Near Space Launch Applied Science Research Menlo School William Baldwin - Project Leader Nikhil Bhatia - Software Engineer Travis Chambers - Mechanical Engineer William Kittler - Quality Control John Strong - Experiment Designer Adam Yecies - Design Engineer December 16, 2013 Date Performed: December 5, 2013 Instructor: Dr. James Dann Abstract In this project we built, tested, and launched a compact payload into Earths atmosphere. Our payload was complete with a variety of calibrated sensors, 3 Hero 3+ GoPros, multiple GPS and transmitting systems, a data collection system, and a central battery system. The goal of the project was to bring back a variety of data and footage that would help us better understand the components of the Earths atmosphere and make sense of the relationships between different measurements at high altitudes. Our experiment was successful and resulted in breathtaking video and pictures of the Earth from above, as well as clear relationships between temperature, pressure, speed of sound, humidity, and altitude throughout the phases of Earths atmosphere. 1
Transcript
Near Space Launch
Applied Science Research
Menlo School
William Baldwin - Project LeaderNikhil Bhatia - Software Engineer
Date Performed: December 5, 2013Instructor: Dr. James Dann
Abstract
In this project we built, tested, and launched a compact payloadinto Earths atmosphere. Our payload was complete with a variety ofcalibrated sensors, 3 Hero 3+ GoPros, multiple GPS and transmittingsystems, a data collection system, and a central battery system. The goalof the project was to bring back a variety of data and footage that wouldhelp us better understand the components of the Earths atmosphere andmake sense of the relationships between different measurements at highaltitudes. Our experiment was successful and resulted in breathtakingvideo and pictures of the Earth from above, as well as clear relationshipsbetween temperature, pressure, speed of sound, humidity, and altitudethroughout the phases of Earths atmosphere.
During the space launch our payload traveled a total of one hundred thou-sand feet upwards into the sky passing through several layers of the atmosphere.The earths atmospheric layers include the troposphere, the stratosphere, themesosphere and the thermosphere; however, our balloon only traveled throughfirst two layers the troposphere and the stratosphere.
1.1.1 Troposphere
The troposphere stretches from the earth’s surface up until 12 kilometers,7.5 miles, when it becomes the Stratosphere. This layer makes up between70 and 80 percent of the atmosphere and is where life and weather preside.It is also home to 99 percent of the worlds water vapour, which is consistentwith our data our experiment collected using a humidity sensor on board thepayload. Humidity data will be discussed later in more depth in AppendixIV. Winds increase as you ascend through the troposphere, culminating in ajet stream which usually will occur in the upper troposphere, right underneaththe tropopause. Inversely, temperatures decrease severely with height with afactor of 6.5 degrees celsius per kilometer until the Tropopause is reached. Thetemperature drops from almost 20 degrees celsius at sea level to near -60 degreescelsius at the bottom of the Tropopause. The Tropopause is the border inbetween the troposphere and the stratosphere. Temperatures remain relativelyconsistent within the tropopause.
1.1.2 Stratosphere
After leaving the Troposphere, the Stratosphere continues for another 38kilometers for a total of 50 kilometers or 21.1 miles. This is the last layerthat our balloon entered. Opposite to the troposphere, temperatures withinthe stratosphere gradually rise with height. While the lower stratosphere cansee temperatures of around -60 degrees in the upper sections the temperaturecan rise to 0 degrees celsius. This rise in temperature can be attributed to theconcentration of ozone in the region. The ozone converts the suns solar energyinto kinetic energy, absorbing ultralight radiation. The lack of moisture in theair makes it extremely rare for clouds of any kind to form. Airplane pilotswill often fly in the Stratosphere because of this lack of clouds. Within theStratosphere is the ozone layer around 20 to 30 kilometers above the earth. Thislayer of ozone is earths main defense against UV light, absorbing 97 to 99 percentof the earths medium frequency waves. These range from 200 nanometers to315 nanometers. The ozone is created when rising air is photolyzed and ozonemolecules are produced from oxygen molecules. The air, rich with newly createdozone, circulates towards middle latitudes while ozone depleted air returns tothe low stratosphere. Without the ozone layer, life on earth would inevitably
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be different than it is today. UV rays are responsible for many types of skincancers and can damage DNA.
1.1.3 Mesophere
After the Stratosphere is the Mesosphere, the third layer of the atmospherewhich exists from 50 kilometers to 80 kilometers from the earths surface. At itscoldest, the Mesosphere can reach temperatures of down to -100 degrees celsius.Like the Troposphere, temperature drops with height. There is little to no watervapour in the Mesosphere because it all freezes out, creating noctilucent clouds,which sometimes can be seen after sunset if their are illuminated by sunlight.It is in the Mesosphere where most meteors burn up during their attempt topenetrate earths atmosphere.
1.1.4 Thermosphere
The final layer of the atmosphere, the thermosphere starts at 90 kilometersand ends into space. As its name suggests, the thermosphere is the hottest layerin the atmosphere. Because of the lack of particle, absorbing small amounts ofsolar energy can change the temperature dramatically. The thermosphere canrecord temperature of up to 1000 degrees celsius. Due to the lack of a largeatmospheric pressure, the gases in the thermosphere sort themselves by theirmolecular mass creating several small layers much like gold sifting to the bottomof a washbasin. Moving even further away from earth, the thermosphere blendsinto space, concluding the final layer of the atmosphere.
1.2 Applications of Atmospheric Science
Studying the layers of the atmosphere can help scientists understand moreabout the inner workings of global warming. One important topic to investigateis the greenhouse effect. This process works just like the physical greenhouse itis named after. Certain gases called greenhouse gasses such as carbon dioxideabsorb and emit infrared radiation. So when IR light from the sun that is notabsorbed by earth on its first pass through reflects off the earths surface andattempts to exit back into space, it is absorbed by greenhouse gasses and re-emitted back at earth. This radiation then comes into contact objects on earthraising their internal energy–their temperature. This is effect is crucial, becausewithout it at night time, temperatures would drop to unlivable lows; however,since the advent of the industrial revolution, egregious amounts of greenhousegasses have been artificially added to the atmosphere by man causing too muchIR radiation to return to earth. Even more troublingly, the earth has becomestuck in a positive feedback loop. The higher the global temperature raises,the more ice melts around the world. Without the ice keeping temperaturescool, global temperatures will continue to rise, melting even more ice. A cleardangerous cycle has begun.
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1.3 Experimentation
Since the group understood that the payload was going to have access toa wide range of altitudes as well as two atmospheric layers, we decided to trackpressure, temperature, humidity and speed of sound as the balloon ascended.Pressure was measured using a Vernier Gas Pressure sensor. Temperature wasmeasured using a SparkFun sensor. Humidity was measured using a HIH-4030humidity sensor. In order to measure speed of sound a MB1010 LV-MaxSonar-EZ1 distance sensor measuring a fixed distance of 5 inches was used. Since thesensor operates by recording the time it takes a sonar signal to bounce off afixed object and return, as the speed of sound changes, the computed distancedoes as well, even though the true distance remains the same. Early in ourtesting process we realized our distance sensor would occasionally give off erro-neous measurements. Thus, we took 60 measurements in quick succession fromthe distance sensor and averaged them to achieve a more accurate value. Thereading of this distance data did need a 10 millisecond delay as it was computedmultiple times in a loop that repeated faster than this computation occured.Thus, though pressure, humidity, and temperature were computed instanta-neously, the total delay for a cycle of sensor readings was 2100 milliseconds asthis was the delay of our entire Arduino loop combined with that of our distancesensor. This was how often a line of data was written to the SD card.
1.4 Models of Temperature and Pressure
There are two different models to compare our experimental data for tem-perature and pressure against.
1.4.1 Exponential
The first model, the exponential model for atmospheric pressure, is derivedusing the equation
P (h) = Po ∗ e−Mgh
RT
P (h) = Pressure (pascals)
h = height from Earth
Constants :
k = Universal gas constant for air :8.31432N ∗mmol ∗K
m = Molar mass of Earth′s air : 0.0289644kg/mol
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Po = Static Pressure at sea level : 101325pascals
g = Gravitational acceleration (9.80665m/s)
where temperature and gravity are assumed constant. The exponentialmodel works only for pressure and not temperature.
1.4.2 Empirical
The second is the Nasa empirical model, which uses three separate sets ofequations to estimate changes in pressure and temperature in regards to heightabove earth–or altitude. Each set of equations predicts the changes for tempera-ture and pressure within a given layer in the atmosphere. The temperature andpressure within the first layer of the atmosphere, the troposphere, are predictedby the equations
T = 15.04− .00649 ∗ h and p = 101.29 ∗ (T +273.1
288.08)5.256
p = Pressure (Pasceles)
T = Temperature (Kelvin)
h = Height above earth (meters)
The temperature and pressure within a subsection of the second layer of theatmosphere, the lower stratosphere, are predicted by the equations
T = −56.46 and p = 22.65 ∗ exp(1.73− .000157 ∗ h)
p = Pressure (Pasceles)
T = Temperature (Kelvin)
h = Height above earth (meters)
The temperature and pressure within the higher subsection of the strato-sphere, the upper stratosphere, are predicted by the equations
T = −131.21 + .00299 ∗ h and p = 2.488 ∗ [(T + 273.1)/216.6]−11.388
p = Pressure (Pasceles)
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T = Temperature (Kelvin)
h = Height above earth (meters)
In order to graph both the experimental model and the empirical model,the values for temperature and pressure were computed once every kilometerup to 30 kilometers. Once these values were computed they were ready tocompare with the actual experimental data. The experimental data alone forboth pressure and temperature can be seen within Experimental Results section.
Figure 1: Graph of The Dependency of Empircal and Exponential Temperatureson Altitude.
The recorded temperature data tracked extremely well with the NasaEmpirical Model for the first 10 kilometers of ascent; yet, after this periodsomething caused the data to become extremely sporadic for a distance of 15kilometers or a total of 25 kilometers above earth. However, at a height of 25kilometers the datas sporadic nature curbed and began to fit with the Empiricalmodel for the remainder of the journey (the last 5 kilometers to the height of30 kilometers above earth).
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Figure 2: Graph of The Dependency of Empircal and Exponential Pressures onAltitude.
Figure 3: Graph of The Dependency of Empircal, Exponential and Experimentalpressures on Altitude.
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1.4.3 Advantages of Empirical
The Nasa Empirical model has several advantages over the border and moresimplistic exponential model. A first obvious advantage is that the Nasa empir-ical model can calculate for the changes in temperature, instead of just leavingit constant, as in the case of the exponential model. Another advantage is thatthe Nasa Empirical model avoids the drop off that the exponential model en-counters caused by gravity and temperature not actually being constant whilestill being assumed as much. Since the Nasa Empirical Model is customizedto each different layer or sublayer of the atmosphere it is expected to be moreaccurate; however, the experimental data for pressure appears to line up moreaccurately with the Exponential Model, with the Empirical Models data swing-ing just below the two. Once graphed it is extremely difficult to detect theseadvantages within the pressure data because for the most part, the data fromall three overlap each other.
2 Experiments Conducted
Our experiment was designed in order to determine the following six objec-tives: Dependency of Distance (speed of sound) on Altitude, Altitude vs. Time,Pressure vs. Time, Temperature vs. Altitude, Pressure vs. Altitude. In orderto do so, we had to use a pressure sensor, a temperature sensor, a humiditysensor and a distance sensor. How each sensor functions is detailed below.
2.1 Temperature Sensor
To measure temperature we used a Jameco NTC-103-R Thermo-resistor.Unlike all other sensors we used in our experiment, this thermistor does notoutput a standard linear voltage. Instead it outputs logarithmic voltage num-bers. This made calibration of the sensor far more difficult. The small size andlightweight features of the thermistor allowed us to tape it to the outside of ourpayload.
2.2 Pressure Sensor
To measure the changes in pressure throughout the various levels of atmo-sphere we used a Vernier Gas Pressure Sensor, which is designed to measureabsolute pressure. This sensor contains a thin membrane separating two cham-bers: one open to the atmosphere, and one kept at a constant vacuum. As themembrane flexes, the sensor outputs a linear voltage to the attached micropro-cessor, in this case an Arduino Uno. The linear output makes the sensor easierto calibrate, and thus easier to interpret. We expected the pressure to lowerconsistently all the way through its flight, as our payload is not designed totravel through the mesosphere. Our data fits very well with NASA models mea-suring atmospheric pressure vs. altitude, which produces a smooth logarithmicdecrease in pressure all the way up to the payloads maximum altitude.
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2.3 Humidity Sensor
To measure humidity we used the HIH-4030 humidity sensor, this sensormeasures relative humidity and sends back an analog output voltage. Becauseof the sensors linear voltage output the voltage is easily processed. Our sensoris a thermoset polymer sensor which senses capacitance to measure relativehumidity. The sensor is essentially a small capacitor which uses a polymer asthe dielectric. The dielectric constant is the ratio between capacitance of thecapacitor using the dielectric compared to the capacitance of the capacitor whenusing a vacuum as a dielectric. This dielectric constant changes as the absorptionof water by the dielectric changes. In the absence of moisture, the dielectricconstant of the different polymers used in humidity sensors range from 2 to 15at room temperature, but the dielectric constant of water vapor is around 80at room temperature. This means as the polymer dielectric inside the humiditysensor absorbs more water the dielectric constant increases and with it thecapacitance of the humidity sensor increases as well. The amount of moisture inthe dielectric relies on both temperature and water vapor and relative humidityis a function of both temperature and water vapor pressure, because of this thereis a relationship between relative humidity and the capacitance of the humiditysensor.
2.4 Distance or ”Speed of Sound” Sensor
To measure the change in speed of sound we used the MB1010 LV-MaxSonar-EZ1 sonic range finder. This sensor records the time it takes a sonar signal sentout to return and sends back an analog output voltage. Like the humidity sen-sor, the distance sensor has a linear voltage output which makes the voltageeasy to process. In theory, as the payload increases in height, the density of themedium through which it is traveling should decrease. This change in mediumwould yield an increase in the speed of sound because sound moves faster in lessdense mediums. Because of this, the distance sensor should show a significantlylarger distance than when on Earths surface because it operates using sonar, asound based measurement system.
3 Physical Design
3.1 The Payload
The payload was designed to withstand extremely cold temperatures inorder to protect the temperature sensitive components sheltered within as well asto prolong the battery lives of the cameras and other electronics. Not only doesthe payload have to protect the electronic components from the cold but alsofrom impact with the ground shortly after the cut down. While the payload isequipped with a parachute, the parachute does not reduce the terminal velocityof the payload enough so that the unprotected GoPro cameras, Arduino boardsand various electronic sensors could survive impact. Both of these requirements
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are taken care of by the inherent impact absorbing and insulating ability of afoam shipping container. The foam has an added benefit of being easily cut andmanipulated in order to bore holes for cameras and wires to outside sensors.The antenna for the GPS was tapped to the long side of the payload on theoutside of the box in order to provide and uninhibited view of the surroundingand to keep it away from the possible electrical wire interference. Since thedistance sensor, temperature sensor and humidity sensor have to be outside ofthe payload in order to capture accurate data about the environment, wires aresent from the outside of the payload to the inside where the more temperaturesensitive Arduino board is located. Wires were also run through the top of thepayload, along one strand of the parachute and up to the string connecting theparachute to the balloon. This is where the nichrome wire is wrapped in orderto cut the payload away from the balloon. The distance sensor is epoxied tothe outside of the payload in a small 3D printed rectangular open box. On theinside the payload there were two arduino boards, two solderless breadboards,three GoPro Hero 3+ cameras, a Lumsing 11000mAh external battery, a spotconnect gps back up, four capateries and cutdown circuit, a pressure sensor andDr. Danns iPhone 4s. Each component was secured either to the floor or a wallby permanent grade double sided 3M adhesive tape. The cameras each have acarved out hole for them to rest in snugly and have a power cord linking themto the external battery. Dr. Danns phone is also connected to the externalbattery. The Spot GPS and Dr. Danns phone are not permanently secured toanything within the payload because we didnt want to damage either device.The payloads final weight clocked in at 2.85grams.
3.1.1 The Payload Harness
The payload is connected to the parachute/balloon by a harness constructedof paracord and a carabiner. The harness wraps around the payload snugly,with one stand of paracord per side. The strand of paracord on the side ofthe distance sensor slides through a notch in the distance sensors encasementwithout a problem. All four strands meet at the top and are connected to acarabiner. On the side of the payload on each strand they are loops to whichfour more strands of paracord are attached. Those four strands meet and arefashioned together above the payload to create a pyramid in order to providestability for pictures and video. The top of the pyramid is then connected tothe bottom of the parachute which connects to the balloon above.
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Figure 4: Diagram of long left side of payload.
Figure 5: Diagram of payload with distance sensor.
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Figure 6: Diagram of payload with camera mounting hole.
3.2 The Cut-Down Mechanism
Our cut down mechanism used high resistance 28 gauge nichrome wire tosever the string attaching the balloon to the payloads parachute. When currentis run through the wire, it heats up quickly because of its high resistance, andmelts the string. Using the equation V=IR, we were able to calculate that 10volts must be applied to the wire in order to get the 3.3 amps required for thewire to become hot enough to cut the string. To provide this voltage difference,we used capatteries. Each capattery was able to hold a charge of 2.7 voltsmeaning we needed at least 4 capatteries wired in series to achieve a total of10.8 volts.
3.2.1 Capatteries
Capatteries are used to store and discharge energy at the rate of a tradi-tional battery. Normal capacitors store energy using two metal plates separatedby a non-conducting material a dielectric. Such dielectric materials includeceramic, glass or air. When charged, the electrons accumulate on one of themetal plates creating a positively charged side and a negatively charged side.The electrons are attracted to the positive side but cannot pass through thedielectric. When the circuit is completed, a path is created for the electronsto flow from one metal plate to another. The capattereies we used, also knownas ultracapacitors, use electrochemical principles to replace the solid dielectric.The two metal plates are covered in an electrolyte known as activated carbon.
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Ultracapacitors are unique in that they have two layers of charge on each plate,this allows the ultracapacitors to work as two capacitors in series. This qualityenables ultracapacitors to release the energy over a longer period of time thantraditional capacitors.
Figure 7: Diagram of capattery design.
Although it is possible to simply pop the balloon as the cut downmechanism, we wanted a more controlled method that would not leave us withthe remnants of the balloon. To do this we chose a pre-determined pressureand compared this to the pressure readings from our pressure sensor. Whenthe pressure readings reached the pre-determined pressure, we engaged the cutdown mechanism. To prevent from a premature cut down from a voltage spikeor an errant reading from the pressure sensor, we ensured the sensor wouldhave to read a reading below our pre-determined pressure number 10 timesin our Arduino code. When this happened the Arduino sent power throughthe electromagnet in the relay, triggering the Arduino to complete the circuitbetween the capatteries and the Nichrome wire. When this circuit is completedthe charge stored in the capatteries is discharged sending 3.3 amps through theNichrome wire.
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Figure 8: Diagram of Cut-Down mechanism circuit. The diagram shows thefour capatteries, the Arduino Uno, a relay and the Nichrome wire coil.
3.3 The Reel In System
3.3.1 Mechanical Advantage
Mechanical advantage is a measure of the force amplification achieved byusing a tool, mechanical device or machine system. It is one of the most usefultools on the workbench of an engineer in that its application is in almost everymotor system in the world. Mechanical advantage relies on the idea of a lever,which is when different forces are applied at different distances from a fulcrumor pivot point. The type of mechanical advantage used during the tetheredballoon launch was a similar one to that used in a bicycle, two gears attachedwith a chain. The increase in size of the gears provides greater force because ithas a greater radius. The big gear will have a lower RPM than the small gearbut it will make up for it in increased force.
Figure 9: Diagram of the right side of the reel in system.
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Figure 10: Diagram of the rear side of the reel in system.
Figure 11: Diagram of the left side of the reel in system.
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Figure 12: Diagram of the top of the reel in system.
3.3.2 Design
The DC motors we were allowed to use for the tethered launch could notgenerate enough force to reel in the balloon (which had an upward buoyant forceof 28.2 N) on their own. The Upward buoyant force was found by the equation:
Forcebuoyant = ρgv
Forcebuoyant = ρg(πr2)
Forcebuoyant = (1.225kg
m3)(9.8
m
s2)(π ∗ 2.25m2)
Forcebuoyant = 28.2N
However, the reel in system only had to pull down the net buoyant force(15.5N)which is found by the equation:
The equation shows that the Net buoyant force is equal to the buoyantforce with the downwards force of the payload subtracted off. In order to pullthe balloon back down, we had to implicate mechanical advantage. We fixed asmall gear with a radius of .98 in, to a larger gear with a radius of 3in. Thelarger gear was attached to a horizontal steel dowel which was inserted intotwo ball bearings in wood. I used a steel dowel rather than wood in order toprevent warping or bending from the tension in the reel in string. In order totest the reel in system, we attached a 12lb (53.4 N) weight to the system andit was able to reel it in, however quite slowly. The mechanical advantage of thereel in system can now be calculated because 53.4N was around the maximumforce the large gear could output. The ratio of the force between the two gearsis the same as the ratio between the radius of the gears. The ratio of the twogears was 0.98in / 3in, so to solve how much force the motor was generating wecalculate:
radiussmall
radiusbig=forcesmall
forcebig
0.98
3=
x
53.4
x = 17.44N
From this calculation we see the the larger gear more than tripled theamount of force than just the motor alone, thus reeling in the payload andballoon.
3.3.3 Results
In all, the reel in system was a fantastic success for our group, it pulledthe balloon down with ease without any issues. There were some issues in thebuilding process of the smaller gear getting pulled off the motor when there wastoo much stress on the axle system. This was solved by generous amounts ofepoxy and a very tight nut on the axel of the motor. However, on the day ofthe tethered launch, the system worked flawlessly. The chain didn’t fall of thegears and the payload returned just as it had left.
3.4 Batteries
3.4.1 The Alkaline Battery
A battery is considered two or more connected cells that produce a directcurrent by converting chemical energy to electrical energy. An alkaline batteryis dependent on the reaction between zinc and manganese dioxide, and is themain battery used in around 80 percent of electronics around the world. Thechemical equation is detailed as:
This reaction is generally very efficient in the running of electronics. The amountof current a battery can output tends to be proportional to the size of the batteryitself; in our payload, we used the standard 9-volt sized battery.
3.4.2 Environmental Effects on Batteries
High in the stratosphere, temperatures fall very low. A standard alkalinebattery that can be found at most stores starts to fail if it gets below a certaintemperature. As shown in the following diagrams, an alkaline battery will freezeat temperatures below -20C. A frozen battery does not put out as much currentas when it is warm, so for our project I turned to using lithium ion batteries.A cold alkaline battery emits much less current when it is cold because like anychemical reaction, it goes much slower when it is cold. Lithium-ion batterieshave a much lower freezing point than alkaline batteries so they were perfect forgoing to space.
Figure 13: Diagram alkalnine battery performance and lithium ion battery per-formance as a result of temperature.
Figure 14: Diagram alkalnine battery performance and lithium ion battery per-formance as a result of temperature.
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C + LiCoO2 ←−→ LiC6 + Li0.5CoO2
LiCoO2−Li+−e– ←−→ Li0.5CoO2 => 143 mAhg
3.4.3 The Lithium Ion Battery
Lithium ion batteries contain a liquid mixture of thionyl chloride (SOCl2)and lithium tetrachloroaluminate (LiAlCl). These batteries are also optimal foruse in situations where the battery will be sitting for extended periods of timesuch as a fire alarm. They have a very long shelf life and are more expensivein most cases. Over The lithium batteries were used for the arduino and thebattery backpacks for the gopros. The battery backpacks allowed the Goprosto stay charged throughout the balloon flight and survive the cold temperaturesand low pressures. If the batteries didnt work, none of the sensors, cameras, orelectronics would work therefore we would get no data and the project wouldhave been a failure.
4 Electrical Software and Design
4.1 Radio and GPS System
4.1.1 Wiring
We wired our output from the GPS receiver into pin 10 on the Arduino.The input to the transmitter was set to pin 8 on the Arduino. Additionally,GPS receiver was connected to the 3.3V pin and one of the ground pins and theNTX2 transmitter was connected to the 5V pin and one of the ground pins.
Figure 15: Diagram of GPS tracking system circuit.
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4.1.2 Description
The second Arduino UNO R3 in our payload was used to get GPS data andtransmit it to a handheld radio. Our radio and GPS program first checked for apresent and valid GPS system. If this GPS is incorrectly wired or not present,an error message is thrown to the Serial monitor and the program tries to findthe GPS once again. If it is successful in finding the GPS, the program reads inthe GPS coordinates from the output pin of the GPS. Because this reading isin a special $GPMRC format, our program then reformats it into an intelligiblestring with the format:
Lat: 00000.00N/S Long: 00000.00E/W
However, the computer program we used to decipher the sound output from ourhandheld radio required a specific string format. Thus we then converted thislatitude and longitude string into the following format:
$$Will Launch, ID #, time, latitude, longitude *checksum
The checksum in the above format was calculated using a special checksumalgorithm. This algorithm is commonly known as a longitudinal parity check.It breaks the data down into specific words each with a fixed number of bits.It then computes the exclusive or of all of the words. This result is appendedto our original string with a * before it so that the deciphering program knowswhere the checksum begins. This reconstructed string is then passed through theRTTY transmitting style and checked for a valid checksum. If the checksumis invalid, incomplete, or missing, the program throws another error to theSerial monitor and gets new GPS coordinates, starting the process again. If thechecksum is valid, the transmitting pin on our transmitter is pulled to high andthe transmission of our data string is initiated. After the data in transmitted,the program loops back to retrieving new GPS coordinates, starting the processover again.
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Figure 16: Flow chart of GPS and radio circuit.
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4.2 Microcontroller Data-Taking System
4.2.1 Wiring
We wired our SD card output into pin 10 with assisting secondary portsto pins 11, 12, and 13. Our distance sensor output was wired to pin A0. Ourpressure sensor output was wired to pin A1. Our humidity sensor output waswired to pin A2. Our temperature sensor output was wired to A3. Each sensorand SD card was also wired to 5V (power) and ground.
Figure 17: Diagram of data collection circuit.
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4.2.2 Description
We programmed an Arduino UNO R3 to take data from our distance,pressure, humidity, and temperature sensors and write these readings to an SDcard. Our program begin with a check to see if the SD card was initializedand present. If there was no SD card in the slot or the card reader was wiredincorrectly, the program would print an error message to the Serial monitor. Itwould then continue to check for the SD card until it was properly initialized.Once the SD card is properly initialized, the program reads in voltage outputsfrom the pressure, temperature, humidity, and distance sensors and stores eachin its own variable. We then use conversions from our calibration experimentsand sensor data sheets to convert each voltage output to a true sensor valueand format the sensor values into one string. Next, our program checks the SDcard for a data file to write to. If this data file does not exist, an error messageis printed to the Serial monitor and the program reads in a new set of data. Itthen repeats, once again checking for a data file to write to. If this data fileis found, it writes the formatted string to a new line in the data file. Oncethis occurs, the program goes back to reading in a new set of sensor values andcontinues through the rest of the loop again.
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Figure 18: Flow chart of data collection circuit.
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5 Tracking
5.1 Radio Signals
Since first being demonstrated in 1887 by Heinrich Hertz, radio wavesand signals have drastically changed the world given their involvement in alarge variety of modern technology. Radio waves occupy the section of theelectromagnetic spectrum with wavelengths ranging from one millimeter to one-hundred kilometers. Radio waves are low energy electromagnetic waves that areused to transmit data. Whether the data is music, cell phone signals or evenGPS coordinates, radio signals all operate on the same basic principles. In itssimplest form, a radio system consists of a transmitter and a receiver.
Figure 19: Diagram of the electromagnetic spectrum.
5.1.1 Transmitting
The transmitter works by operating at a base frequency then using pro-cesses known as amplitude modulation or frequency modulation. In amplitudemodulation, the amplitude of the wave modified to encode data, whereas infrequency modulation, the frequency is modified. Regardless of the mode usedto encode data, the signal is then transmitted via an antenna of correspondingfrequency. In order for the antenna to transmit correctly, it must be a fractionof the transmitting frequency. Once transmitted, the signal is out for reception.
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Figure 20: Diagram of amplitude modulation.
Figure 21: Diagram of frequency modulation.
5.1.2 Receiving
After transmission, the signal is then picked up by a receiver. In order toreceive a signal, a similar antenna to the one used to transmit is needed. Thereceiver must then be tuned to receive the specific frequency using a resonator.The resonator is set up to resonate at a specific frequency, blocking out allother interfering signals. Using this process, people are able to use radio wavesto communicate across the globe or even into space.
5.2 The Global Positioning System
The first GPS or global positioning system was introduced in 1973 by theUnited States Air Force. Originally, it as strictly used for military operationssuch as missile aiming systems and navigation, however, in 1989, the launch ofthe GPS II satellite gave way to an area of publicly open GPS satellites. Thecurrent system is comprised of twenty-four GPS operating satellites operatingin geosynchronous orbit at 12,600 miles or 20,300 kilometres. Because of thegeometries of Earth compared with the satellites orbits, any GPS receiver onEarth always has a direct line of sight to at least four satellites at any giventime. The receiver and GPS use a process known as trilateration to develop apoint of interest or the position of the receiver. Trilateration involves the usageof the distances between the receiver and three GPS satellites. From thesemeasurements, the current GPS systems are able provide an accurate locationof the receiver within a twenty foot radius. However, in order to reduce thiserror, the current system is slowly being replaced. By 2020, the United Statesplanes to be operating on a generation three system which will include newsatellites with clocks accurate down to a fraction of a billionth of a second andlocational accuracy up to three feet.
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Figure 22: Diagram of trilateration.
5.3 Antenna Gain
Antenna gain, a measurement expressed in dBi, decibels respective to anisotropic radiator, is the measure of an antennas ability to either transmit orreceive in or from a specific direction. In a transmitting antenna, the measure-ment is defined as an antennas ability to convert its input into directional radiowaves, whereas in a receiving antenna, it is defined as an antennas ability toconvert receiving waves into an output. The specific gain of an antenna dependson the power gain, which is a result of an antennas efficiency and directivity.These relationships can be outlined by the following equations:
Gpower = Eantenna ∗D
GdBi = 10 ∗ log10(Gpower)
Eantenna = The efficiency rating of the antenna
D = The directivity of the antenna
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5.4 Our Tracking System
From the inception of the project, we knew that tracking the payloadwould be a fundamentally important part of the project. With both its mon-etary value, the three GoPros and the electronics, and its immeasurable value,the irreplaceable data, we certainly did not want to lose track of the payloadonce it landed. In order to ensure that we didnt lose track of our payload, wedecided to install not one, not two, but three tracking systems. These threetracking systems comprised of a ham radio system, hand built by us, a SPOTConnect GPS tracking system and an iPhone equipped with the Find My iPhonesoftware. Both the SPOT Connect and the iPhone are fairly self explanatory interms of setup and usage and very little explanation. They are both are used bysimply checking the coordinates on an external website or app. The ham radiosystem on the other hand, involved two primary components, the in-payloaddata sending network and the earth based data retrieval station.
5.4.1 The Payload Components
The components in the payload include a SparkFun Venus GPS receiverwith its antenna, and a Radiometrix NTX2 transmitter operating at 434.65 Hzwith an antenna of the same frequency. These components are mediated by anArduino Leonardo which in simplest terms, provides the transmitter with theGPS coordinates in a correctly formatted string. In more complex terms, theArduino receives the output of the GPS receiver as a combination of variousmeasurements in different formats. Our code selectively chooses the $GPMRCfield of coordinates and organizes them into two numbers of latitude and lon-gitude separated by a comma. Next, our transmitting code organizes this datainto our string which consists of a callsign, an ID number, time, latitude andlongitude. Our callsign, Will Launch, is an identification number used in theHAM radio world to identify a radio signal with a specific operator. Our IDnumber is any integer which is used specifically for identifying yourself amongother balloon trackers. The time is a log of the time since initiation or take off.This string then passes a checksum, verifying the content of the string, and istransmitted as an RTTY transmission. A typical string of our data looked likethis:
This specific string format is necessary because when it is transmitted as adata packet through our 434.65 Hz frequency, it is converted into tones. We thenpick up the tones using a Kenwood TH-F6 ham radio in USB mode. The radiooutputs the string as a tones which are similar to the sound a warbler bird makes.The radio is linked to a computer running the software dl-flidigi, a open sourceradio interpretation software. We set up the software to correctly interpretour data packet, which it then packets and processes. Meanwhile, the software
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communicates with an external server entitles space near us (spacenearus.com),which plots the coordinates of the payload on a map showing its location.
Figure 23: Diagram of dl-fldigi decoding an RTTY data packet.
5.4.3 Range Testing
To test line of sight for the GPS systems, we sent the balloon and payload to300 meters for the tethered launch. This was the maximum distance we testedline of sight and it worked perfectly the whole test.
To test the GPS system with obstructions, we set up the receiving stationin Atherton, then placed the payload in a car and drove around the Athertonand Menlo Park area. The system performed admirably in these tests as well.
6 Sensor Calibration
6.1 Pressure Sensor Calibration
To measure pressure we used a Vernier Gas Pressure Sensor with an ArduinoUno microprocessor to record the pressure data. The Arduino recorded a singlevoltage number that corresponded with a certain pressure from the pressuresensor. To calibrate pressure, we placed the Vernier sensor and an Extech SD700Datalogger (the calibration standard) in the vacuum chamber. Both sensorsrecorded data as the chamber was brought down to near-complete vacuum, andthen slowly released. The Extech Datalogger recorded pressure in hPa, andrecorded the pressure once every five seconds (not an average over five seconds),whereas the Arduino recorded a voltage number once per second. We graphedthe data taken from the Arduino against the data taken from the Extech togenerate a linear equation which converted voltage readings from the Arduinointo hPa, shown in following graph. Our pressure recordings ranged from 8.5hPa to 1016.6 hPA. Our data fit perfectly to a linear trendline, of which the
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function was:
Pressure = 2.505 ∗ (arduino voltage reading)− 247.5
Because our data was extremely consistent, we generated a percent error of0.2112%.
Figure 24: Calibration graph for Vernier Gas Pressure Sensor: Compares actualpressure (Y-axis, hPA) to arduino voltage number (X-axis, no units) providingan equation for calculating the correct atmospheric pressure. Linear fit function:y = 2.505x - 247.5.
Calculations for Error Bars:
Uncertainty Value =08.005291
Slope = 2.505
(0.005291
2.505) ∗ 100 = 0.2112% Error
6.2 Temperature Sensor Calibration
The process for calibrating our temperature sensor was relatively similarto that of the pressure sensor. Our SparkFun temperature sensor, wired to thearduino microcontroller, outputted a single voltage number that correspondedto a single temperature. Initially, we attempted to calibrate that sensor withthe Extech SD700 Datalogger by recording data on both sensors at the same
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time in a freezer. However, we found that either the freezer never bottomed out(which was problematic because we then could not synchronize the data pointsbetween arduino and Extech), or that our procedure was flawed and the arduinomalfunctioned at low temperatures. We altered our strategy to record data atdifferent temperatures (mostly below -10 C), at different times in the freezer. Wethen compared that data to recorded readings from our temperature calibrationstandard, a Fieldpiece ST4 Dual Temperature Meter. Because the sensor weused for our calibration standard could not record data autonomously, we tapedthe dual sensors inside the freezer arduino and kept the display outside so thatwe could record data manually. This also meant we had to wait for the freezerto bottom out at a constant temperature for 2 plus minutes before recordingthe temperature off of the ST4. Although this procedure yielded actual datapoints, the data we gathered seemed extremely inconsistent, would not producean accurate logarithmic equation from which we could convert arduino voltagenumbers into a real Celsius temperature. The data we tested it at ranged from-43 C to 20 C. We fit our data to a logarithmic curved fit, to which the equationwas:
Actual Temperature = 17.432 ∗ ln(arduino reading)− 96.304
Although our data and the trendline was not totally consistent above zero de-grees Celsius, the large majority of data taken during the space launch (whichis the data that matters most) was below zero degrees Celsius. This contributedto a percent error of 10.247% generated by our data.
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Figure 25: Calibration graph for the NTC-103-R temperature sensor: Comparesactual temperature (Y-axis, C) to arduino voltage number (X-axis, no units)to produce a logarithmic calibration equation. Temperature function: y =17.43(ln(x)) - 96.3. Note: Our data was somewhat inconsistent, yielding apercent error of 10.246%
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7 Experimental Results
7.1 Data
Figure 26: Table of summary of data
7.1.1 Description
Averaged sensor values are given for each interval of 5 km. NA representsdata that was either very untrustworthy or a max sensor output. Both thedistance and temperature sensors were shaken loose or unable to take accuratedata due to excessive swinging and thus outputted faulty data. A clear decreas-ing relationship can be seen in the humidity, pressure, and temperature data,while the distance data shows an upward trend.
7.2 Pressure
We graphed our gathered pressure data against calculated Altitude data.Our altitude was calculated using the equation
H = −8.42 ∗ ln(P
1013.25)
where H is the altitude above sea level and P is the given pressure taken from ourVernier sensor and any given moment. However, this equation is most accurateup to 80,000 ft. This meant that for our pressure readings above that height,we were expecting some deviation from the accepted graph. It does not seemlike this inaccuracy made much of a difference at all for these higher altitudepressure readings, as indicated by our error-bars. These miniscule error-bars
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(so much so that you cant see them) indicate that our data was very accurate.Pressure data recorded during space launch ranged from 26.19 hPA to 1010.7hPA.
Figure 27: Graph of data taken from Vernier Gas Pressure Sensor against cal-culated altitude. Note: Although there appear to be no error bars, there are.The calculated error bars for our pressure data (0.2113%) are too small to seeon this scaled graph.
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Figure 28: Graph of pressure data (Y-axis, hPA) against time of experiment.The constant initial pressure indicates the time between data started recordingand the balloon was released. Pressure can be seen dropping somewhat slowlyas the balloon ascends, while rising very quickly during the parachute-assistedfall.
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7.3 Temperature
Although calibrating the temperature sensor was the most time-consuming,and perhaps the most inaccurate calibrations, we gathered temperature datathat fit well with temperature models of the atmosphere. Our temperaturesensor malfunctioned between altitudes of about 10km and 22km, recording aconsistent temperature of 128C. We deleted each data point at 128C to providethe most consistent and accurate data available. Beyond 22 kilometers, ourtemperatures sensor malfunctioned again, most likely due to excessive spinningand shaking that could have dislodged a pin. This led to random and sporadicdata beyond that altitude.
Figure 29: Graph of data gathered from the NTC-103-R temperature sensoragainst calculated altitude.
7.4 Humidity
Our relative humidity varied significantly more at lower altitudes than athigher altitudes, but as it slowly rose the humidity began to decrease consis-tently, as expected. This can be attributed to a number of factors. Our humiditydata is almost unreliable at low altitudes because of the huge range of valuestaken with a small change in height. Between 2 and 3 km, the relative humiditydrops from near 30% to under 5%, an unpredictable drop which can most likelybe attributed to different sources of error. Near sea level our payload experi-
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enced far more shaking and turbulence, which could contributed to inaccuracyand small malfunctions of our sensor. Another possible reason is that the aircloser to sea level experienced more changes due to sudden gusts of hot air, pol-lution, smoke, or anything resulting from human effects. Regardless, after thepayload reached near 10 kilometers above sea level our data became far morepredictable and dropped steadily as expected.
Figure 30: Graph of true humidity (Y-axis, %) as a function of altitude (X-axis,km).
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7.5 Altitude
Figure 31: Graph of calculated altitude (Y-axis, km) against time. Altitudewas calculated using the equation H = -8.42*ln(P/1013.25), where H is altitudeand P is any given pressure reading.
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7.6 Distance or ”Speed of Sound”
We used a sonar distance sensor to measure a fixed distance throughoutour payload’s flight. Because the speed of sound varies inversely with the squareroot of the density through which it travels, and the density of air changes withaltitude, the sensor’s measured distance should change as the sonar beam takesa longer or shorter period of time to return to the sensor. We hypothesizedthat the speed of sound would decrease with altitude for a majority of our flightas air density decreases in the troposphere, thus meaning our distance readingwould increase. According to the speed of sound model below, the speed ofsound should decrease by about 20 percent within the first 11 km of ascension.Our distance readings showed about a 30 percent increase within these first 12km. Starting at 15 km, the below model shows that the speed of sound beginsto increase again after leveling off at 11 km. Our graph shows a similar trendwith a plateau at 11 km and a decrease in distance starting at 15 km. The hugespikes in the data around these constant and more accurate plateaus of readingscan most likely be attributed to swinging and shaking of our payload. Distancetests of our sensor while swinging it and shaking it yielded very jumpy results,though it still displayed an accurate reading from time to time. Past an altitudeof 20 km, our distance sensor began to max out at 254 in, and thus we believea wire must have dislodged at that point, causing it to give completely faultyreadings.
Figure 32: Graph of distance of speed of sound sensor (Y-axis, inches) againstcalculated altitude (X-axis, km).
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Figure 33: Graph of accepted speed of sound as altitude increases.
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8 Conclusion
Our groups mission to send a payload into near space while recording dataduring the journey was ultimately success given that not only were we able to re-cover the payload but also, for the most part, record data both on the ascent anddescent. Apart from the actual scientific data our payload also accomplished anadditional goal of capturing high quality pictures and video from start to finishof the launch–two out of the three cameras captured all the way until completedarkness after the sun had set, while the other camera overheated after sittingin the tree for an hour and a half. These staggering photos have already beendebuted on both the menlo school website and the Menlo School facebook page,drawing extra recognition to the already highly respected ASR program. How-ever, with every success is not without the occasional failure, or in our projectscase, three failures. The first problem arose mid launch when our temperaturedata started to become increasingly random, yet roughly 10 kilometers later itappeared to return to following some sort of trend. The second problem thatwas potentially devastating for the recovery of the payload, was that the GPSreceiver appeared to have become unplugged from the arduino after the cutdown. The violent nature of the descent, which was caught on video, must haveshaken the pin lose. Without the ham radio sending coordinates back to Willslaptop, the payload recovery was contingent on two backup gps devices–Dr.Danns iphone and the Spot GPS–put in the payload for this very reason. Thisleads us to the final failure, the find my iphone app on Dr. Danns Iphone wasgiving a 6 mile wide search radius instead of an actual point. This occurredbecause the Iphone did not have a clear view of the sky and had to rely on itsconnection to a single cell tower to locate itself. Luckily our third GPS devicesent several accurate GPS coordinates which were all within a few feet of eachother but this was not without a few hours of nerve racking radio silence and afalse gps reading on the California Oregon border.
Our pressure data returned extremely accurate data, closely matchingcommon models of atmospheric pressure. This is attributed to the copiousamount of data taken from the pressure calibration in which our sensor recordedvalues ranging from 8.5 hPa to 1016.6 hPA, producing a calibration functionwith only 0.2113 percent error. Our temperature data was far less accurate. Thedata collected during calibration was inconsistent, proven by the 10% error ofthe calibration equation. Regardless, it matched up well traditional temperaturemodels of the atmosphere: cooling in the Troposphere (between 0 and 10 km),then warming up in the Stratosphere (12 to 50 km). Although there was noclear trend in our humidity data at low altitudes (¡10 km), it eventually balancedout and a consistent and curved decreasing trend could be found.
The space launch, with its hands on nature, has left us with two impor-tant conclusions, the importance of teamwork, and the necessity for redundancy.Like all group projects, the space launch has reminded us of the intricacies ofteamwork and helped every one of us improve on our abilities to work togetherefficiently. Without a well functioning team, our payload would not have beenready to go come launch day. Also, since two out of three of our GPS devices
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failed we are reminded of the importance of redundancy. If it had not been forthe Spot GPS, our payload would still be stuck in a tree, with little hope ofrecovery. AND finally, Remember, shoot for the stars and if you miss, you’llland amongst the california nut trees.
Will Kittler Check that all sensors are functioning properly and recordingdata; use a rangefinder to monitor the height of the balloon as it ascends;make sure that the data appears to be reasonable after the balloon returns
Johan Strong Make sure the payload is ready to launch
Nikhil Bhatia Make sure that all of the code is compiled onto the arduinoand ready to go
Will Baldwin Monitor the GPS data being transmitted to the ground andhelp with everything else
Travis Chambers Monitor the cut down mechanism
a. Check electronics
• SD card reader
• Micro SD card
• Trasmitter
• Humidity sensor
• Pressure sensor
• Temperature sensor
• Distance Sensor
b. Connect batteries to Arduinos
c. Updates current Arduino code
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d. Check connectin between ham radio and GPS transmitter
e. Charge the cut down capatteries
f. Power on the Arduino
g. Make sure that the data is consistent and reasonable
h. Turn the Gopros on and place them in their camera holes. Make sure theyare taking both video and pictures. Place the fully charged batteries intothe payload.
i. Place the harness around the payload.
j. Attach Parachute to the payload carabiner
k. Tie the box to the reel down system.
l. Tie the nichrome wire around the cut down rope and connect the wiresdown to the payload.
m. Attach payload to balloon ring
n. Let it fly!
o. Serenade yourself with the beautiful music of the ham radio
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9.2 Pre-Launch Form
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48
10 Appendix II
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11 Appendix III
In the Introduction.
12 Appendix IV
In the Experimental Results.
13 Appendix V
13.1 Microcontroller Data-Taking System Code
1 /∗2 Nikh i l Bhatia3 December 10 , 20134 Data Co l l e c t i on and Writing to SD Card56 Code uploaded to the data−t a k ing arduino . Co l l e c t e d
pressure , d i s tance , temperature , and humidi ty .7 The code a l s o wrote a l l o f the data c o l l e c t e d to an SD
card ( raw vo l t a g e va l u e s as w e l l as conver ted va l u e s )8 ∗/9
10 // i n i t i a l i z i n g por t s and o ther v a r i a b l e s11 int temperaturePin = A0 ;12 int d i s tancePin = A1 ;13 int humidityPin = A2 ;14 int pres sureP in = A3 ;1516 int counter = 0 ;17 // pres sure (hPa) at which we cut down18 double cutPress = 20 ;19 const int r e l a y = 8 ;2021 #include <SD. h>22 #include <math . h>
50
2324 const int c h i p S e l e c t = 10 ;2526 // ensures S e r i a l por t i s up and running27 void setup ( )28 {29 pinMode ( re lay , OUTPUT) ;3031 // Open s e r i a l communications and wai t f o r por t to open :32 S e r i a l . begin (9600) ;33 while ( ! S e r i a l )34 {35 ; // wai t f o r s e r i a l por t to connect36 }3738 S e r i a l . p r i n t ( ” I n i t i a l i z i n g SD card . . . ” ) ;39 pinMode ( ch ipSe l e c t , OUTPUT) ; // make sure t ha t the
d e f a u l t ch ip s e l e c t pin i s s e t to output4041 i f ( ! SD. begin ( c h i p S e l e c t ) ) // see i f the card i s
pre sen t and can be i n i t i a l i z e d :42 {43 S e r i a l . p r i n t l n ( ”Card f a i l e d , or not pre sent ” ) ;44 return ; // don ’ t do anyth ing more :45 }46 S e r i a l . p r i n t l n ( ” card i n i t i a l i z e d . ” ) ; //we ’ re good !47 }4849 //main loop o f program : c o l l e c t s data from a l l s ensors
and wr i t e s to the SD card50 void loop ( )51 {52 f loat pressureV = getPre s sure ( ) ; // ge t analog pre s sure
read ing53 f loat pre s su r e = (2 . 5167∗ ( pressureV ) ) − 2 5 5 . 2 ; // use
convers ion to conver t v o l t a g e to pre s sure in hPa54 i f ( p r e s su r e < cutPress ) // i f the read pres sure i s l e s s
than the pre s sure we want to cut at :55 {56 counter++; // increa se counter by 157 i f ( counter > 10) // only once the counter i s 10 does
the cutdown mechanism engage ,58 // t h i s p reven t s a s p a r a t i c data po in t from
a c c i d e n t a l l y s e t t i n g o f f our cutdown mechanism59 {
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60 d i g i t a l W r i t e ( re lay , HIGH) ; // sends power to ther e l a y pin , thus engaging the cutdown mechanism
61 }62 }636465 f loat d i s t anc e = getDis tance ( ) ; // ge t the d i s t ance in
inches from the motion sensor6667 double temperatureV = getTemperature ( ) ; // ge t the raw
analog output from the temperature sensor68 double temperature = (1/− .04364) ∗ l og ( (10000∗ ( (5∗
69 // ˆ convers ion o f raw temperature v o l t a g e to c e l s i u sva lue
7071 f loat supplyVolt = 5 . 0 ; // cons tant f o r power (5V)72 f loat HIH4030 Value= getHumidity ( ) ; // ge t raw d i g i t a l
v o l t a g e va lue f o r humidi ty7374 f loat vo l tage = HIH4030 Value /1023 . ∗ supplyVolt ; //
conver t to the analog s c a l e75 f loat sensorRH = 161 .0 ∗ vo l tage / supplyVolt − 2 5 . 8 ; //
conver t to raw humidity va lue (%)76 f loat trueRH = sensorRH / (1 .0546 − 0 .0026 ∗
temperature ) ; // temperature adjustment to ge t t ruehumidity
7778 F i l e da taF i l e = SD. open ( ” data . txt ” , FILE WRITE) ; //open
up the data f i l e7980 // i f the f i l e i s a v a i l a b l e , wr i t e to i t :81 i f ( da taF i l e ) {82 dataF i l e . p r i n t ( ”P: ” ) ;83 dataF i l e . p r i n t ( p r e s su r e ) ;84 da taF i l e . p r i n t ( ”hPa @ ” ) ;85 dataF i l e . p r i n t ( pressureV ) ;86 dataF i l e . p r i n t ( ”V, ” ) ;87 dataF i l e . p r i n t ( ”T: ” ) ;88 dataF i l e . p r i n t ( temperature ) ;89 da taF i l e . p r i n t ( ”C @ ” ) ;90 dataF i l e . p r i n t ( temperatureV ) ;91 dataF i l e . p r i n t ( ”V, ” ) ;92 dataF i l e . p r i n t ( ”H: ” ) ;93 dataF i l e . p r i n t ( trueRH ) ;
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94 dataF i l e . p r i n t ( ”% @ ” ) ;95 dataF i l e . p r i n t ( HIH4030 Value ) ;96 dataF i l e . p r i n t ( ”V, ” ) ;97 dataF i l e . p r i n t ( ”D: ” ) ;98 dataF i l e . p r i n t ( d i s t anc e ) ;99 dataF i l e . p r i n t l n ( ” in ” ) ;
100 dataF i l e . c l o s e ( ) ;101102 // p r i n t to the s e r i a l por t too so we can see whats
be ing wr i t t en to the t e s t f i l e :103 S e r i a l . p r i n t ( ”P: ” ) ;104 S e r i a l . p r i n t ( p r e s su r e ) ;105 S e r i a l . p r i n t ( ”hPa @ ” ) ;106 S e r i a l . p r i n t ( pressureV ) ;107 S e r i a l . p r i n t ( ”V, ” ) ;108 S e r i a l . p r i n t ( ”T: ” ) ;109 S e r i a l . p r i n t ( temperature ) ;110 S e r i a l . p r i n t ( ”C @ ” ) ;111 S e r i a l . p r i n t ( temperatureV ) ;112 S e r i a l . p r i n t ( ”V, ” ) ;113 S e r i a l . p r i n t ( ”H: ” ) ;114 S e r i a l . p r i n t ( trueRH ) ;115 S e r i a l . p r i n t ( ”% @ ” ) ;116 S e r i a l . p r i n t ( HIH4030 Value ) ;117 S e r i a l . p r i n t ( ”V, ” ) ;118 S e r i a l . p r i n t ( ”D: ” ) ;119 S e r i a l . p r i n t ( d i s t anc e ) ;120 S e r i a l . p r i n t l n ( ” in ” ) ;121 }122123 // i f the f i l e i sn ’ t open , pop up an error :124 else125 {126 S e r i a l . p r i n t l n ( ” e r r o r opening data . txt ” ) ;127 }128129 de lay (1000) ; // de lay between each wr i t e so t ha t we dont
cut o f f data wr i t i n g130 }131132 /∗133 methods t ha t g e t raw vo l t a g e va l u e s from a l l s ensors :134 getTemperature ( ) ;135 getHumidity ( ) ;136 ge tPres sure ( ) ;137 ge tDi s tance () ;
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138 ∗/139140 f loat getTemperature ( )141 {142 int voltageReading = analogRead ( temperaturePin ) ; //
reads v o l t a g e drop over the temperature sensor143 return voltageReading ;144 }145146147 f loat getHumidity ( )148 {149 f loat supplyVolt = 5 . 0 ;150151 // read the va lue from the sensor :152 int HIH4030 Value = analogRead ( humidityPin ) ;153 return HIH4030 Value ;154155156 }157158 f loat ge tPre s sure ( )159 {160 // read v o l t a g e va lue from the pres sure pin161 f loat vo l tage = analogRead ( pres sureP in ) ;162 return vo l tage ;163 }164165 f loat getDi s tance ( )166 {167168 f loat sum = 0 ;169 long anVolt , inches , cm ;170 int avgrange = 60 ;171 f loat s en so rva lue ;172173 // averages 60 va l u e s from the motion sensor ( our motion
sensor was known to be174 //somewhat innacurate at t imes . Thus we took 60
read ings and took the average in order175 // to ge t a more accura te va lue from the sensor .176 for ( int i = 0 ; i < avgrange ; i++)177 {178 //Used to read in the analog v o l t a g e output t ha t i s
be ing sen t by the MaxSonar dev i c e .
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179 // Sca le f a c t o r i s (Vcc/512) per inch . A 5V supp lyy i e l d s ˜9.8mV/ in
180 //Arduino analog pin goes from 0 to 1024 , so theva lue has to be d i v i d ed by 2 to ge t the a c t ua linches
181 s enso rva lue = analogRead ( d i s tancePin ) ;182 f loat i nchva lue = (254 . 0/1024 . 0 ) ∗2 .0∗ s en so rva lue ;183 //sums up 60 read ings from the sensor184 sum += inchva lue ;185 de lay (10) ;186 }187188 // d i v i d e s the sum by 60 to ge t the average read in
va lue189 f loat averagedInches = sum/ avgrange ;190 de lay (500) ;191 return averagedInches ;192 }
13.2 Radio anc GPS System Code
1 /∗2 GPS and Transmit t ing Code3 Written by Wil l Baldwin and N i kh i l Bhatia4 December 14 th , 201356 Receives GPS coord ina t e s and t ransmi t s them to a
handheld rad io in the f o l l ow i n g format :7 $$Will Launch , ID #,time , l a t i t u d e , l o n g i t u d e ∗checksum89 ∗/
10111213 #include <S o f t w a r e S e r i a l . h>14 #include <s t r i n g . h>15 #include <u t i l / crc16 . h>1617 S o f t w a r e S e r i a l g p s S e r i a l (10 , 11) ; // i n i t i a l i z e TX and RX
pins1819 const int s e n t e nc e S i z e = 80 ;20 St r ing l a t i t u d e ;21 St r ing l ong i tude ;22 char sentence [ s e n t e n c e S i z e ] ;
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2324 void setup ( )25 {26 //Begin S e r i a l and g p sS e r i a l a t 9600 baud ra t e27 S e r i a l . begin (9600) ;28 g p s S e r i a l . begin (9600) ;29 }3031 void loop ( )32 {33 stat ic int i = 0 ;34 i f ( g p s S e r i a l . a v a i l a b l e ( ) ) // check to see i f GPS i s
p rope r l y hooked up and v a l i d35 {36 char ch = g p s S e r i a l . read ( ) ; // read in GPS output3738 // i f GPS i s ou t pu t t i n g b lank s t r i n g s , remove them
from GPS output39 i f ( ch != ’ \n ’ && i < s e n t e nc e S i z e )40 {41 sentence [ i ] = ch ;42 i ++;43 }44 // i f not a b lank output , re format in t o r eadab l e
output45 else46 {47 sentence [ i ] = ’ \0 ’ ;48 i = 0 ;49 displayGPS ( ) ; // c a l l f o rmat t ing method5051 // cons t ruc t new s t r i n g in proper t r an sm i t t i n g format52 St r ing d a t a s t r i n g = ” $$Will Launch , 2 , 1 0 : 1 0 : 1 0 , ” ;53 d a t a s t r i n g += l a t i t u d e ;54 d a t a s t r i n g += ” , ” ;55 d a t a s t r i n g += long i tude ;56 d a t a s t r i n g += ” , ” ;57 char datastr ingChar [ 6 0 ] ;58 d a t a s t r i n g . toCharArray ( datastr ingChar , 60) ;5960 // c a l c u l a t e a checksum fo r the s t r i n g61 unsigned int CHECKSUM = gps CRC16 checksum (
datastr ingChar ) ;62 char checksum str [ 1 0 ] ;63 s p r i n t f ( checksum str , ”∗%04X\n” , CHECKSUM) ;
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64 s t r c a t ( datastr ingChar , checksum str ) ; // a t t achchecksum onto s t r i n g
6566 // transmi t r e cons t ruc t ed s t r i n g con ta in ing checksum67 d i g i t a l W r i t e (3 , HIGH) ;68 de lay (10) ;69 S e r i a l . p r i n t ( datastr ingChar ) ;70 de lay (10) ;71 d i g i t a l W r i t e (3 , LOW) ;72 de lay (10) ;73 }74 }75 }7677 /∗78 method g e t s and re formats output in t o proper readab l e
format79 ∗/80 void displayGPS ( )81 {82 char f i e l d [ 2 0 ] ;83 g e t F i e l d ( f i e l d , 0) ;84 i f ( strcmp ( f i e l d , ”$GPRMC” ) == 0)85 {86 // S e r i a l . p r i n t (” Lat : ”) ;87 l a t i t u d e = ”” ;88 g e t F i e l d ( f i e l d , 3) ; // number89 l a t i t u d e += f i e l d ;90 g e t F i e l d ( f i e l d , 4) ; // N/S91 l a t i t u d e += f i e l d ;92 // S e r i a l . p r i n t ( l a t i t u d e ) ;9394 // S e r i a l . p r i n t (” Long : ”) ;95 l ong i tude = ”” ;96 g e t F i e l d ( f i e l d , 5) ; // number97 l ong i tude += f i e l d ;98 g e t F i e l d ( f i e l d , 6) ; // E/W99 l ong i tude += f i e l d ;
100 // S e r i a l . p r i n t l n ( l on g i t u d e ) ;101 }102 }103104 /∗105 a s s i s t s g e t displayGPS method in read ing in from GPS106 ∗/107 void g e t F i e l d (char∗ bu f f e r , int index )
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108 {109 int sentencePos = 0 ;110 int f i e l d P o s = 0 ;111 int commaCount = 0 ;112 while ( sentencePos < s e n t e nc e S i z e )113 {114 i f ( sentence [ sentencePos ] == ’ , ’ )115 {116 commaCount ++;117 sentencePos ++;118 }119 i f (commaCount == index )120 {121 b u f f e r [ f i e l d P o s ] = sentence [ sentencePos ] ;122 f i e l d P o s ++;123 }124 sentencePos ++;125 }126 b u f f e r [ f i e l d P o s ] = ’ \0 ’ ;127 }128129130 /∗131 method c a l c u l a t e s the checksum fo r a g iven charac t e r
sequence132 ∗/133 u i n t 1 6 t gps CRC16 checksum (char ∗ s t r i n g )134 {135 s i z e t i ;136 u i n t 1 6 t c r c ;137 u i n t 8 t c ;138139 c rc = 0xFFFF;140141 // Ca l cu l a t e checksum ignor ing the f i r s t two $s142 for ( i = 2 ; i < s t r l e n ( s t r i n g ) ; i++)143 {144 c = s t r i n g [ i ] ;145 c rc = crc xmodem update ( crc , c ) ;146 }147148 return c r c ;149 }
