wind_sensor:meeting_minutes_apr_28_2017

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wind_sensor:meeting_minutes_apr_28_2017 [2017/04/30 10:53]
mwu [Ultrasonic Wind Sensor]
wind_sensor:meeting_minutes_apr_28_2017 [2021/09/19 21:59] (current)
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 =====Acoustic Wind Sensor===== =====Acoustic Wind Sensor=====
   * Updates:   * Updates:
 +    * Inaccuracies in single microphone wind speed algorithm due to assumption that all microphones are set the same way
 +    * To fix this, microphones were re-calibrated individually,​ each microphone calibrated with 8 wind speeds
 +    * Peak detector coefficients were determined for each microphone ​
 +    * Raw wind direction tests were conducted from 0 to 360 degrees using the new peak detector equations ​
 +    * Peak detector outputs of each microphone with the north microphone at 0 to 360 degrees were plotted
 +    * Using this raw data, microphone angle and ratio of the two largest microphone readings at each angle were plotted
 +    * A linear relationship was derived mapping the microphone angle to this raio 
   * To Do:   * To Do:
 +    * Conduct tests to verify relationship
 +    * Look at implementing some other filters (i.e. FIR)
 =====Ultrasonic Wind Sensor===== =====Ultrasonic Wind Sensor=====
   * Updates:   * Updates:
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       * We do this 500 times and average all the differences. This produces our propagation time.       * We do this 500 times and average all the differences. This produces our propagation time.
     * When testing our program with our setup, our results were pretty consistent (difference += 0.4us). We decided to start taking data points and testing with the anemometer.     * When testing our program with our setup, our results were pretty consistent (difference += 0.4us). We decided to start taking data points and testing with the anemometer.
-    ​+      ​The first thing we did was plot the measured propagation times at different wind speeds. 
 +      * We measured the propagation time with no wind speed and with the three speed settings on the black fan (note: we also tested it with the grey fan but because we may have shifted the box during the movement of the fans, the results weren'​t as consistent. We chose to omit them, but we will have to revisit this){{ :​wind_sensor:​prop_time_diff_speeds.png?​direct&​600 |}} 
 +        * These results are in line with our initial assumptions:​ increasing wind speeds in the direction of propagation will reduce the propagation time. 
 +        * There was one issue however: at the distance that we were testing, we expected our propagation time to be ~240us. However, our measured propagation time was around ~340us, which is significantly different. We believe this may be due to some constant time delay added into our measurements. 
 +      * To calculate this constant time delay, we use this equation:{{ :​wind_sensor:​time_delay_equation.png?​direct&​300 |}} 
 +        * t_meas is our measured propagation time from our setup, V_wind is the measured wind speed using the anemometer, and V_sound is the speed of sound. We plotted t_meas against the inverse (V_wind + V_sound) to get this plot:{{ :​wind_sensor:​prop_time_vs_inverse_velocity.png?​direct&​600 |}} 
 +        * Looking back at the equation, we see that the slope of this plot represents the '​d'​ or distance, and the y-intercept of this plot is our time delay. Now that we know all our parameters, we can calculate the wind speed using the following equation:{{ :​wind_sensor:​wind_speed_eqtn.png?​direct&​300 |}} 
 +    * We also wanted to see what would happen if we plotted the wind speed against the measured propagation time. We were surprised to see that it was also very linear:{{ :​wind_sensor:​wind_speed_vs_prop_time.png?​direct&​600 |}} 
 +      * This meant that we could go directly from our measured propagation time to the wind speed, with the only caveat being that it would only work for a given temperature (since the speed of sound changes with temperature) 
 +    * In other news, we also finished our poster for the poster presentation and the final presentation for the SCEL general meeting.
   * To Do:   * To Do:
 +    * Instead of just using the first set of times to calculate the difference, try use all ten sets to see if the overall average becomes more stable.
 +    * Add in calculation of wind speed into program so it can print out the calculated wind speed directly, and conduct tests with more wind speeds and the other fan.
 +    * Experiment with amplifiers to see if we can increase the SNR (signal-to-noise ratio). This should give us better results. Also, see if we can utilize use the Schmitt trigger'​s two threshold levels to have one act as a "​qualification"​ and the other as the actual zero-crossing detector.
 +    * See if we can reduce the ringing of the emitter by sending 180-degree phase shifted pulses after we send our actual pulses (destructive interference).
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