Presentation is loading. Please wait.

Presentation is loading. Please wait.

Analysis of Rocket Flights Section 4, Team 4 Student 1, Student 2, Student 3, Student 4.

Similar presentations


Presentation on theme: "Analysis of Rocket Flights Section 4, Team 4 Student 1, Student 2, Student 3, Student 4."— Presentation transcript:

1 Analysis of Rocket Flights Section 4, Team 4 Student 1, Student 2, Student 3, Student 4

2 Temperature Predictions Decrease in temperature upon ascent Rise in temperature upon descent Further increase after landing

3 Thermistor 3 (middle of rocket body, on surface)

4 Thermistor 2 (on fin)

5 Altimeters Expect decrease in pressure with increase in altitude, and vice versa Used barometric equation to find altitude Calibrated sensors in lab using vacuum chamber

6 Altimeter vs. Models for Flight

7 Flight Modeling (2-D) CGCG CPCP mg D T y z r Wind T CGCG CPCP mg r Wind D y z θ

8 Euler’s Integration Method for numerical integration Iterative For given a(t) and initial conditions for x and v: v(t+Δt)=v(t)+a(t)*t x(t+Δt)=x(t)+v(t)*t

9 IMU Analysis: Mudd IIIC (Large) Rocket Rotation from local to global axes Euler integration of rotation matrix azaz axax ayay AyAy AzAz AxAx y azaz ayay axax

10 Processing Algorithm (Matlab) Raw RDAS Data (counts) Local Acceleration (m/s 2 ) Calibrations Global Acceleration (m/s 2 ) Global Velocity (m/s) and Position (m) Local Rotation Rate (radians/sec) Rotation Matrix (radians/sec) Calibrations Euler integration Local Rotation Angle (degrees) Filtered Global Acceleration (m/s 2 ) Acceleration Filtering (optional)

11 Principle Axis Rotation: Plot vs. Video

12 1-D Model Comparison (launch 2) day 1 2 nd launch (13-20 mph winds) IMU dataR-DAS pressure altimeter % difference from altimeter Student model % difference from model Rocksim model % difference from model Apogee height 160.3390 meters 154.53 m+3.759%147.3- 182.3 m (lies within range) 165.3 m-3.001% Apogee time 6.38 sec4.645- 6.145 sec +3.824%5.763- 6.293 sec +1.382%5.888 sec+8.356% Max z vel 54.35 m/sN/A 52.46- 58.88 m/s (lies within range) 57.24 m/s-5.049% Max z accel 206.4 m/s 2 N/A 180.8- 198.4 m/s 2 +4.032%202.5 m/s 2 +1.926%

13 Acceleration Filtering (Before)

14 Acceleration Filtering (After)

15 Acceleration Filtering (Descent Plot) E80 teams wind z

16 Bad Data Mudd IIIA IMU rocket  Failure to eject parachute  Flat spin  crash after apogee  WHY? http://www.tribuneindia.com/2002/20020715/world.htm

17 Principle Axis Rotation Plot vs. Video, Round 2

18 Acceleration Data… Very pronounced 0.2149 Hz oscillations Possible causes: camera interference, camera overpowering Band-stop filter might be able to retrieve data

19 Vibration Analysis

20 Tap tests on hollow tube are inaccurate Mass spring damper system Theoretical Analysis

21 Spring-Mass-Damper Model Rocket can be modeled as a single degree of freedom spring- mass-damper system. Effective mass, m Spring constant, k Damping  Half-Power Bandwidth Predicted Resonance Frequency 

22 Analysis No control variables! Treat Sensor 10 as input. Create FRFs of other sensors to see relative peaks Sensor 10

23 FRF plots Removed DC offset fdomain.m used to generate Fourier Coefficients Relative Amplitudes First set of data is not trustworthy Second set of data has more coherent peaks Used 1 st second of data, short motor burn time

24

25 1 st Set of Data Results Peak around 60 or 70 Hz Other peaks are inconsistent Sensor 15 seems to be malfunctioning Locally, 3 sensors show local peaks between 60-80 No video

26

27 2 nd Set of Data Results Consistent peaks at 64 Hz Possible peaks around 30 Hz, but not consistent Sensors 1, 3, and 8 are 13 show peak frequencies Sensor 13 farther away from the input source

28 Noises Only 64 Hz showed in every FRF Others are jumbled by the noise Running averages smoothes out the data too much.  Too little data during the 1 st second of input  Ineffective way of removing noise

29

30 Mode Shapes Absolute magnitude of Fourier Coefficients vs Relative Sensor Distances Sensor 10 was normalized as “0” point.

31 Results from FRF Not enough frequencies to test all 3 mode shapes Does not deal well with noise, especially with highly aliased data

32 Problems with FFT Using just FFT coefficients to calculate Frequency Response Functions assumes a clean periodic signal. The rocket data is neither. A better estimator is Power Spectral Density (PSD).

33 Power Spectral Density Auto power spectral density Cross power spectral density Frequency Response Function

34 PSD and Noise H(j  x(t)v(t)y(t) n(t) Assume n(t) is unrelated to v(t) 0

35 Hamming Window Time DomainFrequency Domain

36 Averaging Overlap Overlapping windowed segments by 50% minimizes attenuation of time domain signal near the end of segment

37 Frequency Response Function

38 Waterfall Analysis freq (Hz) time (.1 sec) magnitude (dB) FRF of Sensor 5 over time

39 Conclusions Thermistor behavior depends on location Euler Integration Method not sufficient to model whole flight path Spring-Mass-Damper model can simplify system to find theoretical resonance FFT method of finding FRF is not consistent due to large noise component PSD method gives much sharper peaks in FRF

40 Interesting Precautions... Check battery…sensors are sensitive! Wait until last moment to turn on R- DAS and video camera…otherwise, ejection charge could go off early! Don’t try to catch rocket…it may have a chute, but it’s still falling fast!

41 Extra: Altimeter Plots

42

43 Extra: Why We Didn’t Do 2-D Model Comparison

44

45 Acknowledgements The professors and proctors who helped to make this beta-test a success. All of our classmates for their infinite support and advice during this semester Student A for a discussion on the causes of small rocket IMU corruption Student B for his help with setting up the Single Degree of Freedom model

46 References E80 The Next Generation Spring 2008, http://www.eng.hmc.edu/New E80/index.html. R. Wang, http://fourier.eng.hmc.edu/e80/inertialnavigation/ Q. Yang, http://www.eng.hmc.edu/NewE80/PDFs/Lecture_PressureSensor Thermistors.ppt H. Buchholdt, Structural Dynamics for Engineers (Telford, 1997), pp. 17-22. The Hanning Window, http://www.dliengineering.com/vibman/thehanning window.htm


Download ppt "Analysis of Rocket Flights Section 4, Team 4 Student 1, Student 2, Student 3, Student 4."

Similar presentations


Ads by Google