5.11 Phase Angle as a Function of Frequency. S1 Bladder July-MRAP Test (Excitation acc_251_) Calculated (Top Subplot), Compared To Measured Signal (Bottom Subplot) Figure A5.12 Signal Phasors Real Value (Left) and Imaginary Value (Right), as a Function of Frequency, S1 Blackhawk Test (Excitation acc_251_) Calculated (Top Subplot) Compared to Measured (Bottom) 9

10 A B Figure A5.13 Both Figures (A) and (B) Shows Signal Magnitude and Phase angle (Left Top-Bottom ), and Real and Imaginary (Right-Top- Bottom), for Both Measured Response (A) and State Eqns. Prediction (B) all versus Frequency up to 100 Hz. Bladder Tested is S1_Onboard Blackhawk,(Excitation _acc_251). S-log Scale 10

11 A B Figure A5.14 Both Figures (A) and (B) Shows Signal Magnitude and Phase Angle (A): Semi-Log-Scale (Top Eqns, Bottom- Measured), (B): Log-Log Scale (Left-Magnitude, Right, and Phase), Both Measured Response (Bottom) and State Eqns. Prediction (Top). Low-Pass-Frequency cutoff is to 100 Hz. Bladder Tested is S1_Onboard MRAP- July (Excitation _acc_251). 11

12 Figure A5.15 Atypical screen shot, after a Matlab code run. Here is an actual last work-space view of end screen for S4-bladder of November MRAP on excitation (acc_30) SBlt values: Linear Hammerstein Wiener Hammerstein-Wiener Notice the effect of non-filtering and non-optimum SBlt values on accuracy and agreement between the Equation model prediction and measured responses Percentage = Linear yddt SBlt Lowest band is of fs - resampling to Hz for bands up to 4.0 Hz center freq... 12

13 S2 - July MRAP [acc_258] filtered into a 100 Hz cutoff Figure A5.16 Hanning Time-Window Filter Applied on S2 Bladder July-MRAP Test (Excitation acc_258). Spectrum of Calculated (Top Subplot) Compared to Measured Signal (Bottom Subplot) Figure A5.17 Hanning Time-Window Filter Applied on S2 Bladder July-MRAP Test (Excitation acc_258). Spectrum of Calculated (Top Subplot) Compared to Measured Signal (Bottom Subplot) 13

14 Figure A5.18 State Equation Prediction Time History and Measured Response (Left Subplots). Right Side: is the Power Spectrum of both Prediction and Measurement Response. (St. Eqnns: Up, Measured: Down). S2 Bladder July-MRAP Test (Excitation acc_258). Figure A5.19 Phase Angle as a Function of Frequency. S2 Bladder July-MRAP Test (Excitation acc_258_) Calculated (Top Subplot), Compared to Measured Signal (Bottom Subplot) 14

15 Figure A5.20 Signal Phasors Real Value (Left) and Imaginary Value (Right), as a Function of Frequency. S2 Blackhawk Test (Excitation acc_258_) Calculated (Top Subplot) Compared to Measured Signal- (Bottom) A B Figure A5.21 Both Figures (A) and (B) Shows Signal Magnitude and Phase angle (Left Top-Bottom ), and Real and Imaginary (Right-Top- Bottom), for Both Measured Response (A) and State Eqns. Prediction (B) all versus Frequency up to 100 Hz. Bladder Tested is S2_Onboard Blackhawk,(Excitation _acc_258). S.log Scale 15

16 A B Figure A5.22 Both Figures (A) and (B) Shows Signal Magnitude and Phase Angle (A): Semi-Log-Scale (Top Eqns, Bottom- Measured), (B): Log-Log Scale (Left-Magnitude, Right, and Phase), Both Measured Response (Bottom) and State Eqns. Prediction (Top). Low-Pass-Frequency cutoff is to 100 Hz. Bladder Tested is S2_Onboard MRAP- July (Excitation _acc_258). 16

17 S2 AAA Distinct_Plots_Sound_Match_S2_258 S2 S2_258 Model : [test Foam D M SBlt ] = [ ] test = test; Foam = 2.0; D = 3/8; M = M; SBlt = SBlt; Model = [test Foam D M SBlt ] Linear-S2-258 Hammerstein Wiener Hammerstein-Wiener Linear Hammerstein Wiener Hammerstein-Wiener A t t e n c i o n " ATTENTION For SOUND-PLEASE Linear State_Eqn_yddt Linear-S2-258 State_Eqn_yddt Lowest band is of fs - resampling to Hz for bands up to 4.0 Hz center freq... 17

18 Nov. Tests MRAP S3:[acc:25] and S4 [acc:33] S3 - November MRAP [acc_25] filtered into a 100 Hz cutoff Figure A5.23 Hanning Time-Window Filter Applied On S3 Bladder Nov-MRAP Test (Excitation acc_25). Spectrum of Calculated (Top Subplot) Compared to Measured Signal (Bottom Subplot) Figure A5.24 Hanning Time-Window Filter Applied on S3 Bladder Nov-MRAP Test (Excitation Acc_25_). Spectrum of Calculated (Top Subplot) Compared To Measured Signal (Bottom Subplot) 18

19 Figure A5.25 State Equation prediction time history and measured response (left subplots). Right side: power spectrum of both prediction and measurement response. Plots show large disparities in both cases. But not at the frequency location of the peaks Figure A5.26 Shows Signal Phase Angle vs. Frequency. S3 Bladder Nov-MRAP Test (Excitation acc_25_) Calculated (Top Subplot), Compared to Measured Signal (Bottom Subplot) 19

20 Figure A5.27 Signal Phasors Real Value (Left) and Imaginary Value (Right), vs Frequency. S3 Blackhawk Test (Excitation Acc_25) Calculated (Top Subplot) Compared to Measured Signal-(Bottom) 20

21 A B Figure A5.28 Both Figures (A) and (B) Shows Signal Magnitude and Phase angle (Left Top-Bottom ), and Real and Imaginary (Right-Top- Bottom), for Both Measured Response (A) and State Eqns. Prediction (B) all versus Frequency up to 100 Hz. Bladder Tested is S3_Onboard Blackhawk,(Excitation _acc_25). S.log Scale 21

22 A B Figure A5.29 Both Figures (A) and (B) Shows Signal Magnitude and Phase Angle (A): Semi-Log-Scale (Top Eqns, Bottom- Measured), (B): Log-Log Scale (Left-Magnitude, Right, and Phase), Both Measured Response (Bottom) and State Eqns. Prediction (Top). Low-Pass-Frequency cutoff is to 100 Hz. Bladder Tested is S3_Onboard MRAP- July (Excitation _acc_25). 22

23 S3 - November MRAP [acc_27] filtered into a 100 Hz cutoff Figure A5.30 Hanning Time-Window Filter Applied on S3 Bladder Nov-MRAP Test (Excitation acc_27_). Spectrum of Calculated (Top Subplot) Compared to Measured Signal (Bottom Subplot) Figure A5.31 Hanning Time-Window Filter Applied on S3 Bladder Nov-MRAP Test (Excitation Acc_27_). Spectrum of Calculated (Top Subplot) Compared to Measured Signal (Bottom Subplot) 23

24 Figure A5.32 State Equation Prediction Time History And Measured Response (Left Subplots). Right Side: Power Spectrum of both Prediction and Measurement Response. S3_ Acc_27 S3_27 Model : S3 S3_27 Model = [test Foam D M SBlt ] = [ ] Linear Hammerstein Wiener Hammerstein-Wiener Linear Hammerstein Wiener Hammerstein-Wiener A t t e n c i o n " ATTENTION For SOUND-PLEASE Linear State_Eqn_yddt Linear State_Eqn_yddt

25 November Tests MRAP S3:[acc:27] and S4 [acc:33] S4 - November MRAP [acc_33] filtered into a 100 Hz cutoff Figure A5.33: Signal Phase Angle as a Function of Frequency. S3 Bladder Nov-MRAP Test (Excitation acc_27_) Calculated (Top Subplot), Compared to Measured Signal (Bottom Subplot) Figure A5.34 Signal Phasors Real Value (Left) and Imaginary Value (Right), vs. Frequency. S3 Nov. MRAP Test (Excitation acc_27_) Calculated (Top Subplot) Compared to Measured Signal-(Bottom) 25

26 A B Figure A5.35 Both Figures (A) and (B) Shows Signal Magnitude and Phase Angle (Left Top-Bottom ), Real And Imaginary (Right-Top- Bottom), for Both Measured Response (A) and State Eqns. Prediction (B) vs. Frequency up to 100 Hz. Bladder Tested Is S3_Onboard Blackhawk,(Excitation _acc_27). S-Log Scale 26

27 A B Figure A5.36 Both Figures (A) and (B) Shows Signal Magnitude and Phase Angle (A): Semi-Log-Scale (Top Eqns, Bottom- Measured), (B): Log-Log Scale (Left-Magnitude, Right, and Phase), Both Measured Response (Bottom) and State Eqns. Prediction (Top). Low-Pass-Frequency cutoff is to 100 Hz. Bladder Tested is S3_Onboard MRAP-July (Excitation _acc_27). 27

28 Figure A5.37 Hanning Time-Window Filter Applied on S4 Bladder Nov-MRAP Test (Excitation acc_33_). Spectrum of Calculated (Top Subplot) Compared to Measured Signal (Bottom Subplot) Figure A5.38 Hanning Time-Window Filter Applied on S4 Bladder Nov-MRAP Test (Excitation acc_33_). Spectrum of Calculated (Top Subplot) Compared to Measured Signal (Bottom Subplot) 28

29 Figure A5.39 State Equation Prediction Time History and Measured Response (Left Subplots). Right Side: Power Spectrum of both Prediction and Measurement Response. S4_acc_33 Nov. MRAP Figure A5.40: Signal Phase Angle vs Frequency. S4 Bladder Nov-MRAP Test (Excitation acc_33_) Calculated (Top Subplot), Compared to Measured Signal (Bottom Subplot) 29

30 Figure A5.41 Signal Phasors Real Value (Left) and Imaginary Value (Right), vs. Frequency. S4 Blackhawk Test (Excitation Acc_33_) Calculated (Top Subplot) Compared to Measured Signal-(Bottom) 30

31 A B Figure A5.42 Both Figures (A) and (B) Shows Signal Magnitude and Phase Angle (Left Top-Bottom ), and Real and Imaginary (Right-Top- Bottom), for Both Measured Response (A) and State Eqns. Prediction (B) all versus Frequency up to 100 Hz. Bladder Tested is S4_Onboard Blackhawk,(Excitation _acc_33). S.log Scale 31

32 A B Figure A5.43 Both Figures (A) and (B) Shows Signal Magnitude and Phase Angle (A): Semi-Log-Scale (Top Eqns, Bottom- Measured), (B): Log-Log Scale (Left-Magnitude, Right, and Phase), Both Measured Response (Bottom) and State Eqns. Prediction (Top). Low-Pass-Frequency cutoff Hz. Bladder Tested is S4_Onboard Nov-MRAP (Excitation _acc_33). 32

33 S4 S4_33 Model = [test Foam D M SBlt ] AAA_l_accel100_Distinct_Plots_Sound_Match_S4_33_ sym S4 test = test; Foam = 2.0; D = 3/8; M = M; SBlt; Model = [test Foam D M SBlt ] S4 S4_33 Model: [test Foam D M SBlt ] = [ ] Linear Hammerstein Wiener Hammerstein-Wiener Linear Hammerstein Wiener Hammerstein-Wiener Linear State_Eqn_yddt Linear State_Eqn_yddt Lowest band is of fs - resampling to Hz for bands up to 4.0 Hz center freq... 33

34 A5.2.2 BLACKHAWK HELICOPTER TESTS Blackhawk S3:[acc:305] and S4 [acc:330] S3 - Blackhawk [acc_305] filtered into a 100 Hz cutoff Figure A5.44 Rectangular Time-Window Filter Applied on S3 Bladder Blackhawk Test (Excitation acc_305). Spectrum of Calculated (Top Subplot) Compared to Measured Signal (Bottom) Figure A5.45 Hanning Time-Window Filter Applied on S3 Bladder Blackhawk Test (Excitation acc_305). Spectrum of Calculated (Top Subplot) Compared to Measured Signal (Bottom Subplot) 34

35 Figure A5.46 State Equation Prediction Time History and Measured Response (Left Subplots). Right Side: Power Spectrum of Both Prediction and Measurement Response. (Blackhawk-S3_acc_305) Figure A5.47 Signal Phase Angle vs. Frequency. S3 Bladder Blackhawk Test (Excitation Acc_305_) Calculated (Top Subplot), Compared to Measured Signal (Bottom Subplot) 35

36 Figure A5.48 Signal Phasors Real Value (Left) and Imaginary Value (Right), vs Of Frequency. S3 Blackhawk Test (Excitation acc_305_) Calculated (Top Subplot) Compared To Measured Signal-(Bottom) 36

37 A B Figure A5.49 Both Figures (A) and (B) Shows Signal Magnitude And Phase Angle (Left Top-), And Real and Imaginary (Right-Top, for Both Measured Response (A) and State Eqns. Prediction (B) all vs Frequency up to 100Hz. Bladder Tested Is S3_Onboard Blackhawk,(Excitn.. _Acc_305). S-Log Scale 37

38 A B Figure A5.50 Both Figures (A) and (B) Shows Signal Magnitude and Phase Angle (A): Semi-Log-Scale (Top Eqns, Bottom- Measured), (B): Log-Log Scale (Left-Magnitude, Right, and Phase), Both Measured Response (Bottom) and State Eqns. Prediction (Top). Low-Pass-Frequency cutoff is to 100 Hz. Bladder Tested is S3_Blackhawk (Excitation _acc_305). 38

39 S3 S3_305 Model: [test Foam D M SBlt ] = [ ] Linear Hammerstein Wiener Hammerstein-Wiener A t t e n c i o n " ATTENTION For SOUND-PLEASE Linear State_Eqn_yddt Linear State_Eqn_yddt Lowest band is of fs - resampling to Hz for bands up to 4.0 Hz center freq... S4 BLACKHAWK [acc_350] filtered into a 100 Hz cutoff 39

40 Figure A5.51 Rectangular-Time-Window Filter Applied on S4 Bladder Blackhawk Test (Excitation acc_350) of Calculated (Top Subplot) Compared to Measured Response (Bottom Subplot) Figure A5.52 Hanning Time-Window Filter Applied on S4 Bladder Blackhawk Test (Excitation Acc_350_). Spectrum of Calculated (Top Subplot) Compared to Measured Signal (Bottom Subplot) 40

41 Figure A5.53 State Equation Prediction Time History and Measured Response (Left Subplots). Right Side: Power Spectrum of Both Prediction and Measurement Response. (Blackhawk-S4_acc_350) Figure A5.54: Signal Phase Angle vs Frequency. S4 Bladder Blackhawk Test (Excitation acc_350_) Calculated (Top Subplot), Compared to Measured Signal (Bottom Subplot) 41

42 Figure A5.55: Signal Phasors Real value (left) and Imaginary value (right), vs. S4 Blackhawk Test (excitation acc_330_) Calculated (Top subplot) Compared to Measured Signal-(Bottom) 42

43 A B Figure A5.56 Both Figures (A) and (B) Shows Signal Magnitude and Phase angle (Left Top-Bottom ), and Real and Imaginary (Right-Top- Bottom), for Both Measured Response (A) and State Eqns. Prediction (B) versus Frequency up to 100 Hz. Bladder Tested is S4_Onboard Blackhawk,(Excitation _acc_350). S-log Scale 43

44 Figure A5.57 Shows Signal Magnitude and Phase Angle (Top Eqns, Bottom- Measured), (Left-Magnitude, Right, Phase), Both Measured Response (Bottom) and State Eqns. Prediction (Top). Low-Pass-Frequency cutoff is to 100 Hz. Bladder Tested is S4_Onboard MRAP-July (Excitation _acc_350). Semi-Log-Scale A5. 3 DISCUSSION Validation for viability of our Model prediction requires comparing measured actual and calculated results. We will show in this chapter both acquired measured acceleration and model calculated acceleration results both for the same input acceleration values acquired directly from input accelerometers. Results will be analyzed in next chapters. Frequency and time domain responses will be listed here than later discussed. Both System Identification and Model calculated through the system of developed equations are compared to the respective measured values in terms of acceleration responses and response criteria. Model calculated results used for comparisons and measured values averages are obtained in the same manner, as both tabulated and the operated on to obtain, the required response criteria such as, transmissibility or RMS, VDV, and even test averages, are all made in the same way and on both sets tabulated together in the same matrix. Results presented in this chapter will be discussed in the following 44

45 chapters along with and co moments and conclusion. Test environment and tested items will be identified, followed by results of each test. There are four bladders. Input accelerometer is placed under the bladder, in each test and output or measured response accelerometer is placed above the bladder, and underneath the seat occupant. No accelerometer is placed on the seat back portion.... " T h e I m p o r t a n t T h i n g i s N o t t o S t o p Q u e s t i o n i n g. C u r i o s i t y h a s i t s O w n R e a s o n f o r E x i s t i n g ; Albert Einstein. 45

Discrete Fourier Transform (DFT)

Discrete Fourier Transform (DFT) Amplitude Amplitude Discrete Fourier Transform (DFT) DFT transforms the time domain signal samples to the frequency domain components. DFT Signal Spectrum Time Frequency DFT is often used to do frequency

More information

Reference Sources. Prelab. Proakis chapter 7.4.1, equations to as attached

Reference Sources. Prelab. Proakis chapter 7.4.1, equations to as attached Purpose The purpose of the lab is to demonstrate the signal analysis capabilities of Matlab. The oscilloscope will be used as an A/D converter to capture several signals we have examined in previous labs.

More information

Response spectrum Time history Power Spectral Density, PSD

Response spectrum Time history Power Spectral Density, PSD A description is given of one way to implement an earthquake test where the test severities are specified by time histories. The test is done by using a biaxial computer aided servohydraulic test rig.

More information

Experimental investigation of crack in aluminum cantilever beam using vibration monitoring technique

Experimental investigation of crack in aluminum cantilever beam using vibration monitoring technique International Journal of Computational Engineering Research Vol, 04 Issue, 4 Experimental investigation of crack in aluminum cantilever beam using vibration monitoring technique 1, Akhilesh Kumar, & 2,

More information

TBM - Tone Burst Measurement (CEA 2010)

TBM - Tone Burst Measurement (CEA 2010) TBM - Tone Burst Measurement (CEA 21) Software of the R&D and QC SYSTEM ( Document Revision 1.7) FEATURES CEA21 compliant measurement Variable burst cycles Flexible filtering for peak measurement Monitor

More information

EE233 Autumn 2016 Electrical Engineering University of Washington. EE233 HW7 Solution. Nov. 16 th. Due Date: Nov. 23 rd

EE233 Autumn 2016 Electrical Engineering University of Washington. EE233 HW7 Solution. Nov. 16 th. Due Date: Nov. 23 rd EE233 HW7 Solution Nov. 16 th Due Date: Nov. 23 rd 1. Use a 500nF capacitor to design a low pass passive filter with a cutoff frequency of 50 krad/s. (a) Specify the cutoff frequency in hertz. fc c 50000

More information

EXPERIMENT 4 INTRODUCTION TO AMPLITUDE MODULATION SUBMITTED BY

EXPERIMENT 4 INTRODUCTION TO AMPLITUDE MODULATION SUBMITTED BY EXPERIMENT 4 INTRODUCTION TO AMPLITUDE MODULATION SUBMITTED BY NAME:. STUDENT ID:.. ROOM: INTRODUCTION TO AMPLITUDE MODULATION Purpose: The objectives of this laboratory are:. To introduce the spectrum

More information

Lecture 3 Complex Exponential Signals

Lecture 3 Complex Exponential Signals Lecture 3 Complex Exponential Signals Fundamentals of Digital Signal Processing Spring, 2012 Wei-Ta Chu 2012/3/1 1 Review of Complex Numbers Using Euler s famous formula for the complex exponential The

More information

PART I: The questions in Part I refer to the aliasing portion of the procedure as outlined in the lab manual.

PART I: The questions in Part I refer to the aliasing portion of the procedure as outlined in the lab manual. Lab. #1 Signal Processing & Spectral Analysis Name: Date: Section / Group: NOTE: To help you correctly answer many of the following questions, it may be useful to actually run the cases outlined in the

More information

Vibration Analysis on Rotating Shaft using MATLAB

Vibration Analysis on Rotating Shaft using MATLAB IJSTE - International Journal of Science Technology & Engineering Volume 3 Issue 06 December 2016 ISSN (online): 2349-784X Vibration Analysis on Rotating Shaft using MATLAB K. Gopinath S. Periyasamy PG

More information

MATLAB Assignment. The Fourier Series

MATLAB Assignment. The Fourier Series MATLAB Assignment The Fourier Series Read this carefully! Submit paper copy only. This project could be long if you are not very familiar with Matlab! Start as early as possible. This is an individual

More information

Laboratory Experiment #2 Frequency Response Measurements

Laboratory Experiment #2 Frequency Response Measurements J.B.Francis College of Engineering Mechanical Engineering Department 22-403 Laboratory Experiment #2 Frequency Response Measurements Introduction It is known from dynamic systems that a structure temporarily

More information

Figure 1: Block diagram of Digital signal processing

Figure 1: Block diagram of Digital signal processing Experiment 3. Digital Process of Continuous Time Signal. Introduction Discrete time signal processing algorithms are being used to process naturally occurring analog signals (like speech, music and images).

More information

EE 560 Electric Machines and Drives. Autumn 2014 Final Project. Contents

EE 560 Electric Machines and Drives. Autumn 2014 Final Project. Contents EE 560 Electric Machines and Drives. Autumn 2014 Final Project Page 1 of 53 Prof. N. Nagel December 8, 2014 Brian Howard Contents Introduction 2 Induction Motor Simulation 3 Current Regulated Induction

More information

ADC Clock Jitter Model, Part 1 Deterministic Jitter

ADC Clock Jitter Model, Part 1 Deterministic Jitter ADC Clock Jitter Model, Part 1 Deterministic Jitter Analog to digital converters (ADC s) have several imperfections that effect communications signals, including thermal noise, differential nonlinearity,

More information

A METHOD FOR OPTIMAL RECONSTRUCTION OF VELOCITY RESPONSE USING EXPERIMENTAL DISPLACEMENT AND ACCELERATION SIGNALS

A METHOD FOR OPTIMAL RECONSTRUCTION OF VELOCITY RESPONSE USING EXPERIMENTAL DISPLACEMENT AND ACCELERATION SIGNALS ICSV14 Cairns Australia 9-12 July, 27 A METHOD FOR OPTIMAL RECONSTRUCTION OF VELOCITY RESPONSE USING EXPERIMENTAL DISPLACEMENT AND ACCELERATION SIGNALS Gareth J. Bennett 1 *, José Antunes 2, John A. Fitzpatrick

More information

FFT Analyzer. Gianfranco Miele, Ph.D

FFT Analyzer. Gianfranco Miele, Ph.D FFT Analyzer Gianfranco Miele, Ph.D www.eng.docente.unicas.it/gianfranco_miele g.miele@unicas.it Introduction It is a measurement instrument that evaluates the spectrum of a time domain signal applying

More information

MODEL MODIFICATION OF WIRA CENTER MEMBER BAR

MODEL MODIFICATION OF WIRA CENTER MEMBER BAR MODEL MODIFICATION OF WIRA CENTER MEMBER BAR F.R.M. Romlay & M.S.M. Sani Faculty of Mechanical Engineering Kolej Universiti Kejuruteraan & Teknologi Malaysia (KUKTEM), Karung Berkunci 12 25000 Kuantan

More information

SHAKER TABLE SEISMIC TESTING OF EQUIPMENT USING HISTORICAL STRONG MOTION DATA SCALED TO SATISFY A SHOCK RESPONSE SPECTRUM

SHAKER TABLE SEISMIC TESTING OF EQUIPMENT USING HISTORICAL STRONG MOTION DATA SCALED TO SATISFY A SHOCK RESPONSE SPECTRUM SHAKER TABLE SEISMIC TESTING OF EQUIPMENT USING HISTORICAL STRONG MOTION DATA SCALED TO SATISFY A SHOCK RESPONSE SPECTRUM By Tom Irvine Email: tomirvine@aol.com May 6, 29. The purpose of this paper is

More information

2015 HBM ncode Products User Group Meeting

2015 HBM ncode Products User Group Meeting Looking at Measured Data in the Frequency Domain Kurt Munson HBM-nCode Do Engineers Need Tools? 3 What is Vibration? http://dictionary.reference.com/browse/vibration 4 Some Statistics Amplitude PDF y Measure

More information

User-friendly Matlab tool for easy ADC testing

User-friendly Matlab tool for easy ADC testing User-friendly Matlab tool for easy ADC testing Tamás Virosztek, István Kollár Budapest University of Technology and Economics, Department of Measurement and Information Systems Budapest, Hungary, H-1521,

More information

SHOCK RESPONSE SPECTRUM SYNTHESIS VIA DAMPED SINUSOIDS Revision B

SHOCK RESPONSE SPECTRUM SYNTHESIS VIA DAMPED SINUSOIDS Revision B SHOCK RESPONSE SPECTRUM SYNTHESIS VIA DAMPED SINUSOIDS Revision B By Tom Irvine Email: tomirvine@aol.com April 5, 2012 Introduction Mechanical shock can cause electronic components to fail. Crystal oscillators

More information

Experimental Investigation of Crack Detection in Cantilever Beam Using Natural Frequency as Basic Criterion

Experimental Investigation of Crack Detection in Cantilever Beam Using Natural Frequency as Basic Criterion INSTITUTE OF TECHNOLOGY, NIRMA UNIVERSITY, AHMEDABAD 382 481, 08-10 DECEMBER, 2011 1 Experimental Investigation of Crack Detection in Cantilever Beam Using Natural Frequency as Basic Criterion A. A.V.Deokar,

More information

Laboratory Experiment #1 Introduction to Spectral Analysis

Laboratory Experiment #1 Introduction to Spectral Analysis J.B.Francis College of Engineering Mechanical Engineering Department 22-403 Laboratory Experiment #1 Introduction to Spectral Analysis Introduction The quantification of electrical energy can be accomplished

More information

Advanced Lab LAB 6: Signal Acquisition & Spectrum Analysis Using VirtualBench DSA Equipment: Objectives:

Advanced Lab LAB 6: Signal Acquisition & Spectrum Analysis Using VirtualBench DSA Equipment: Objectives: Advanced Lab LAB 6: Signal Acquisition & Spectrum Analysis Using VirtualBench DSA Equipment: Pentium PC with National Instruments PCI-MIO-16E-4 data-acquisition board (12-bit resolution; software-controlled

More information

Window Method. designates the window function. Commonly used window functions in FIR filters. are: 1. Rectangular Window:

Window Method. designates the window function. Commonly used window functions in FIR filters. are: 1. Rectangular Window: Window Method We have seen that in the design of FIR filters, Gibbs oscillations are produced in the passband and stopband, which are not desirable features of the FIR filter. To solve this problem, window

More information

SHAKER TABLE SEISMIC TESTING OF EQUIPMENT USING HISTORICAL STRONG MOTION DATA SCALED TO SATISFY A SHOCK RESPONSE SPECTRUM Revision C

SHAKER TABLE SEISMIC TESTING OF EQUIPMENT USING HISTORICAL STRONG MOTION DATA SCALED TO SATISFY A SHOCK RESPONSE SPECTRUM Revision C SHAKER TABLE SEISMIC TESTING OF EQUIPMENT USING HISTORICAL STRONG MOTION DATA SCALED TO SATISFY A SHOCK RESPONSE SPECTRUM Revision C By Tom Irvine Email: tom@vibrationdata.com March 12, 2015 The purpose

More information

Understanding Probability of Intercept for Intermittent Signals

Understanding Probability of Intercept for Intermittent Signals 2013 Understanding Probability of Intercept for Intermittent Signals Richard Overdorf & Rob Bordow Agilent Technologies Agenda Use Cases and Signals Time domain vs. Frequency Domain Probability of Intercept

More information

Digital Signal Processing

Digital Signal Processing Digital Signal Processing Lab 1: FFT, Spectral Leakage, Zero Padding Moslem Amiri, Václav Přenosil Embedded Systems Laboratory Faculty of Informatics, Masaryk University Brno, Czech Republic amiri@mail.muni.cz

More information

Chapter 5 Window Functions. periodic with a period of N (number of samples). This is observed in table (3.1).

Chapter 5 Window Functions. periodic with a period of N (number of samples). This is observed in table (3.1). Chapter 5 Window Functions 5.1 Introduction As discussed in section (3.7.5), the DTFS assumes that the input waveform is periodic with a period of N (number of samples). This is observed in table (3.1).

More information

Electrical & Computer Engineering Technology

Electrical & Computer Engineering Technology Electrical & Computer Engineering Technology EET 419C Digital Signal Processing Laboratory Experiments by Masood Ejaz Experiment # 1 Quantization of Analog Signals and Calculation of Quantized noise Objective:

More information

Basic Signals and Systems

Basic Signals and Systems Chapter 2 Basic Signals and Systems A large part of this chapter is taken from: C.S. Burrus, J.H. McClellan, A.V. Oppenheim, T.W. Parks, R.W. Schafer, and H. W. Schüssler: Computer-based exercises for

More information

Experiment 2 Effects of Filtering

Experiment 2 Effects of Filtering Experiment 2 Effects of Filtering INTRODUCTION This experiment demonstrates the relationship between the time and frequency domains. A basic rule of thumb is that the wider the bandwidth allowed for the

More information

Introduction. A Simple Example. 3. fo = 4; %frequency of the sine wave. 4. Fs = 100; %sampling rate. 5. Ts = 1/Fs; %sampling time interval

Introduction. A Simple Example. 3. fo = 4; %frequency of the sine wave. 4. Fs = 100; %sampling rate. 5. Ts = 1/Fs; %sampling time interval Introduction In this tutorial, we will discuss how to use the fft (Fast Fourier Transform) command within MATLAB. The fft command is in itself pretty simple, but takes a little bit of getting used to in

More information

Proportional-Integral Controller Performance

Proportional-Integral Controller Performance Proportional-Integral Controller Performance Silver Team Jonathan Briere ENGR 329 Dr. Henry 4/1/21 Silver Team Members: Jordan Buecker Jonathan Briere John Colvin 1. Introduction Modeling for the response

More information

Time and Frequency Domain Windowing of LFM Pulses Mark A. Richards

Time and Frequency Domain Windowing of LFM Pulses Mark A. Richards Time and Frequency Domain Mark A. Richards September 29, 26 1 Frequency Domain Windowing of LFM Waveforms in Fundamentals of Radar Signal Processing Section 4.7.1 of [1] discusses the reduction of time

More information

Wireless Communication Systems Laboratory Lab#1: An introduction to basic digital baseband communication through MATLAB simulation Objective

Wireless Communication Systems Laboratory Lab#1: An introduction to basic digital baseband communication through MATLAB simulation Objective Wireless Communication Systems Laboratory Lab#1: An introduction to basic digital baseband communication through MATLAB simulation Objective The objective is to teach students a basic digital communication

More information

Portable FFT Analyzer CF-9200/9400

Portable FFT Analyzer CF-9200/9400 Portable FFT Analyzer CF-9200/9400 Frequency response measurement by impact excitation by using Impulse hammer November2015 Contents 1 Introduction 2 Preparing equipment 3 Before measurement 3-1. Connection

More information

Digital Video and Audio Processing. Winter term 2002/ 2003 Computer-based exercises

Digital Video and Audio Processing. Winter term 2002/ 2003 Computer-based exercises Digital Video and Audio Processing Winter term 2002/ 2003 Computer-based exercises Rudolf Mester Institut für Angewandte Physik Johann Wolfgang Goethe-Universität Frankfurt am Main 6th November 2002 Chapter

More information

LABORATORY - FREQUENCY ANALYSIS OF DISCRETE-TIME SIGNALS

LABORATORY - FREQUENCY ANALYSIS OF DISCRETE-TIME SIGNALS LABORATORY - FREQUENCY ANALYSIS OF DISCRETE-TIME SIGNALS INTRODUCTION The objective of this lab is to explore many issues involved in sampling and reconstructing signals, including analysis of the frequency

More information

Digital Filters IIR (& Their Corresponding Analog Filters) Week Date Lecture Title

Digital Filters IIR (& Their Corresponding Analog Filters) Week Date Lecture Title http://elec3004.com Digital Filters IIR (& Their Corresponding Analog Filters) 2017 School of Information Technology and Electrical Engineering at The University of Queensland Lecture Schedule: Week Date

More information

Experimental Modal Analysis of an Automobile Tire

Experimental Modal Analysis of an Automobile Tire Experimental Modal Analysis of an Automobile Tire J.H.A.M. Vervoort Report No. DCT 2007.084 Bachelor final project Coach: Dr. Ir. I. Lopez Arteaga Supervisor: Prof. Dr. Ir. H. Nijmeijer Eindhoven University

More information

Developer Techniques Sessions

Developer Techniques Sessions 1 Developer Techniques Sessions Physical Measurements and Signal Processing Control Systems Logging and Networking 2 Abstract This session covers the technologies and configuration of a physical measurement

More information

1.5 The voltage V is given as V=RI, where R and I are resistance matrix and I current vector. Evaluate V given that

1.5 The voltage V is given as V=RI, where R and I are resistance matrix and I current vector. Evaluate V given that Sheet (1) 1.1 The voltage across a discharging capacitor is v(t)=10(1 e 0.2t ) Generate a table of voltage, v(t), versus time, t, for t = 0 to 50 seconds with increment of 5 s. 1.2 Use MATLAB to evaluate

More information

ENG 100 Lab #2 Passive First-Order Filter Circuits

ENG 100 Lab #2 Passive First-Order Filter Circuits ENG 100 Lab #2 Passive First-Order Filter Circuits In Lab #2, you will construct simple 1 st -order RL and RC filter circuits and investigate their frequency responses (amplitude and phase responses).

More information

Real-Time FFT Analyser - Functional Specification

Real-Time FFT Analyser - Functional Specification Real-Time FFT Analyser - Functional Specification Input: Number of input channels 2 Input voltage ranges ±10 mv to ±10 V in a 1-2 - 5 sequence Autorange Pre-acquisition automatic selection of full-scale

More information

Adaptive Filters Application of Linear Prediction

Adaptive Filters Application of Linear Prediction Adaptive Filters Application of Linear Prediction Gerhard Schmidt Christian-Albrechts-Universität zu Kiel Faculty of Engineering Electrical Engineering and Information Technology Digital Signal Processing

More information

BIOE 198MI Biomedical Data Analysis. Spring Semester Lab6: Signal processing and filter design

BIOE 198MI Biomedical Data Analysis. Spring Semester Lab6: Signal processing and filter design BIOE 198MI Biomedical Data Analysis. Spring Semester 2018. Lab6: Signal processing and filter design Problem Statement: In this lab, we are considering the problem of designing a window-based digital filter

More information

Frequency Response Function Measurements of Disc and Drum Brake With its Verification by CAE

Frequency Response Function Measurements of Disc and Drum Brake With its Verification by CAE Frequency Response Function Measurements of Disc and Drum Brake With its Verification by CAE Aniket B. Ghatwai 1, Prof. S.V. Chaitanya 2, Sandip B. Phadke 3 1 Student at AISSMS COE,PUNE,Maharashtra 2Prof.

More information

Sampling and Reconstruction

Sampling and Reconstruction Experiment 10 Sampling and Reconstruction In this experiment we shall learn how an analog signal can be sampled in the time domain and then how the same samples can be used to reconstruct the original

More information

SignalCalc Drop Test Demo Guide

SignalCalc Drop Test Demo Guide SignalCalc Drop Test Demo Guide Introduction Most protective packaging for electronic and other fragile products use cushion materials in the packaging that are designed to deform in response to forces

More information

Beam Dynamics + Laser Micro Vibrometry 1

Beam Dynamics + Laser Micro Vibrometry 1 ENMF 529 INTRODUCTION TO MICROELECTROMECHANICAL SYSTEMS p. 1 DATE:... Note: Print this document at Scale (Page Setup) = 75% LAB #4 ( VIL #7 ) Beam Dynamics + Laser Micro Vibrometry 1 SAFETY and instrument

More information

DSP First. Laboratory Exercise #2. Introduction to Complex Exponentials

DSP First. Laboratory Exercise #2. Introduction to Complex Exponentials DSP First Laboratory Exercise #2 Introduction to Complex Exponentials The goal of this laboratory is gain familiarity with complex numbers and their use in representing sinusoidal signals as complex exponentials.

More information

Waveforms and Spectra in NBFM Receiver

Waveforms and Spectra in NBFM Receiver Waveforms and Spectra in NBFM Receiver GNU radio was used to create the following NBFM receiver. The USRP with the RFX400 daughterboard was used to capture the signal. 64Ms/s 256Ks/s 32Ks/s 32Ks/s FPGA

More information

Microcomputer Systems 1. Introduction to DSP S

Microcomputer Systems 1. Introduction to DSP S Microcomputer Systems 1 Introduction to DSP S Introduction to DSP s Definition: DSP Digital Signal Processing/Processor It refers to: Theoretical signal processing by digital means (subject of ECE3222,

More information

Lab #2 First Order RC Circuits Week of 27 January 2015

Lab #2 First Order RC Circuits Week of 27 January 2015 ECE214: Electrical Circuits Laboratory Lab #2 First Order RC Circuits Week of 27 January 2015 1 Introduction In this lab you will investigate the magnitude and phase shift that occurs in an RC circuit

More information

RLC Frequency Response

RLC Frequency Response 1. Introduction RLC Frequency Response The student will analyze the frequency response of an RLC circuit excited by a sinusoid. Amplitude and phase shift of circuit components will be analyzed at different

More information

MTE 360 Automatic Control Systems University of Waterloo, Department of Mechanical & Mechatronics Engineering

MTE 360 Automatic Control Systems University of Waterloo, Department of Mechanical & Mechatronics Engineering MTE 36 Automatic Control Systems University of Waterloo, Department of Mechanical & Mechatronics Engineering Laboratory #1: Introduction to Control Engineering In this laboratory, you will become familiar

More information

IADS Frequency Analysis FAQ ( Updated: March 2009 )

IADS Frequency Analysis FAQ ( Updated: March 2009 ) IADS Frequency Analysis FAQ ( Updated: March 2009 ) * Note - This Document references two data set archives that have been uploaded to the IADS Google group available in the Files area called; IADS Frequency

More information

Appendix III Graphs in the Introductory Physics Laboratory

Appendix III Graphs in the Introductory Physics Laboratory Appendix III Graphs in the Introductory Physics Laboratory 1. Introduction One of the purposes of the introductory physics laboratory is to train the student in the presentation and analysis of experimental

More information

6.555 Lab1: The Electrocardiogram

6.555 Lab1: The Electrocardiogram 6.555 Lab1: The Electrocardiogram Tony Hyun Kim Spring 11 1 Data acquisition Question 1: Draw a block diagram to illustrate how the data was acquired. The EKG signal discussed in this report was recorded

More information

THE SINUSOIDAL WAVEFORM

THE SINUSOIDAL WAVEFORM Chapter 11 THE SINUSOIDAL WAVEFORM The sinusoidal waveform or sine wave is the fundamental type of alternating current (ac) and alternating voltage. It is also referred to as a sinusoidal wave or, simply,

More information

(i) Sine sweep (ii) Sine beat (iii) Time history (iv) Continuous sine

(i) Sine sweep (ii) Sine beat (iii) Time history (iv) Continuous sine A description is given of one way to implement an earthquake test where the test severities are specified by the sine-beat method. The test is done by using a biaxial computer aided servohydraulic test

More information

Capacitive MEMS accelerometer for condition monitoring

Capacitive MEMS accelerometer for condition monitoring Capacitive MEMS accelerometer for condition monitoring Alessandra Di Pietro, Giuseppe Rotondo, Alessandro Faulisi. STMicroelectronics 1. Introduction Predictive maintenance (PdM) is a key component of

More information

Impact sound insulation: Transient power input from the rubber ball on locally reacting mass-spring systems

Impact sound insulation: Transient power input from the rubber ball on locally reacting mass-spring systems Impact sound insulation: Transient power input from the rubber ball on locally reacting mass-spring systems Susumu HIRAKAWA 1 ; Carl HOPKINS 2 ; Pyoung Jik LEE 3 Acoustics Research Unit, School of Architecture,

More information

ijdsp Workshop: Exercise 2012 DSP Exercise Objectives

ijdsp Workshop: Exercise 2012 DSP Exercise Objectives Objectives DSP Exercise The objective of this exercise is to provide hands-on experiences on ijdsp. It consists of three parts covering frequency response of LTI systems, pole/zero locations with the frequency

More information

MATHEMATICAL MODEL VALIDATION

MATHEMATICAL MODEL VALIDATION CHAPTER 5: VALIDATION OF MATHEMATICAL MODEL 5-1 MATHEMATICAL MODEL VALIDATION 5.1 Preamble 5-2 5.2 Basic strut model validation 5-2 5.2.1 Passive characteristics 5-3 5.2.2 Workspace tests 5-3 5.3 SDOF

More information

STUDY OF FIXED WING AIRCRAFT DYNAMICS USING SYSTEM IDENTIFICATION APPROACH

STUDY OF FIXED WING AIRCRAFT DYNAMICS USING SYSTEM IDENTIFICATION APPROACH STUDY OF FIXED WING AIRCRAFT DYNAMICS USING SYSTEM IDENTIFICATION APPROACH A.Kaviyarasu 1, Dr.A.Saravan Kumar 2 1,2 Department of Aerospace Engineering, Madras Institute of Technology, Anna University,

More information

APPLICATION NOTE 3560/7702. Introduction

APPLICATION NOTE 3560/7702. Introduction APPLICATION NOTE Order Tracking of a Coast-down of a Large Turbogenerator by Svend Gade, Henrik Herlufsen and Hans Konstantin-Hansen, Brüel& Kjær, Denmark In this application note, it is demonstrated how

More information

Fourier Signal Analysis

Fourier Signal Analysis Part 1B Experimental Engineering Integrated Coursework Location: Baker Building South Wing Mechanics Lab Experiment A4 Signal Processing Fourier Signal Analysis Please bring the lab sheet from 1A experiment

More information

Choosing the Best ADC Architecture for Your Application Part 3:

Choosing the Best ADC Architecture for Your Application Part 3: Choosing the Best ADC Architecture for Your Application Part 3: Hello, my name is Luis Chioye, I am an Applications Engineer with the Texas Instruments Precision Data Converters team. And I am Ryan Callaway,

More information

Experiment No. 6. Audio Tone Control Amplifier

Experiment No. 6. Audio Tone Control Amplifier Experiment No. 6. Audio Tone Control Amplifier By: Prof. Gabriel M. Rebeiz The University of Michigan EECS Dept. Ann Arbor, Michigan Goal: The goal of Experiment #6 is to build and test a tone control

More information

Using Root Locus Modeling for Proportional Controller Design for Spray Booth Pressure System

Using Root Locus Modeling for Proportional Controller Design for Spray Booth Pressure System 1 University of Tennessee at Chattanooga Engineering 3280L Using Root Locus Modeling for Proportional Controller Design for Spray Booth Pressure System By: 2 Introduction: The objectives for these experiments

More information

DECENTRALISED ACTIVE VIBRATION CONTROL USING A REMOTE SENSING STRATEGY

DECENTRALISED ACTIVE VIBRATION CONTROL USING A REMOTE SENSING STRATEGY DECENTRALISED ACTIVE VIBRATION CONTROL USING A REMOTE SENSING STRATEGY Joseph Milton University of Southampton, Faculty of Engineering and the Environment, Highfield, Southampton, UK email: jm3g13@soton.ac.uk

More information

Performing the Spectrogram on the DSP Shield

Performing the Spectrogram on the DSP Shield Performing the Spectrogram on the DSP Shield EE264 Digital Signal Processing Final Report Christopher Ling Department of Electrical Engineering Stanford University Stanford, CA, US x24ling@stanford.edu

More information

EE 215 Semester Project SPECTRAL ANALYSIS USING FOURIER TRANSFORM

EE 215 Semester Project SPECTRAL ANALYSIS USING FOURIER TRANSFORM EE 215 Semester Project SPECTRAL ANALYSIS USING FOURIER TRANSFORM Department of Electrical and Computer Engineering Missouri University of Science and Technology Page 1 Table of Contents Introduction...Page

More information

Islamic University of Gaza. Faculty of Engineering Electrical Engineering Department Spring-2011

Islamic University of Gaza. Faculty of Engineering Electrical Engineering Department Spring-2011 Islamic University of Gaza Faculty of Engineering Electrical Engineering Department Spring-2011 DSP Laboratory (EELE 4110) Lab#4 Sampling and Quantization OBJECTIVES: When you have completed this assignment,

More information

System analysis and signal processing

System analysis and signal processing System analysis and signal processing with emphasis on the use of MATLAB PHILIP DENBIGH University of Sussex ADDISON-WESLEY Harlow, England Reading, Massachusetts Menlow Park, California New York Don Mills,

More information

Laboratory Test of Vibration of Micro/Nano Satellite for Environment Test Standardization

Laboratory Test of Vibration of Micro/Nano Satellite for Environment Test Standardization Laboratory Test of Vibration of Micro/Nano Satellite for Test Standardization Amgalanbat Batsuren, Toru Hatamura, Hirokazi Masui, Mengu Cho Interaction Kyushu Institute of Technology 5 th Nano Satellite

More information

TABLE OF CONTENTS CHAPTER TITLE PAGE DECLARATION DEDICATION ACKNOWLEDGEMENT ABSTRACT ABSTRAK

TABLE OF CONTENTS CHAPTER TITLE PAGE DECLARATION DEDICATION ACKNOWLEDGEMENT ABSTRACT ABSTRAK vii TABLES OF CONTENTS CHAPTER TITLE PAGE DECLARATION DEDICATION ACKNOWLEDGEMENT ABSTRACT ABSTRAK TABLE OF CONTENTS LIST OF TABLES LIST OF FIGURES LIST OF ABREVIATIONS LIST OF SYMBOLS LIST OF APPENDICES

More information

SYSTEM IDENTIFICATION: A STUDY OF VARIOUS METHODS FOR CONTINUOUS SYSTEMS

SYSTEM IDENTIFICATION: A STUDY OF VARIOUS METHODS FOR CONTINUOUS SYSTEMS SYSTEM IDENTIFICATION: A STUDY OF VARIOUS METHODS FOR CONTINUOUS SYSTEMS Ayush Raizada, Vishnuvardhan Krishnakumar, Dr. P. M. Singru Abstract This paper addresses and evaluates the methods of system identification

More information

sin(wt) y(t) Exciter Vibrating armature ENME599 1

sin(wt) y(t) Exciter Vibrating armature ENME599 1 ENME599 1 LAB #3: Kinematic Excitation (Forced Vibration) of a SDOF system Students must read the laboratory instruction manual prior to the lab session. The lab report must be submitted in the beginning

More information

29:128 Homework Problems

29:128 Homework Problems 29:128 Homework Problems Revised 22 Feb 2012 29:128 Homework 1 (15 points) references: Sections 1.6-1.7 & 4.8, Meyer Chapter 1 of Horowitz and Hill, 2nd Edition (1) In the circuit shown below, V in = 9

More information

THE STUDY OF TRAIN INTELLIGENT MONITORING SYSTEM USING ACCELERATION OF ORDINARY TRAINS

THE STUDY OF TRAIN INTELLIGENT MONITORING SYSTEM USING ACCELERATION OF ORDINARY TRAINS THE STUDY OF TRAIN INTELLIGENT MONITORING SYSTEM USING ACCELERATION OF ORDINARY TRAINS HIRONORI ISHII, YOZO FUJINO, YUSUKE MIZUNO, KIYOYUKI KAITO ABSTRACT Local railways, even though they have a very limited

More information

Lab 0: Introduction to TIMS AND MATLAB

Lab 0: Introduction to TIMS AND MATLAB TELE3013 TELECOMMUNICATION SYSTEMS 1 Lab 0: Introduction to TIMS AND MATLAB 1. INTRODUCTION The TIMS (Telecommunication Instructional Modelling System) system was first developed by Tim Hooper, then a

More information

Resonator Factoring. Julius Smith and Nelson Lee

Resonator Factoring. Julius Smith and Nelson Lee Resonator Factoring Julius Smith and Nelson Lee RealSimple Project Center for Computer Research in Music and Acoustics (CCRMA) Department of Music, Stanford University Stanford, California 9435 March 13,

More information

Homework Set 3.5 Sensitive optoelectronic detectors: seeing single photons

Homework Set 3.5 Sensitive optoelectronic detectors: seeing single photons Homework Set 3.5 Sensitive optoelectronic detectors: seeing single photons Due by 12:00 noon (in class) on Tuesday, Nov. 7, 2006. This is another hybrid lab/homework; please see Section 3.4 for what you

More information

SHOCK AND VIBRATION RESPONSE SPECTRA COURSE Unit 4. Random Vibration Characteristics. By Tom Irvine

SHOCK AND VIBRATION RESPONSE SPECTRA COURSE Unit 4. Random Vibration Characteristics. By Tom Irvine SHOCK AND VIBRATION RESPONSE SPECTRA COURSE Unit 4. Random Vibration Characteristics By Tom Irvine Introduction Random Forcing Function and Response Consider a turbulent airflow passing over an aircraft

More information

Transfer Function (TRF)

Transfer Function (TRF) (TRF) Module of the KLIPPEL R&D SYSTEM S7 FEATURES Combines linear and nonlinear measurements Provides impulse response and energy-time curve (ETC) Measures linear transfer function and harmonic distortions

More information

SIA Software Company, Inc.

SIA Software Company, Inc. SIA Software Company, Inc. One Main Street Whitinsville, MA 01588 USA SIA-Smaart Pro Real Time and Analysis Module Case Study #2: Critical Listening Room Home Theater by Sam Berkow, SIA Acoustics / SIA

More information

Windows and Leakage Brief Overview

Windows and Leakage Brief Overview Windows and Leakage Brief Overview When converting a signal from the time domain to the frequency domain, the Fast Fourier Transform (FFT) is used. The Fourier Transform is defined by the Equation: j2πft

More information

CHAPTER 4 IMPLEMENTATION OF ADALINE IN MATLAB

CHAPTER 4 IMPLEMENTATION OF ADALINE IN MATLAB 52 CHAPTER 4 IMPLEMENTATION OF ADALINE IN MATLAB 4.1 INTRODUCTION The ADALINE is implemented in MATLAB environment running on a PC. One hundred data samples are acquired from a single cycle of load current

More information

ECE438 - Laboratory 7a: Digital Filter Design (Week 1) By Prof. Charles Bouman and Prof. Mireille Boutin Fall 2015

ECE438 - Laboratory 7a: Digital Filter Design (Week 1) By Prof. Charles Bouman and Prof. Mireille Boutin Fall 2015 Purdue University: ECE438 - Digital Signal Processing with Applications 1 ECE438 - Laboratory 7a: Digital Filter Design (Week 1) By Prof. Charles Bouman and Prof. Mireille Boutin Fall 2015 1 Introduction

More information

SHOCK AND VIBRATION RESPONSE SPECTRA COURSE Unit 17. Aliasing. Again, engineers collect accelerometer data in a variety of settings.

SHOCK AND VIBRATION RESPONSE SPECTRA COURSE Unit 17. Aliasing. Again, engineers collect accelerometer data in a variety of settings. SHOCK AND VIBRATION RESPONSE SPECTRA COURSE Unit 17. Aliasing By Tom Irvine Email: tomirvine@aol.com Introduction Again, engineers collect accelerometer data in a variety of settings. Examples include:

More information

PYKC 13 Feb 2017 EA2.3 Electronics 2 Lecture 8-1

PYKC 13 Feb 2017 EA2.3 Electronics 2 Lecture 8-1 In this lecture, I will cover amplitude and phase responses of a system in some details. What I will attempt to do is to explain how would one be able to obtain the frequency response from the transfer

More information

N. Papadakis, N. Reynolds, C.Ramirez-Jimenez, M.Pharaoh

N. Papadakis, N. Reynolds, C.Ramirez-Jimenez, M.Pharaoh Relation comparison methodologies of the primary and secondary frequency components of acoustic events obtained from thermoplastic composite laminates under tensile stress N. Papadakis, N. Reynolds, C.Ramirez-Jimenez,

More information

Noise Measurements Using a Teledyne LeCroy Oscilloscope

Noise Measurements Using a Teledyne LeCroy Oscilloscope Noise Measurements Using a Teledyne LeCroy Oscilloscope TECHNICAL BRIEF January 9, 2013 Summary Random noise arises from every electronic component comprising your circuits. The analysis of random electrical

More information

Beating Phenomenon of Multi-Harmonics Defect Frequencies in a Rolling Element Bearing: Case Study from Water Pumping Station

Beating Phenomenon of Multi-Harmonics Defect Frequencies in a Rolling Element Bearing: Case Study from Water Pumping Station Beating Phenomenon of Multi-Harmonics Defect Frequencies in a Rolling Element Bearing: Case Study from Water Pumping Station Fathi N. Mayoof Abstract Rolling element bearings are widely used in industry,

More information

What Do You Think? GOALS

What Do You Think? GOALS Patterns and Predictions Activity 7 Special Relativity GOALS In this activity you will: Plot a muon clock based on muon half-life. Use your muon clock and the speed of muons to predict an event. Identify

More information

Testing Sensors & Actors Using Digital Oscilloscopes

Testing Sensors & Actors Using Digital Oscilloscopes Testing Sensors & Actors Using Digital Oscilloscopes APPLICATION BRIEF February 14, 2012 Dr. Michael Lauterbach & Arthur Pini Summary Sensors and actors are used in a wide variety of electronic products

More information