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Ultrasonic Sensors Calibration

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US Sensor Calibration. 1. Ultrasonic Sensors Calibration. Omar A. Daud ... US ... US Sensor Calibration. 5. In performing a calibration, the following ... – PowerPoint PPT presentation

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Title: Ultrasonic Sensors Calibration


1
Ultrasonic Sensors Calibration
  • Omar A. Daud
  • Truc-Vien T. Nguyen
  • May 16, 2008

2
Plan
  • Ultrasonic sensors
  • Calibration
  • Approaches
  • Analysis
  • Conclusion

3
Ultrasonic sensors
  • Evaluate attributes of a target by interpreting
    the echoes of sound waves.
  • Generate high frequency sound waves and evaluate
    the echo which is received back by the sensor.
  • Sensors calculate the time interval between
    sending the signal and receiving the echo to
    determine the distance to an object.

4
Plan
  • Ultrasonic sensors
  • Calibration
  • Approaches
  • Analysis
  • Conclusion

5
Calibration
  • In performing a calibration, the following steps
    are necessary
  • Examine the construction of the instrument,
    identifying the inputs.
  • Decide which of the inputs are significant for
    the application.
  • By holding some inputs constant, varying others,
    and recording the output(s), develop the desired
    static input-output relations

6
Plan
  • Ultrasonic sensors
  • Calibration
  • Approaches
  • Analysis
  • Conclusion

7
Static Calibration Approach
  • All inputs, except one are kept at some constant
    values. Then the one input under study is varied
    over some range of constant values, which causes
    the output(s) to vary over some range of constant
    values.
  • Considerable care in choosing the means of
    determining the numerical values of these inputs.

Object Distance Cm Mean Mean Mean Std Std Std
field 60 Cm Sensor 4 Sensor 5 Sensor 6 Sensor 4 Sensor 5 Sensor 6
Eighth_field 18,24 12,03 9 14,13 0,12 0
Quarter_field 41,13 19,92 17,85 21,64 0,19 0,33
Half_field 42,22 33,87 31,69 22,32 0,26 0,33
1_field 65,84 56,92 59,68 5,92 3,66 1,61
2_field 59,63 47,31 60,98 18,58 25,58 7,59
3_field 56,67 49,09 55,09 21,56 24,49 12,80
8
Correlation between Sensors - Distance
  • Support Vector Machine (SVM) Approach
  • LibSVM Polynomial kernel, degree 3, One vs.
    One
  • Parameter C 2 n-fold cross-validation n 10
  • 12 sensors accuracy 58.3667
  • 4 sensors 4,5,6,7 accuracy 84.5667
  • 3 sensors 4,5,6 accuracy 85.4333

9
Plan
  • Ultrasonic sensors
  • Calibration
  • Approaches
  • Analysis
  • Conclusion

10
Analysis Sensor 4
11
Analysis Sensor 5
12
Analysis Sensor 6
13
Analysis Three sensors
3 2 1 1/2 1/4 1/8
Mean 47.5 53 36.5 43 40.5 27
Std 28.43 31.61 22.08 25.84 24.39 16.6
Var 419.81 389.78 30.89 186.65 266.7 81.31
14
Gaussian distribution
Gaussian distribution in six distances
15
Plan
  • Ultrasonic sensors
  • Calibration
  • Approaches
  • Analysis
  • Conclusion

16
Conclusions
  • Farther is the object from the scene more
    inaccurate is the measurement of the US sensors.
  • By the contrary, as the object is near the
    sensors, the measurement is more accurate.
  • There is a sort of linear relationship between
    the input and the output until the measurement
    of 1 field.
  • Beyond the 1 field this relationship is lost.
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