In this lab you will get acquainted with the IOLab device and its software. You will not need to turn in any report in this lab. There will be no grade issued for this lab. This is just a training exercise to make you familiar with the equipment. In this lab you will install necessary software, make a simple measurement and fit your experimental data to the equation.
Download and install the latest version of iOLab Application. You might want to watch appropriate short video that shows you how to do that.
Launch iOLab application. You might need to configure Windows Defender and/or other antivirus software on your computer to allow iOLab application to run.
Insert USB Dongle into USB slot on your computer. Notice that, once paired, “Dongle ID XXXXX – PAIRED” becomes highlighted in the gray status bar on the top of the application window.
Turn on your device. “Remote1: ID XXXXX” should light up on gray status bar.
Measurement.
Figure E.1
You are now ready to make your first measurement! Click on “Wheel” button and select “Position” option only. An empty graph of position vs time should appear. Place your device wheels down on some flat surface. Click on “Record” button and give your device a slight push. Observe the position vs. time data displayed on the screen. It will look similar to Figure E.1.
Figure E. 2 We encourage you to play with zoom and stats buttons (they are very useful).
Zoom in on some segment of the graph. Click Stats button and select a region of the data (see Figure E.2).
What is the meaning of the data shown in red?
Uploading the data to the cloud.
Figure E.3
In order to export the data for further analysis you need to first upload it to the cloud. Click on the cloud button in the menu. A new window appears (Figure E.3). If this is your first time logging into the cloud storage you need to “Register as a new user”. Note: this system is not related to GaTech. Create a new account with your email and brand-new password. Once you are logged in the cloud icon changes to . This means the system is ready to upload your data to the cloud. Click on this button. You will see the entry with your data in the cloud storage window. Click on this entry – you will see your data again (see Figure E.4). Now you may click on the download button and download your data from the cloud to your computer in CSV format for further processing. You will always follow this procedure (unload data to the cloud and then download data from there) whenever you need to download data to your computer for processing. The reason is that different sensors in the iOLab device work at different frequencies. For example, magnetometer works on frequency 80Hz (i.e. it records 80 measurements for the magnetic field each second). The position sensor works on frequency 100Hz. Uploading to the cloud automatically synchronizes all sensor data. Cloud also allows you to share your data. You may share with another student as well as with TA and instructor.
Figure E.4
Please click on “My groups” and click on “+”.This will create a group of users with whom you may share some of your data. Click on this group, edit its name, and add your instructor and your TA into this group by typing their emails. Creating such group does not mean members of this group will see all your data. If you want to share your data, type a user email or a group name in the “Share with” window under your data.
Fitting the data.
Figure E.5
You may use spreadsheet application of your choice to analyze/fit the data. In this tutorial I will show how to do this in Excel. Open CSV file in Excel. Delete data rows preceding first positive position data (when the device was at rest before you pushed it) and following the moment when it stopped (i.e. when position stopped changing).
We will fit our data to a parabola . Our parameters are a, b, and c. We need to find optimal values for these parameters so that this equation fits our data with minimal deviation (residual). You might also plot the data (see Figure E.5).
Figure E.6
Select some area on your spreadsheet and input arbitrary initial values for our parameters (Figure E.6).
Figure E.7
Calculate a new series in Excel using our equation and input parameters. The series will be a function of the parameters a, b, and c, and the independent variable, time. Note the use of $ in the cell references to keep the location of the a, b, and c cells in series calculations intact (Figure E.7).
Figure E.8
We will fit our data to the parabolic equation using Solver add-in in Excel. Solver will minimize one objective cell. We need to create an output that defines how well our function fits the data. We will create another series – residuals (difference between value calculated with our function and the actual data). Then we will create a single cell – the sum of residuals squared. Solver will minimize this sum.
Create the column of residuals (Figure E.8).
Figure E.9
Now calculate the sum of the residuals squared. You may use the SUMSQ function (Figure E.9).
Figure E.10
If you haven’t already activated the Solver add-in in your copy of Excel, you need to do it now. This step will guide you through this activation. If you already have Solver activated, you may go to the next step.
At first, we need to display the Developer Tab in the ribbon. Go to File>Options. In the window that opens, select Customize Ribbon (see Figure E.10).
Figure E. 11
Select the checkbox next to Developer in the List Box on the right side. Click OK (Figure E.11).
Figure E. 12
Now the Developer tab will show up in the ribbon (Figure E.12).
Figure E.13
Navigate to the Developer tab and select Excel Add-Ins (Figure E.13).
From the list of Add-Ins that appears, select the Solver Add-In and Click OK.
Figure E.14
Once enabled, Solver is accessed via the Data Tab (Figure E.14).
Figure E.15
Open the Solver and select the cell that contains the sum of the squares of the residuals as the objective, and the cells containing the values for a, b, and c parameters as the variable cells. Uncheck the box “Make Unconstrained Variable Non-Negative” (see Figure E.15). Click Solve.
Figure E.16
Now you should see a, b, and c parameters optimized and the sum of the residual’s squares should be very small. You may also plot the fitted function values on the same plot as the data to see how well the function fits the data – the two graphs virtually coincide (Figure 16).
What is the physical meaning of coefficients a, b, and c?
Go back to your data in cloud and click on Wheel-Acceleration option. Acceleration vs time graph will appear. Use statistics tool to select a time interval where the iOLab device was slowing (this is the interval you analyzed in the spreadsheet). Note the average value for the acceleration over this time interval shown above acceleration graph. Do you have a good agreement between this mean acceleration value and your calculated value for coefficient a?
(they are very useful).
Zoom in on some segment of the graph. Click Stats button and select a region of the data (see Figure E.2).
in the menu. A new window appears (Figure E.3). If this is your first time logging into the cloud storage you need to “Register as a new user”. Note: this system is not related to GaTech. Create a new account with your email and brand-new password. Once you are logged in the cloud icon changes to 
. This means the system is ready to upload your data to the cloud. Click on this button. You will see the entry with your data in the cloud storage window. Click on this entry – you will see your data again (see Figure E.4). Now you may click on the download button and download your data from the cloud to your computer in CSV format for further processing. You will always follow this procedure (unload data to the cloud and then download data from there) whenever you need to download data to your computer for processing. The reason is that different sensors in the iOLab device work at different frequencies. For example, magnetometer works on frequency 80Hz (i.e. it records 80 measurements for the magnetic field each second). The position sensor works on frequency 100Hz. Uploading to the cloud automatically synchronizes all sensor data. Cloud also allows you to share your data. You may share with another student as well as with TA and instructor.
. Our parameters are a, b, and c. We need to find optimal values for these parameters so that this equation fits our data with minimal deviation (residual). You might also plot the data (see Figure E.5).
